Massive lets users pay for premium features, content, or services with background computing power, rather than directly or with personal attention and data

Massive

massive

Massive is a decentralized ZK verification network service focused on achieving mass adoption for Web3. It aims to alleviate or even solve some of the key issues currently facing the industry. Here’s a breakdown: Mass Adoption: Massive could attract more users The sector is actively exploring ways to attract more traditional users and resources. Massive takes a novel approach by starting with mobile phones, a device most users are familiar with. By employing a “Verify to Earn” incentive mechanism and simplifying operations, Massive aims to draw more participants. This strategy helps newcomers gradually understand and join the Web3 industry, continuously injecting fresh blood into the sector. Web3 Highly Effective and Cheap: Massive could work as a settlement layer of blockchain Currently, all Rollup solutions based on ZK technology face delays in state confirmation on Layer1 (L1) due to cost and security concerns. This is typically addressed through proof aggregation technology and verification delays. introduces a solution that ensures Layer2 (L2)states can be decentralized and verified immediately after proof generation, significantly reducing the time for state transition confirmation. The verified state is then synchronized to L1, ensuring a swift and secure process. Massive Capital Efficiency: Massive could improve profits Nodes in the POS (Proof of Stake) network can join through staking and re-staking. If approach is reused, the POS consensus network can achieve Ethereum-level security. Massive supports staking and re-staking of various token types and offers flexible staking schemes tailored to different ecosystem types. Eigenlayer’s Modular Design: Massive could complete the modularity The emergence of Massive further advances the modular design of blockchain. It can be specifically divided into ZKRollup (off-chain computation), DA (Data Availability — off-chain transaction storage), ZKVaaS (Zero-Knowledge Verification as a Service — off-chain verification), and L1 (state updates and consensus). Keywords: Zero Knowledge, Mobile devices, Staking, Re-staking, Modularity, POS Introduction In essence, the blockchain industry is currently plagued by a crucial question: "How do we attract more traditional users to this sector?" Even though we witnessed a historical moment in January when a BTC spot ETF was approved, allowing some traditional investors to trade BTC in a compliant manner, the influx of new users and resources still falls far short of the industry's urgent need for fresh participants. Simply opening up investment opportunities can only bring in some investors; achieving mass adoption requires different strategies. Some believe gaming could be the key to reaching this goal, others see potential in social media, and still, others think AI could pave the way. Regardless of the method, it's clear that industry insiders are all striving for mass adoption of blockchain. A recent event that caught my attention was Starkware's STRK token airdrop, which highlighted a significant fact: some developers outside of the usual crypto circles began to explore and show interest in entering the industry. This interest was sparked because Starkware conducted an airdrop to contributors of certain GitHub repositories, developers who might not have known about blockchain previously but became interested due to this event. Another application that left a strong impression on me is StepN, an app that became popular in the last bull market for its "earn while you run" concept. Users simply needed to purchase a pair of virtual shoes and then could earn rewards by running a very straightforward proposition daily. This led to a surge in user numbers and effectively broke into new user demographics. These examples underscore applications or infrastructure projects capable of attracting new users to the industry. To draw new users, the following characteristics are necessary: Simple operation, easy for users to get started; Low hardware requirements; An incentive mechanism. Both examples satisfy the first criteria: GitHub is familiar to developers, and mobile phones are familiar to general users. They also meet the second criteria, requiring either a computer or a mobile phone. The third criteria is met as well, with one offering "contribute to earn" and the other "running to earn." However, to continuously attract new users, sustainable incentives are essential. For Starkware, continuous token airdrops may not be viable; likewise, for StepN, perpetual mining and selling are also unsustainable. Thus, for an application to sustainably attract new users and hold long-term value, it must inherently sustain its appeal. Massive serves as an infrastructure service aimed at sustainably attracting new users to achieve the goal of mass adoption. It can support all ZK chain services, whether ZK layer1, ZK layer2, or ZK layer3, introducing new users to these ZK chains, enhancing system security, reducing operational costs, and improving capital efficiency. Architecture Massive is a POS (Proof of Stake) consensus network that primarily utilizes mobile devices as its nodes. Users are required to download the official app on their mobile devices, which supports both iOS and Android, the two leading operating systems. The architectural framework is outlined as follows (Fig.1): To become a node, users can fall into one of the following two categories: New users without any cryptocurrency assets can initially join the network. Their accumulated rewards must reach a certain amount before they can start unlocking subsequent mining rewards. Users already possessing some cryptocurrency assets can stake these assets to become a node on the Massive network. Depending on the underlying L1 blockchain, users can stake different assets. For example, in a Massive network serving BTC L2/L3, users can stake BRC20 and BTC assets. For Ethereum-based L2/L3 services, users can stake ERC20 and ETH assets. The wallet will integrate several mainstream ZK technology stacks for verification, such as plonky2, plonky3, and boojum, all of which belong to the STARK family. Following market trends, support for mainstream algorithms from the SNARK family, such as Halo2 or Nova, will be iteratively introduced. Mobile nodes that have completed staking will form a POS network to provide Timely Settlement for all Layer 2s and Layer 3s. If there is an excessive number of participating users, sharding technology can be utilized to form multiple independent POS networks according to specific standards. Provide Timely Settlement As mentioned earlier, Massive is not solely focused on attracting users; it also aims to address some of the current issues in the industry. Among these, the confirmation time for ZK L2s/L3s is a frequently discussed issue. Before we delve into this, let's take a look at the main solutions for ZK L2s as illustrated in the following diagram (Fig.2): It's evident that in the design of most L2 solutions, there's a need to aggregate a sufficient number of proofs on L2 and then send them to Ethereum for verification. This approach is adopted to reduce costs. Even with this premise, the aggregated proofs sent to L1 must wait for a certain period before calling the Verify contract to alter the global state, a measure taken from a security standpoint, although this delay can be configured. Therefore, it can be concluded that a L2 transaction, to be finally confirmed, requires a waiting period of between 2 to 23 hours. Until then, the validity of the proofs is verified only by a centralized sequencer. The diagram below (Fig.3) illustrates the current situation where, after their generation, proofs will be verified. Therefore, the primary intention behind Massive's design is to ensure that, before a proof is verified on L1, it goes through a verification process by a decentralized network, so everyone can verify now. It's important to note that if the POS network used for verifying the proof is provided by Eigenlayer's AVS ( ) service, then this POS network possesses the same level of security as Ethereum. Ultimately, only the latest global state needs to be updated on Ethereum. This aspect also offers insights into the modular design evolution discussed in later chapters. Actively Validated Services After incorporating Massive, the entire process flow for L2s could be transformed as shown in the following diagram (Fig.4): By extracting the ZK verify function from L1 and placing trust in the security of the Massive network, then adding a challenge mechanism to reduce the probability of Massive acting maliciously, the entire system's security will depend on the security of the Massive network. If the ecosystem of these ZK L2s is more finance-oriented, Massive could be built on EigenLayer's AVS to ensure the cost of acting maliciously is sufficiently high. Conversely, if the ecosystem of these ZK L2s is related to gaming or social scenarios, then a basic Massive construction would suffice. Capital Efficiency Staking and re-staking have recently become very popular concepts, focusing on capital efficiency. Reutilizing staked assets to achieve compound interest is an attractive economic mechanism currently seen in platforms like Blast and Manta. Unlike these schemes, Massive offers a novel destination for native assets across various networks, as well as for staked assets, by allowing them to become nodes within the Massive network through staking and re-staking mechanisms. Since the Massive network can provide more users, lower costs, and improved security for ZK L2s/L3s, nodes within the Massive network will share in the network maintenance profits, embodying the "verify to earn" concept. Based on the actual circumstances of ZK L2s/L3s, different security levels of ZKVaaS can be chosen. The security level depends on the total amount staked and the number of nodes in the network. New Modular Design As mentioned earlier, Massive, from a certain perspective, further changes the process of blockchain modular design. Before Massive, modular design mainly consisted of execution modularization, with various Rollups solutions, and Data Availability (DA) modularization, with various DA solutions, leaving only verification, storage, and consensus functions on L1. After the introduction of Massive, modular design will evolve to include execution modularization, DA modularization, and verification modularization, with only storage and consensus remaining on L1. This is logical since verification itself is part of computation. Given that execution modularization has already moved computation off-chain, then only storage and consensus should remain on-chain. The specifics are illustrated in the following diagram (Fig.6): If verification remains on Layer 1 (L1), the specific consensus process involves each node executing, verifying proofs, and updating the state. However, if we extract the verification process and assign it to a separate network for consensus, the L1 consensus process would then only involve updates to storage. Under the latest modular design, existing L1 nodes will no longer undertake any computational tasks. They will only handle transactions related to the update of the global state and then execute the consensus process. There are two main reasons for this approach: As mentioned in previous sections, considering costs and security, the execution of verification can be significantly delayed. Therefore, extracting it and utilizing the Massive network for verification not only achieves rapid validation but also reduces the hardware requirements for verification nodes, making it easier for users to connect. The security of the separate Massive network is ensured by the amount of staked assets and the number of nodes. Compared to the original scheme, this might sacrifice a certain level of security (which depends on the value of the staked assets) but, in return, offers significant architectural advantages. The Ecosystem of Massive Leveraging the three core features of mobile phone mining, staking/re-staking, and Timely Settlement, Massive has the potential to become the largest network, providing safe, efficient, and low-cost services for a variety of ZK L2s/L3s. Additionally, due to its extremely low barrier to entry and profit effects, it will inject a significant number of real users into the industry. Massive's vision is to facilitate massive adoption within the industry. Mobile mining represents a highly exploratory practice. Through straightforward operations, lower thresholds, and continuous earnings, it aims to utilize the computational power of smartphones. According to statistics, the global sales of smartphones exceeded 1 billion units in 2023. Solana and Aptos have also successively launched their own Web3 phones. Through the Massive network, these devices will be leveraged. Reference Eigenlayer whitepaper: https://docs.eigenlayer.xyz/assets/files/EigenLayer_WhitePaper-88c47923ca0319870c611decd6e562ad.pdf Scroll explorer: https://scrollscan.com/batch/86321 Polygon explorer: https://zkevm.polygonscan.com/batches Zksync contract: https://etherscan.io/address/0xa0425d71cB1D6fb80E65a5361a04096E0672De03#readContract Starkware explorer: https://voyager.online/block/572773 Halo2: https://github.com/zcash/halo2 Nova: https://eprint.iacr.org/2021/370 Celestia: https://docs.celestia.org/learn/how-celestia-works/overview

Unveiling the Technical Vision Behind Massive: Decentralized, Cheap, Fair, and More

বিশালের পিছনে প্রযুক্তিগত দৃষ্টিভঙ্গি উন্মোচন করা: বিকেন্দ্রীভূত, সস্তা, ন্যায্য এবং আরও অনেক কিছু

Enthüllung der technischen Vision hinter Massive: Dezentralisiert, günstig, fair und mehr

Revelando la visión técnica detrás de Massive: descentralizado, barato, justo y más

Dévoiler la vision technique derrière Massive : décentralisé, bon marché, équitable et plus encore

बड़े पैमाने पर तकनीकी दृष्टि का अनावरण: विकेंद्रीकृत, सस्ता, निष्पक्ष और बहुत कुछ

Massive の背後にある技術的ビジョンを明らかにする: 分散化、安価、公正など

Massive의 기술적 비전 공개: 분산화, 저렴함, 공정함 등

Revelando a visão técnica por trás do Massive: descentralizado, barato, justo e muito mais

Раскрытие технического видения Massive: децентрализованное, дешевое, справедливое и многое другое

Massive'ın Arkasındaki Teknik Vizyonu Ortaya Çıkarıyoruz: Merkezi Olmayan, Ucuz, Adil ve Daha Fazlası

Tiết lộ tầm nhìn kỹ thuật đằng sau Massive: Phi tập trung, giá rẻ, công bằng và hơn thế nữa

揭示 Massive 背后的技术愿景：去中心化、廉价、公平等等

Authors:
(1) Hoon Kim, Beeble AI, and contributed equally to this work;
(2) Minje Jang, Beeble AI, and contributed equally to this work;
(3) Wonjun Yoon, Beeble AI, and contributed equally to this work;
(4) Jisoo Lee, Beeble AI, and contributed equally to this work;
(5) Donghyun Na, Beeble AI, and contributed equally to this work;
(6) Sanghyun Woo, New York University, and contributed equally to this work. Editor's Note: This is Part 8 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below. Table of Links Abstract and 1. Introduction
2. Related Work
3. SwitchLight and 3.1. Preliminaries
3.2. Problem Formulation
3.3. Architecture
3.4. Objectives
4. Multi-Masked Autoencoder Pre-training
5. Data
6. Experiments
7. Conclusion Appendix A. Implementation Details
B. User Study Interface
C. Video Demonstration
D. Additional Qualitative Results & References 5. Data We constructed the OLAT (One Light at a Time) dataset using a light stage [10, 49] equipped with 137 programmable LED lights and 7 frontal-viewing cameras. Our dataset comprises images of 287 subjects, with each subject being captured in up to 15 different poses, resulting in a total of 29,705 OLAT sequences. We sourced HDRI dataset from several publicly available archives. Specifically, we acquired 559 HDRI maps from Polyhaven, 76 from Noah Witchell, 364 from HDRMAPS, 129 from iHDRI, and 34 from eisklotz. In addition, we incorporated synthetic HDRIs created using the method proposed in [31]. During training, HDRIs are randomly selected with equal probability from either real-world or synthetic collections. We produced training pairs by projecting the sampled source and target lighting maps onto the reflectance fields of the OLAT images [10]. To derive the ground truth intrinsics, we applied the photometric stereo method [51] and obtained normal and albedo maps. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. Authors: (1) Hoon Kim, Beeble AI, and contributed equally to this work; (2) Minje Jang, Beeble AI, and contributed equally to this work; (3) Wonjun Yoon, Beeble AI, and contributed equally to this work; (4) Jisoo Lee, Beeble AI, and contributed equally to this work; (5) Donghyun Na, Beeble AI, and contributed equally to this work; (6) Sanghyun Woo, New York University, and contributed equally to this work. Authors: Authors: (1) Hoon Kim, Beeble AI, and contributed equally to this work; (2) Minje Jang, Beeble AI, and contributed equally to this work; (3) Wonjun Yoon, Beeble AI, and contributed equally to this work; (4) Jisoo Lee, Beeble AI, and contributed equally to this work; (5) Donghyun Na, Beeble AI, and contributed equally to this work; (6) Sanghyun Woo, New York University, and contributed equally to this work. Editor's Note: This is Part 8 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below. Editor's Note: This is Part 8 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below. Editor's Note: This is Part 8 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below. Editor's Note: This is Part 8 of 14 of a study introducing a method for improving how light and shadows can be applied to human portraits in digital images. Read the rest below. Table of Links Abstract and 1. Introduction 2. Related Work 3. SwitchLight and 3.1. Preliminaries 3.2. Problem Formulation 3.3. Architecture 3.4. Objectives 4. Multi-Masked Autoencoder Pre-training 5. Data 6. Experiments 7. Conclusion Abstract and 1. Introduction Abstract and 1. Introduction 2. Related Work 2. Related Work 3. SwitchLight and 3.1. Preliminaries 3. SwitchLight and 3.1. Preliminaries 3.2. Problem Formulation 3.2. Problem Formulation 3.3. Architecture 3.3. Architecture 3.4. Objectives 3.4. Objectives 4. Multi-Masked Autoencoder Pre-training 4. Multi-Masked Autoencoder Pre-training 5. Data 5. Data 6. Experiments 6. Experiments 7. Conclusion 7. Conclusion Appendix A. Implementation Details B. User Study Interface C. Video Demonstration D. Additional Qualitative Results & References A. Implementation Details A. Implementation Details B. User Study Interface B. User Study Interface C. Video Demonstration C. Video Demonstration D. Additional Qualitative Results & References D. Additional Qualitative Results & References 5. Data We constructed the OLAT (One Light at a Time) dataset using a light stage [10, 49] equipped with 137 programmable LED lights and 7 frontal-viewing cameras. Our dataset comprises images of 287 subjects, with each subject being captured in up to 15 different poses, resulting in a total of 29,705 OLAT sequences. We sourced HDRI dataset from several publicly available archives. Specifically, we acquired 559 HDRI maps from Polyhaven, 76 from Noah Witchell, 364 from HDRMAPS, 129 from iHDRI, and 34 from eisklotz. In addition, we incorporated synthetic HDRIs created using the method proposed in [31]. During training, HDRIs are randomly selected with equal probability from either real-world or synthetic collections. We produced training pairs by projecting the sampled source and target lighting maps onto the reflectance fields of the OLAT images [10]. To derive the ground truth intrinsics, we applied the photometric stereo method [51] and obtained normal and albedo maps. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. available on arxiv

Researchers Build Massive AI Training Dataset to Perfect Lighting on Faces

AUSTIN, TX, September 18th, 2024/CyberNewsWire/--Research indicates that an infostealer malware infection is often a precursor to a ransomware attack SpyCloud, the leader in Cybercrime Analytics, today announced new cybersecurity research highlighting the growing and alarming threat of infostealers – a type of malware designed to exfiltrate digital identity data, login credentials, and session cookies from infected devices. SpyCloud’s latest findings reveal the staggering scale of identity exposure caused by infostealers, the influence this type of malware has had on the surge in ransomware incidents, and the profound implications for businesses worldwide. Massive Scale of Identity Exposure Creates New Risks According to SpyCloud, 61% of all data breaches in the past year were malware-related, with infostealers responsible for the theft of 343.78 million credentials. These stolen credentials are then sold in criminal communities for use in further attacks. The research also found that one in five individuals has been a victim of an infostealer infection. Each infection, on average, exposes 10-25 third-party business application credentials, creating fertile ground for further access and exploitation, particularly by ransomware operators. “Our latest findings reveal a critical shift in the cybersecurity landscape,” said Damon Fleury, chief product officer at SpyCloud. “Infostealers have become the go-to tool for cybercriminals, with their ability to exfiltrate valuable data in a matter of seconds, creating a runway for cyberattacks like ransomware off the vast amounts of stolen access to SSO, VPN, admin panels, and other critical applications.” Infostealers: The Precursor To Ransomware Attacks The link between infostealers and ransomware is becoming increasingly evident. Through deep analysis of recaptured infostealer logs, SpyCloud discovered a worrying trend: companies with employees and contractors who are infected with infostealer malware are significantly more likely to experience a ransomware attack. In fact, nearly one-third of companies that suffered a ransomware attack last year had previously experienced an infostealer infection. According to the report, this is based on publicly known incidents and confirmed ransomware events. The true exposure is potentially even higher as not all ransomware incidents are made publicly available. “The correlation between infostealer infections and subsequent ransomware attacks is a wake-up call for businesses,” said Trevor Hilligoss, vice president of SpyCloud Labs, SpyCloud. “However, this field is incredibly complex and fast-moving. This year, we’re seeing new infostealers families that make use of expanded capabilities such as advanced encryption to stay stealthy or the ability to restore expired authentication cookies for more persistent access.” The Rise of Malware-as-a-Service And Account Takeover Attacks The infostealer threat is further exacerbated by the rise of Malware-as-a-Service (MaaS). This off-the-shelf model allows even low-skilled cybercriminals to purchase and deploy sophisticated malware, including infostealers, with ease. Through MaaS, these criminals can acquire fresh and accurate identity data in bulk, fueling the cycle of cybercrime. SpyCloud’s findings also shed light on the evolution of account takeover (ATO) attacks, powered by infostealers. Unlike traditional ATO, which relies on stolen credentials (username and password combinations), next-generation ATO leverages stolen session cookies to sidestep traditional authentication methods in what is known as session hijacking. By taking over these already-authenticated sessions, cybercriminals can mimic legitimate users and infiltrate networks undetected. This method significantly increases the success rate of attacks and poses a severe threat to organizational security. “The sheer volume of credentials and session cookies being siphoned by infostealers is staggering,” said Hilligoss. “In the last 90 days alone, SpyCloud has recaptured over 5.4 billion stolen cookie records – with an average of nearly 2,000 exposed records per infected device. This vast trove of data is increasingly used by ransomware operators and initial access brokers to facilitate their attacks, highlighting the need for advanced defense strategies.” Antivirus, MFA And Traditional Defenses Are No Longer Enough At least 54% of devices infected with infostealers in the first half of 2024 had antivirus or endpoint detection and response (EDR) solutions installed, underscoring the limitations of traditional cybersecurity measures in combating the techniques used by modern cybercriminals. Furthermore, infostealers and session hijacking attacks render multi-factor authentication (MFA) and passwordless authentication methods like passkeys ineffective. By hijacking already-authenticated sessions, cybercriminals can impersonate legitimate users and side-step even the most robust authentication methods. The call for next-generation cybersecurity The findings from SpyCloud make it clear: traditional malware mitigation is no longer sufficient and ignoring the problem only exacerbates the impact on businesses. Organizations must move beyond merely removing infections and focus on remediating the long-term risks posed by exposed data. This includes resetting compromised application credentials and invalidating session cookies siphoned by infostealers. By understanding the risks posed by infostealers and working to mitigate the data that has been exfiltrated, organizations are able to limit the likelihood of devastating cyberattacks such as ransomware that stem from this stolen data. SpyCloud remains committed to helping organizations navigate these challenges and safeguard their digital assets. Readers can download the full 2024 Malware and Ransomware Defense Report. To learn more about how SpyCloud helps organizations defend against ransomware, readers can visit https://spycloud.com/use-case/ransomware-prevention/. About the SpyCloud 2024 Malware and Ransomware Defense Report For this fourth annual report, SpyCloud surveyed 510 individuals in active cybersecurity roles within organizations in the US and the UK with at least 500 employees. The report examines the top concerns and real-life impacts of ransomware, including popular entry points, ransom payments, and the cumulative costs of these attacks to the business. It also highlights key cyber threat prevention strategies and future security priorities identified by these experts. About SpyCloud SpyCloud transforms recaptured darknet data to disrupt cybercrime. Its automated identity threat protection solutions leverage advanced analytics to proactively prevent ransomware and account takeover, safeguard employee and consumer accounts, and accelerate cybercrime investigations. SpyCloud's data from breaches, malware-infected devices, and successful phishes also powers many popular dark web monitoring and identity theft protection offerings. Customers include more than half of the Fortune 10, along with hundreds of global enterprises, mid-sized companies, and government agencies worldwide. Headquartered in Austin, TX, SpyCloud is home to more than 200 cybersecurity experts whose mission is to protect businesses and consumers from the stolen identity data criminals are using to target them now. To learn more and see insights on their company’s exposed data, readers can visit spycloud.com Contact EVP, Public Relations Katie Hanusik REQ on behalf of SpyCloud spycloud@req.co This story was distributed as a release by Cyberwire under HackerNoon’s Business Blogging Program. Learn more about the program here AUSTIN, TX, September 18th, 2024/CyberNewsWire/--Research indicates that an infostealer malware infection is often a precursor to a ransomware attack SpyCloud, the leader in Cybercrime Analytics, today announced new cybersecurity research highlighting the growing and alarming threat of infostealers – a type of malware designed to exfiltrate digital identity data, login credentials, and session cookies from infected devices. SpyCloud’s latest findings reveal the staggering scale of identity exposure caused by infostealers, the influence this type of malware has had on the surge in ransomware incidents, and the profound implications for businesses worldwide. Massive Scale of Identity Exposure Creates New Risks According to SpyCloud, 61% of all data breaches in the past year were malware-related, with infostealers responsible for the theft of 343.78 million credentials. These stolen credentials are then sold in criminal communities for use in further attacks. The research also found that one in five individuals has been a victim of an infostealer infection. Each infection, on average, exposes 10-25 third-party business application credentials, creating fertile ground for further access and exploitation, particularly by ransomware operators. “Our latest findings reveal a critical shift in the cybersecurity landscape,” said Damon Fleury, chief product officer at SpyCloud. “Our latest findings reveal a critical shift in the cybersecurity landscape,” said Damon Fleury, chief product officer at SpyCloud. “Infostealers have become the go-to tool for cybercriminals, with their ability to exfiltrate valuable data in a matter of seconds, creating a runway for cyberattacks like ransomware off the vast amounts of stolen access to SSO, VPN, admin panels, and other critical applications.” “Infostealers have become the go-to tool for cybercriminals, with their ability to exfiltrate valuable data in a matter of seconds, creating a runway for cyberattacks like ransomware off the vast amounts of stolen access to SSO, VPN, admin panels, and other critical applications.” Infostealers: The Precursor To Ransomware Attacks The link between infostealers and ransomware is becoming increasingly evident. Through deep analysis of recaptured infostealer logs, SpyCloud discovered a worrying trend: companies with employees and contractors who are infected with infostealer malware are significantly more likely to experience a ransomware attack. In fact, nearly one-third of companies that suffered a ransomware attack last year had previously experienced an infostealer infection. According to the report, this is based on publicly known incidents and confirmed ransomware events. The true exposure is potentially even higher as not all ransomware incidents are made publicly available. “The correlation between infostealer infections and subsequent ransomware attacks is a wake-up call for businesses,” said Trevor Hilligoss, vice president of SpyCloud Labs, SpyCloud. “The correlation between infostealer infections and subsequent ransomware attacks is a wake-up call for businesses,” said Trevor Hilligoss, vice president of SpyCloud Labs, SpyCloud. “However, this field is incredibly complex and fast-moving. This year, we’re seeing new infostealers families that make use of expanded capabilities such as advanced encryption to stay stealthy or the ability to restore expired authentication cookies for more persistent access.” “However, this field is incredibly complex and fast-moving. This year, we’re seeing new infostealers families that make use of expanded capabilities such as advanced encryption to stay stealthy or the ability to restore expired authentication cookies for more persistent access.” The Rise of Malware-as-a-Service And Account Takeover Attacks The infostealer threat is further exacerbated by the rise of Malware-as-a-Service (MaaS). This off-the-shelf model allows even low-skilled cybercriminals to purchase and deploy sophisticated malware, including infostealers, with ease. Through MaaS, these criminals can acquire fresh and accurate identity data in bulk, fueling the cycle of cybercrime. SpyCloud’s findings also shed light on the evolution of account takeover (ATO) attacks, powered by infostealers. Unlike traditional ATO, which relies on stolen credentials (username and password combinations), next-generation ATO leverages stolen session cookies to sidestep traditional authentication methods in what is known as session hijacking. By taking over these already-authenticated sessions, cybercriminals can mimic legitimate users and infiltrate networks undetected. This method significantly increases the success rate of attacks and poses a severe threat to organizational security. “The sheer volume of credentials and session cookies being siphoned by infostealers is staggering,” said Hilligoss. “The sheer volume of credentials and session cookies being siphoned by infostealers is staggering,” said Hilligoss. “In the last 90 days alone, SpyCloud has recaptured over 5.4 billion stolen cookie records – with an average of nearly 2,000 exposed records per infected device. This vast trove of data is increasingly used by ransomware operators and initial access brokers to facilitate their attacks, highlighting the need for advanced defense strategies.” “In the last 90 days alone, SpyCloud has recaptured over 5.4 billion stolen cookie records – with an average of nearly 2,000 exposed records per infected device. This vast trove of data is increasingly used by ransomware operators and initial access brokers to facilitate their attacks, highlighting the need for advanced defense strategies.” Antivirus, MFA And Traditional Defenses Are No Longer Enough At least 54% of devices infected with infostealers in the first half of 2024 had antivirus or endpoint detection and response (EDR) solutions installed, underscoring the limitations of traditional cybersecurity measures in combating the techniques used by modern cybercriminals. Furthermore, infostealers and session hijacking attacks render multi-factor authentication (MFA) and passwordless authentication methods like passkeys ineffective. By hijacking already-authenticated sessions, cybercriminals can impersonate legitimate users and side-step even the most robust authentication methods. The call for next-generation cybersecurity The findings from SpyCloud make it clear: traditional malware mitigation is no longer sufficient and ignoring the problem only exacerbates the impact on businesses. Organizations must move beyond merely removing infections and focus on remediating the long-term risks posed by exposed data. This includes resetting compromised application credentials and invalidating session cookies siphoned by infostealers. By understanding the risks posed by infostealers and working to mitigate the data that has been exfiltrated, organizations are able to limit the likelihood of devastating cyberattacks such as ransomware that stem from this stolen data. SpyCloud remains committed to helping organizations navigate these challenges and safeguard their digital assets. Readers can download the full 2024 Malware and Ransomware Defense Report . 2024 Malware and Ransomware Defense Report 2024 Malware and Ransomware Defense Report To learn more about how SpyCloud helps organizations defend against ransomware, readers can visit https://spycloud.com/use-case/ransomware-prevention/ . https://spycloud.com/use-case/ransomware-prevention/ https://spycloud.com/use-case/ransomware-prevention/ About the SpyCloud 2024 Malware and Ransomware Defense Report For this fourth annual report , SpyCloud surveyed 510 individuals in active cybersecurity roles within organizations in the US and the UK with at least 500 employees. fourth annual report fourth annual report The report examines the top concerns and real-life impacts of ransomware, including popular entry points, ransom payments, and the cumulative costs of these attacks to the business. It also highlights key cyber threat prevention strategies and future security priorities identified by these experts. About SpyCloud SpyCloud transforms recaptured darknet data to disrupt cybercrime. Its automated identity threat protection solutions leverage advanced analytics to proactively prevent ransomware and account takeover, safeguard employee and consumer accounts, and accelerate cybercrime investigations. SpyCloud SpyCloud SpyCloud's data from breaches, malware-infected devices, and successful phishes also powers many popular dark web monitoring and identity theft protection offerings. Customers include more than half of the Fortune 10, along with hundreds of global enterprises, mid-sized companies, and government agencies worldwide. Headquartered in Austin, TX, SpyCloud is home to more than 200 cybersecurity experts whose mission is to protect businesses and consumers from the stolen identity data criminals are using to target them now. To learn more and see insights on their company’s exposed data, readers can visit spycloud.com spycloud.com spycloud.com Contact EVP, Public Relations Katie Hanusik REQ on behalf of SpyCloud spycloud@req.co This story was distributed as a release by Cyberwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Cyberwire under HackerNoon’s Business Blogging Program. Learn more about the program here here

SpyCloud Unveils Massive Scale Of Identity Exposure, Highlighting Need For Advanced Security Measure

SpyCloud تكشف عن نطاق هائل من الكشف عن الهوية، مما يسلط الضوء على الحاجة إلى تدابير أمنية متقدمة

SpyCloud ukax Jach’a Escala de Exposición de Identidad ukar uñacht’ayi, Medida de Seguridad Avanzada ukan munatapat uñacht’ayi

SpyCloud revela una escala masiva de exposición de identidad, lo que pone de relieve la necesidad de medidas de seguridad avanzadas

SpyCloud مقیاس عظیمی از قرار گرفتن در معرض هویت را معرفی می کند، که نیاز به اقدامات امنیتی پیشرفته را برجسته می کند

स्पाईक्लाउड ने पहचान उजागर करने के बड़े पैमाने का खुलासा किया, उन्नत सुरक्षा उपाय की आवश्यकता पर प्रकाश डाला

SpyCloud が大規模な個人情報漏洩を発表、高度なセキュリティ対策の必要性を浮き彫りに

SpyCloud გამოაქვეყნებს პირადობის ექსპოზიციის მასიურ მასშტაბებს, ხაზს უსვამს უსაფრთხოების გაფართოებული ზომების საჭიროებას

SpyCloud විසින් අනන්‍යතා නිරාවරණයේ දැවැන්ත පරිමාණයක් එළිදක්වයි, උසස් ආරක්ෂක පියවරක අවශ්‍යතාවය ඉස්මතු කරයි

СпиЦлоуд открива огромну скалу откривања идентитета, наглашавајући потребу за напредном мјером сигурности

SpyCloud Inafichua Kiwango Kikubwa cha Ufichuaji wa Utambulisho, Ikiangazia Haja ya Kipimo cha Kina Usalama

ஸ்பைக்ளவுட் அடையாள வெளிப்பாட்டின் பாரிய அளவை வெளிப்படுத்துகிறது, மேம்பட்ட பாதுகாப்பு நடவடிக்கையின் தேவையை எடுத்துக்காட்டுகிறது

SpyCloud tiết lộ quy mô lớn về việc tiết lộ danh tính, làm nổi bật nhu cầu về biện pháp bảo mật tiên tiến

Just when you thought Google couldn’t get any more insufferable, a federal judge throws down a ruling that could rock the very foundation of the tech giant's empire! On Monday, US District Judge Amit Mehta smacked Google with a colossal antitrust defeat, declaring that the company’s search business isn’t just dominant—it’s downright monopolistic. This isn’t just a slap on the wrist; it’s a full-blown smackdown aimed at the heart of Google’s search engine hegemony. Judge Mehta didn’t mince words. He laid it out straight: Google’s not just playing the search game; it’s rigging it to keep everyone else out. Through a web of exclusive contracts and under-the-table deals with major players like Apple, Google has cemented its stranglehold on search—squeezing out competitors like Microsoft’s Bing and DuckDuckGo. And let’s be honest, it’s not like Google’s been subtle about it. They’ve spent billions on these deals, effectively ensuring that when you need to find something online, Google’s your only choice. The court ruling paints a grim picture of Google’s power trip, citing anticompetitive practices and outrageous search ad pricing as key problems. The judge isn’t just wagging a finger; he’s laying the groundwork for potentially groundbreaking remedies. Think “choice screens” and other measures that could force Google to give rivals a fighting chance. And don’t think this is just about search ads—oh no. This decision is setting the stage for a new era of tech antitrust battles. Remember Microsoft’s antitrust debacle back in the day? This case is being compared to that. It’s a landmark moment, echoing historic rulings like the breakups of AT&T and Standard Oil. Attorney General Merrick Garland and the White House are dancing in the streets, calling this a triumph for the American people and a win for fair competition. But don’t expect Google to take this lying down. The company’s already gearing up for an appeal, insisting it’s still the best search engine out there. Classic Google, right? Meanwhile, the ruling is stirring the pot for future tech antitrust cases. With other giants like Apple and Amazon facing their own legal heat, this Google decision might just be the tip of the iceberg. It could also make waves in the Justice Department’s case against Ticketmaster. So, buckle up—Google’s legal rollercoaster is far from over, and the reverberations are going to be felt across the tech world for years to come. Just when you thought Google couldn’t get any more insufferable, a federal judge throws down a ruling that could rock the very foundation of the tech giant's empire! On Monday, US District Judge Amit Mehta smacked Google with a colossal antitrust defeat, declaring that the company’s search business isn’t just dominant—it’s downright monopolistic. This isn’t just a slap on the wrist; it’s a full-blown smackdown aimed at the heart of Google’s search engine hegemony. Judge Mehta didn’t mince words. He laid it out straight: Google’s not just playing the search game; it’s rigging it to keep everyone else out. Through a web of exclusive contracts and under-the-table deals with major players like Apple, Google has cemented its stranglehold on search—squeezing out competitors like Microsoft’s Bing and DuckDuckGo. And let’s be honest, it’s not like Google’s been subtle about it. They’ve spent billions on these deals, effectively ensuring that when you need to find something online, Google’s your only choice. The court ruling paints a grim picture of Google’s power trip, citing anticompetitive practices and outrageous search ad pricing as key problems. The judge isn’t just wagging a finger; he’s laying the groundwork for potentially groundbreaking remedies. Think “choice screens” and other measures that could force Google to give rivals a fighting chance. And don’t think this is just about search ads—oh no. This decision is setting the stage for a new era of tech antitrust battles. Remember Microsoft’s antitrust debacle back in the day? This case is being compared to that. It’s a landmark moment, echoing historic rulings like the breakups of AT&T and Standard Oil. Attorney General Merrick Garland and the White House are dancing in the streets, calling this a triumph for the American people and a win for fair competition. But don’t expect Google to take this lying down. The company’s already gearing up for an appeal, insisting it’s still the best search engine out there. Classic Google, right? Meanwhile, the ruling is stirring the pot for future tech antitrust cases. With other giants like Apple and Amazon facing their own legal heat, this Google decision might just be the tip of the iceberg. It could also make waves in the Justice Department’s case against Ticketmaster. So, buckle up—Google’s legal rollercoaster is far from over, and the reverberations are going to be felt across the tech world for years to come.

Google Slammed with Massive Antitrust Defeat: Monopoly Power Under Fire

LOS ANGELES, United States, July 30th, 2024/Chainwire/--DSCVR, the largest web3 social media and community-building platform, announces the launch of Canvas, a groundbreaking framework that enables developers to effortlessly build and integrate custom applications directly into DSCVR’s social feeds. With just a few tweaks any web application can be made into a Canvas application. Combined with DSCVR’s API, Canvas provides an easy-to-build framework to launch and distribute embedded apps on the DSCVR platform. Canvas apps can have rich interfaces previously unseen in Web3 social that extend beyond the existing frame standards of buttons and textboxes to support games, interactive media, and more. Developers can find viral distribution for Canvases in feed, making them instantly accessible to the community and scaling them across hundreds of thousands of users. With Canvas, building, launching, and managing embedded apps has never been easier or more innovative, offering end users dynamic and rewarding experiences. A New Era of Web3 Embedded App Development DSCVR Canvas introduces a framework that makes app creation accessible to a breadth of developers, from seasoned engineers to students just learning Javascript. The platform offers a user-friendly interface that simplifies the development process, allowing anyone to build dynamic, interactive applications without advanced technical skills. Canvas is also built to support existing Frames and Solana Blinks so developers in these ecosystems can easily share their apps on DSCVR. “We’re excited to introduce Canvas to our developer community,” said Rick Porter, CEO of DSCVR. “Our goal is to empower developers with the framework they need to create and scale apps within the DSCVR ecosystem for the benefit of our users. Canvas is a significant step towards realizing that vision.” Key Features of DSCVR Canvas: Transactions: Canvas applications can interact directly with user wallets which are already paired with DSCVR accounts, creating new utility for NFTs and fungible totokens. Seamless Integration: Apps built on Canvas integrate effortlessly with the DSCVR platform, leveraging robust APIs and the speed of the platform for smooth performance. Enhanced Performance: Designed for scalability, Canvas supports everything from simple ways to earn crypto, tipping, to games and other complex applications. Rich Media Support: Users can incorporate images, videos, and interactive elements to create engaging and immersive apps. Driving Innovation in Web3 Social MeMedia With more canvases being built on DSCVR, users will enjoy a wide range of fun and engaging experiences directly within their social feed. From interactive games and trading platforms to token minting, DSCVR Canvas Embedded Apps will enrich the user experience, making social interactions more dynamic and rewarding. These apps will allow users to easily monetize their activities, participate in immersive gaming and trade digital assets, transforming the way they interact on the platform. At the same time, this is an opportunity for developers to gain distribution for their applications to an audience of hundreds of thousands of users. Launch Event and Community Engagement To celebrate the launch, DSCVR will be organizing a global hackathon on August 5th hosted by Dorahacks to encourage experimentation and creativity among its developer community. Sponsors include Metaplex, Matrica, Helius, Spiderswap and Tweed. Notable judges include Austen Federa, Jon Wong, and Pedro Miranda from the Solana Foundation as well as Josh Finer from Solana Ventures. “We’re committed to supporting our developer community and providing them with the support and tools they need to succeed,” added Rick Porter. “DSCVR Canvas is a testament to our dedication to innovation in the Web3 social ecosystem.” About DSCVR With over 500k monthly unique visitors, DSCVR (pronounced “Discover”) is a Web3 social network combining the usability of a Web2-style social app with crypto technology that unlocks ownership, monetization and distribution for users, creators, and projects. Through its native crypto functionality, DSCVR rewards users and supercharges community-building, while its API allows developers and partners to build applications that target through the social graph, distribute through the feed, and monetize in posts. DSCVR’s seed investors include Polychain Capital, Upfront Ventures, BDMI, Shima Capital, Tomahawk VC, and Fyrfly Venture Partners. Users can follow DSCVR on Twitter (X) for more updates. Contact Press Inquiries Cher Park DSCVR press@dscvr.one This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. LOS ANGELES, United States, July 30th, 2024/Chainwire/--DSCVR, the largest web3 social media and community-building platform, announces the launch of Canvas, a groundbreaking framework that enables developers to effortlessly build and integrate custom applications directly into DSCVR’s social feeds. With just a few tweaks any web application can be made into a Canvas application. Combined with DSCVR’s API, Canvas provides an easy-to-build framework to launch and distribute embedded apps on the DSCVR platform. Canvas apps can have rich interfaces previously unseen in Web3 social that extend beyond the existing frame standards of buttons and textboxes to support games, interactive media, and more. Developers can find viral distribution for Canvases in feed, making them instantly accessible to the community and scaling them across hundreds of thousands of users. With Canvas, building, launching, and managing embedded apps has never been easier or more innovative, offering end users dynamic and rewarding experiences. A New Era of Web3 Embedded App Development DSCVR Canvas introduces a framework that makes app creation accessible to a breadth of developers, from seasoned engineers to students just learning Javascript. The platform offers a user-friendly interface that simplifies the development process, allowing anyone to build dynamic, interactive applications without advanced technical skills. Canvas is also built to support existing Frames and Solana Blinks so developers in these ecosystems can easily share their apps on DSCVR. “We’re excited to introduce Canvas to our developer community,” said Rick Porter, CEO of DSCVR. “Our goal is to empower developers with the framework they need to create and scale apps within the DSCVR ecosystem for the benefit of our users. Canvas is a significant step towards realizing that vision.” “We’re excited to introduce Canvas to our developer community,” said Rick Porter, CEO of DSCVR. “Our goal is to empower developers with the framework they need to create and scale apps within the DSCVR ecosystem for the benefit of our users. Canvas is a significant step towards realizing that vision.” Key Features of DSCVR Canvas: Transactions: Canvas applications can interact directly with user wallets which are already paired with DSCVR accounts, creating new utility for NFTs and fungible totokens. Transactions: Seamless Integration: Apps built on Canvas integrate effortlessly with the DSCVR platform, leveraging robust APIs and the speed of the platform for smooth performance. Enhanced Performance: Designed for scalability, Canvas supports everything from simple ways to earn crypto, tipping, to games and other complex applications. Rich Media Support: Users can incorporate images, videos, and interactive elements to create engaging and immersive apps. Driving Innovation in Web3 Social MeMedia With more canvases being built on DSCVR, users will enjoy a wide range of fun and engaging experiences directly within their social feed. From interactive games and trading platforms to token minting, DSCVR Canvas Embedded Apps will enrich the user experience, making social interactions more dynamic and rewarding. These apps will allow users to easily monetize their activities, participate in immersive gaming and trade digital assets, transforming the way they interact on the platform. At the same time, this is an opportunity for developers to gain distribution for their applications to an audience of hundreds of thousands of users. Launch Event and Community Engagement To celebrate the launch, DSCVR will be organizing a global hackathon on August 5th hosted by Dorahacks to encourage experimentation and creativity among its developer community. Sponsors include Metaplex, Matrica, Helius, Spiderswap and Tweed. Notable judges include Austen Federa, Jon Wong, and Pedro Miranda from the Solana Foundation as well as Josh Finer from Solana Ventures. “We’re committed to supporting our developer community and providing them with the support and tools they need to succeed,” added Rick Porter. “DSCVR Canvas is a testament to our dedication to innovation in the Web3 social ecosystem.” “We’re committed to supporting our developer community and providing them with the support and tools they need to succeed,” added Rick Porter. “DSCVR Canvas is a testament to our dedication to innovation in the Web3 social ecosystem.” About DSCVR With over 500k monthly unique visitors, DSCVR (pronounced “Discover”) is a Web3 social network combining the usability of a Web2-style social app with crypto technology that unlocks ownership, monetization and distribution for users, creators, and projects. DSCVR Through its native crypto functionality, DSCVR rewards users and supercharges community-building, while its API allows developers and partners to build applications that target through the social graph, distribute through the feed, and monetize in posts. DSCVR’s seed investors include Polychain Capital, Upfront Ventures, BDMI, Shima Capital, Tomahawk VC, and Fyrfly Venture Partners. Users can follow DSCVR on Twitter (X) for more updates. Twitter Contact Press Inquiries Cher Park DSCVR press@dscvr.one This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

DSCVR Launches Canvas: A Massive Leap For Web3 Social Embedded Apps

DSCVR ক্যানভাস চালু করেছে: Web3 সোশ্যাল এমবেডেড অ্যাপের জন্য একটি বিশাল ঝাঁপ

DSCVR bringt Canvas auf den Markt: Ein gewaltiger Sprung für eingebettete soziale Web3-Apps

DSCVR lanza Canvas: un gran salto para las aplicaciones sociales integradas en Web3

DSCVR lance Canvas : un grand pas en avant pour les applications sociales Web3 intégrées

डीएससीवीआर ने कैनवास लॉन्च किया: वेब3 सोशल एम्बेडेड ऐप्स के लिए एक बड़ी छलांग

DSCVR が Canvas をリリース: Web3 ソーシャル埋め込みアプリの大きな飛躍

DSCVR, 캔버스 출시: Web3 소셜 임베디드 앱의 대대적인 도약

DSCVR lança Canvas: um grande salto para aplicativos sociais incorporados na Web3

DSCVR запускает Canvas: огромный скачок для встраиваемых приложений Web3 Social

DSCVR Canvas'ı Piyasaya Sürüyor: Web3 Sosyal Gömülü Uygulamalar İçin Büyük Bir Atılım

DSCVR ra mắt Canvas: Bước nhảy vọt lớn cho các ứng dụng nhúng trên mạng xã hội Web3

DSCVR 推出 Canvas：Web3 社交嵌入式应用的一次巨大飞跃

What's Inside the Recent Massive Google Search API Leak?

সাম্প্রতিক ব্যাপক Google অনুসন্ধান API লিক ভিতরে কি?

Was steckt hinter dem jüngsten massiven API-Leck bei der Google-Suche?

¿Qué hay dentro de la reciente filtración masiva de la API de búsqueda de Google?

Que contient la récente fuite massive de l’API de recherche Google ?

हाल ही में हुए बड़े पैमाने पर गूगल सर्च एपीआई लीक के पीछे क्या है?

最近の大規模な Google 検索 API 漏洩の内容とは?

최근 대규모 Google 검색 API 유출 내용은 무엇입니까?

O que há por dentro do recente vazamento massivo da API de pesquisa do Google?

Что скрывается за недавней массовой утечкой API поиска Google?

Son Zamanlardaki Büyük Google Arama API Sızıntısının İçinde Neler Var?

Có gì bên trong vụ rò rỉ API tìm kiếm lớn gần đây của Google?

最近大规模的 Google 搜索 API 泄漏到底是怎么回事？

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan;
(2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan;
(3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan;
(4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan;
(5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Setup Result Summary and Discussion Appendix A. Dual Energy Formalism B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime References A. DUAL ENERGY FORMALISM This paper is available on arxiv under CC 4.0 license. Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Abstract and Intro Setup Setup Result Result Summary and Discussion Summary and Discussion Appendix Appendix A. Dual Energy Formalism A. Dual Energy Formalism B. Convergence of Results B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime C. Change of the Mass Loss Rate in MHD Regime References References A. DUAL ENERGY FORMALISM

Magnetic Wind From a Massive White Dwarf Merger: Dual Energy Formalism

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan;
(2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan;
(3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan;
(4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan;
(5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Setup Result Summary and Discussion Appendix A. Dual Energy Formalism B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime References REFERENCES Briggs, G. P., Ferrario, L., Tout, C. A., Wickramasinghe, D. T., & Hurley, J. R. 2015, MNRAS, 447, 1713, doi: 10.1093/mnras/stu2539 Bryan, G. L., Norman, M. L., Stone, J. M., Cen, R., & Ostriker, J. P. 1995, Computer Physics Communications, 89, 149, doi: 10.1016/0010-4655(94)00191-4 Bucciantini, N., Thompson, T. A., Arons, J., Quataert, E., & Del Zanna, L. 2006, MNRAS, 368, 1717, doi: 10.1111/j.1365-2966.2006.10217.x Caiazzo, I., Burdge, K. B., Fuller, J., et al. 2021, Nature, 595, 39, doi: 10.1038/s41586-021-03615-y Cheng, S., Cummings, J. D., M´enard, B., & Toonen, S. 2020, ApJ, 891, 160, doi: 10.3847/1538-4357/ab733c Contopoulos, I., & Spitkovsky, A. 2006, ApJ, 643, 1139, doi: 10.1086/501161 Ferreira, J. M. 2000, MNRAS, 316, 647, doi: 10.1046/j.1365-8711.2000.03540.x Garc´ıa-Berro, E., Lor´en-Aguilar, P., Aznar-Sigu´an, G., et al. 2012, ApJ, 749, 25, doi: 10.1088/0004-637X/749/1/25 Gvaramadze, V. V., Gr¨afener, G., Langer, N., et al. 2019, Nature, 569, 684, doi: 10.1038/s41586-019-1216-1 Iben, I., J., & Tutukov, A. V. 1984, ApJS, 54, 335, doi: 10.1086/190932 Iijima, H. 2016, PhD thesis, University of Tokyo, Department of Earth and Planetary Environmental Science Jardine, M., & Collier Cameron, A. 2019, MNRAS, 482, 2853, doi: 10.1093/mnras/sty2872 Kashiyama, K., Fujisawa, K., & Shigeyama, T. 2019, ApJ, 887, 39, doi: 10.3847/1538-4357/ab4e97 Kashiyama, K., Ioka, K., & Kawanaka, N. 2011, PhRvD, 83, 023002, doi: 10.1103/PhysRevD.83.023002 Kashiyama, K., & Murase, K. 2017, ApJL, 839, L3, doi: 10.3847/2041-8213/aa68e1 Kilic, M., Kosakowski, A., Moss, A. G., Bergeron, P., & Conly, A. A. 2021, ApJL, 923, L6, doi: 10.3847/2041-8213/ac3b60 Kirsten, F., Marcote, B., Nimmo, K., et al. 2022, Nature, 602, 585, doi: 10.1038/s41586-021-04354-w Ko, T., Suzuki, H., Kashiyama, K., et al. 2023, arXiv e-prints, arXiv:2304.14669, doi: 10.48550/arXiv.2304.14669 Kremer, K., Piro, A. L., & Li, D. 2021, ApJL, 917, L11, doi: 10.3847/2041-8213/ac13a0 Lu, W., Beniamini, P., & Kumar, P. 2022, MNRAS, 510, 1867, doi: 10.1093/mnras/stab3500 Lykou, F., Parker, Q. A., Ritter, A., et al. 2022, arXiv e-prints, arXiv:2208.03946, doi: 10.48550/arXiv.2208.03946 Matt, S. P., MacGregor, K. B., Pinsonneault, M. H., & Greene, T. P. 2012, ApJL, 754, L26, doi: 10.1088/2041-8205/754/2/L26 Michel, F. C. 1969, ApJ, 158, 727, doi: 10.1086/150233 Miyoshi, T., & Kusano, K. 2005, Journal of Computational Physics, 208, 315, doi: 10.1016/j.jcp.2005.02.017 Nomoto, K., & Iben, I., J. 1985, ApJ, 297, 531, doi: 10.1086/163547 Oskinova, L. M., Gvaramadze, V. V., Gr¨afener, G., Langer, N., & Todt, H. 2020, A&A, 644, L8, doi: 10.1051/0004-6361/202039232 Parker, E. N. 1965, SSRv, 4, 666, doi: 10.1007/BF00216273 Raives, M. J., Coleman, M. S. B., & Thompson, T. A. 2023, arXiv e-prints, arXiv:2302.05462, doi: 10.48550/arXiv.2302.05462 Ritter, A., Parker, Q. A., Lykou, F., et al. 2021, ApJL, 918, L33, doi: 10.3847/2041-8213/ac2253 Saio, H., & Nomoto, K. 2004, ApJ, 615, 444, doi: 10.1086/423976 Schwab, J. 2021, ApJ, 906, 53, doi: 10.3847/1538-4357/abc87e Schwab, J., Quataert, E., & Kasen, D. 2016, MNRAS, 463, 3461, doi: 10.1093/mnras/stw2249 Stone, J. M., Tomida, K., White, C. J., & Felker, K. G. 2020, The Astrophysical Journal Supplement Series, 249, 4, doi: 10.3847/1538-4365/ab929b Takasao, S., Tomida, K., Iwasaki, K., & Suzuki, T. K. 2019, ApJL, 878, L10, doi: 10.3847/2041-8213/ab22bb Tout, C. A., Wickramasinghe, D. T., Liebert, J., Ferrario, L., & Pringle, J. E. 2008, MNRAS, 387, 897, doi: 10.1111/j.1365-2966.2008.13291.x Townsend, R. H. D., & Owocki, S. P. 2005, MNRAS, 357, 251, doi: 10.1111/j.1365-2966.2005.08642.x Ud-Doula, A., Owocki, S. P., & Townsend, R. H. D. 2009, MNRAS, 392, 1022, doi: 10.1111/j.1365-2966.2008.14134.x Webbink, R. F. 1984, ApJ, 277, 355, doi: 10.1086/161701 Weber, E. J., & Davis, Leverett, J. 1967, ApJ, 148, 217, doi: 10.1086/149138 Wu, C., Xiong, H., Lin, J., et al. 2023, ApJL, 944, L54, doi: 10.3847/2041-8213/acb6f3 Yao, P. Z., Quataert, E., & Goulding, A. 2023, MNRAS, doi: 10.1093/mnras/stad1934 This paper is available on arxiv under CC 4.0 license. Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Abstract and Intro Setup Setup Result Result Summary and Discussion Summary and Discussion Appendix Appendix A. Dual Energy Formalism A. Dual Energy Formalism B. Convergence of Results B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime C. Change of the Mass Loss Rate in MHD Regime References References REFERENCES Briggs, G. P., Ferrario, L., Tout, C. A., Wickramasinghe, D. T., & Hurley, J. R. 2015, MNRAS, 447, 1713, doi: 10.1093/mnras/stu2539 Bryan, G. L., Norman, M. L., Stone, J. M., Cen, R., & Ostriker, J. P. 1995, Computer Physics Communications, 89, 149, doi: 10.1016/0010-4655(94)00191-4 Bucciantini, N., Thompson, T. A., Arons, J., Quataert, E., & Del Zanna, L. 2006, MNRAS, 368, 1717, doi: 10.1111/j.1365-2966.2006.10217.x Caiazzo, I., Burdge, K. B., Fuller, J., et al. 2021, Nature, 595, 39, doi: 10.1038/s41586-021-03615-y Cheng, S., Cummings, J. D., M´enard, B., & Toonen, S. 2020, ApJ, 891, 160, doi: 10.3847/1538-4357/ab733c Contopoulos, I., & Spitkovsky, A. 2006, ApJ, 643, 1139, doi: 10.1086/501161 Ferreira, J. M. 2000, MNRAS, 316, 647, doi: 10.1046/j.1365-8711.2000.03540.x Garc´ıa-Berro, E., Lor´en-Aguilar, P., Aznar-Sigu´an, G., et al. 2012, ApJ, 749, 25, doi: 10.1088/0004-637X/749/1/25 Gvaramadze, V. V., Gr¨afener, G., Langer, N., et al. 2019, Nature, 569, 684, doi: 10.1038/s41586-019-1216-1 Iben, I., J., & Tutukov, A. V. 1984, ApJS, 54, 335, doi: 10.1086/190932 Iijima, H. 2016, PhD thesis, University of Tokyo, Department of Earth and Planetary Environmental Science Jardine, M., & Collier Cameron, A. 2019, MNRAS, 482, 2853, doi: 10.1093/mnras/sty2872 Kashiyama, K., Fujisawa, K., & Shigeyama, T. 2019, ApJ, 887, 39, doi: 10.3847/1538-4357/ab4e97 Kashiyama, K., Ioka, K., & Kawanaka, N. 2011, PhRvD, 83, 023002, doi: 10.1103/PhysRevD.83.023002 Kashiyama, K., & Murase, K. 2017, ApJL, 839, L3, doi: 10.3847/2041-8213/aa68e1 Kilic, M., Kosakowski, A., Moss, A. G., Bergeron, P., & Conly, A. A. 2021, ApJL, 923, L6, doi: 10.3847/2041-8213/ac3b60 Kirsten, F., Marcote, B., Nimmo, K., et al. 2022, Nature, 602, 585, doi: 10.1038/s41586-021-04354-w Ko, T., Suzuki, H., Kashiyama, K., et al. 2023, arXiv e-prints, arXiv:2304.14669, doi: 10.48550/arXiv.2304.14669 Kremer, K., Piro, A. L., & Li, D. 2021, ApJL, 917, L11, doi: 10.3847/2041-8213/ac13a0 Lu, W., Beniamini, P., & Kumar, P. 2022, MNRAS, 510, 1867, doi: 10.1093/mnras/stab3500 Lykou, F., Parker, Q. A., Ritter, A., et al. 2022, arXiv e-prints, arXiv:2208.03946, doi: 10.48550/arXiv.2208.03946 Matt, S. P., MacGregor, K. B., Pinsonneault, M. H., & Greene, T. P. 2012, ApJL, 754, L26, doi: 10.1088/2041-8205/754/2/L26 Michel, F. C. 1969, ApJ, 158, 727, doi: 10.1086/150233 Miyoshi, T., & Kusano, K. 2005, Journal of Computational Physics, 208, 315, doi: 10.1016/j.jcp.2005.02.017 Nomoto, K., & Iben, I., J. 1985, ApJ, 297, 531, doi: 10.1086/163547 Oskinova, L. M., Gvaramadze, V. V., Gr¨afener, G., Langer, N., & Todt, H. 2020, A&A, 644, L8, doi: 10.1051/0004-6361/202039232 Parker, E. N. 1965, SSRv, 4, 666, doi: 10.1007/BF00216273 Raives, M. J., Coleman, M. S. B., & Thompson, T. A. 2023, arXiv e-prints, arXiv:2302.05462, doi: 10.48550/arXiv.2302.05462 Ritter, A., Parker, Q. A., Lykou, F., et al. 2021, ApJL, 918, L33, doi: 10.3847/2041-8213/ac2253 Saio, H., & Nomoto, K. 2004, ApJ, 615, 444, doi: 10.1086/423976 Schwab, J. 2021, ApJ, 906, 53, doi: 10.3847/1538-4357/abc87e Schwab, J., Quataert, E., & Kasen, D. 2016, MNRAS, 463, 3461, doi: 10.1093/mnras/stw2249 Stone, J. M., Tomida, K., White, C. J., & Felker, K. G. 2020, The Astrophysical Journal Supplement Series, 249, 4, doi: 10.3847/1538-4365/ab929b Takasao, S., Tomida, K., Iwasaki, K., & Suzuki, T. K. 2019, ApJL, 878, L10, doi: 10.3847/2041-8213/ab22bb Tout, C. A., Wickramasinghe, D. T., Liebert, J., Ferrario, L., & Pringle, J. E. 2008, MNRAS, 387, 897, doi: 10.1111/j.1365-2966.2008.13291.x Townsend, R. H. D., & Owocki, S. P. 2005, MNRAS, 357, 251, doi: 10.1111/j.1365-2966.2005.08642.x Ud-Doula, A., Owocki, S. P., & Townsend, R. H. D. 2009, MNRAS, 392, 1022, doi: 10.1111/j.1365-2966.2008.14134.x Webbink, R. F. 1984, ApJ, 277, 355, doi: 10.1086/161701 Weber, E. J., & Davis, Leverett, J. 1967, ApJ, 148, 217, doi: 10.1086/149138 Wu, C., Xiong, H., Lin, J., et al. 2023, ApJL, 944, L54, doi: 10.3847/2041-8213/acb6f3 Yao, P. Z., Quataert, E., & Goulding, A. 2023, MNRAS, doi: 10.1093/mnras/stad1934

Magnetic Wind From a Massive White Dwarf Merger: References

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan;
(2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan;
(3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan;
(4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan;
(5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Setup Result Summary and Discussion Appendix A. Dual Energy Formalism B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime References C. CHANGE OF THE MASS LOSS RATE IN MHD REGIME This paper is available on arxiv under CC 4.0 license. Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Abstract and Intro Setup Setup Result Result Summary and Discussion Summary and Discussion Appendix Appendix A. Dual Energy Formalism A. Dual Energy Formalism B. Convergence of Results B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime C. Change of the Mass Loss Rate in MHD Regime References References C. CHANGE OF THE MASS LOSS RATE IN MHD REGIME

Magnetic Wind From a Massive White Dwarf Merger: Change of the Mass Loss Rate in MHD Regime

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan;
(2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan;
(3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan;
(4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan;
(5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Setup Result Summary and Discussion Appendix A. Dual Energy Formalism B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime References 2. SETUP We conduct a series of numerical simulations of a rotating magnetic wind from a massive WD merger product with a stable nuclear burning occurring at the near surface region. We first describe the general numerical setup including the governing equations, the Riemann solver, the mesh decomposition, and the boundary conditions in Sec. 2.1. We then describe the source term that represents the injection of mass and internal energy at the near surface nuclear burning region in Sec. 2.2. Finally, we elaborate on setups related to magnetic fields. 2.1. Magnetohydrodynamic (MHD) equations We numerically integrate ideal MHD equations with central gravity; We use the HLLD approximate Riemann solver for the MHD equations (Miyoshi & Kusano 2005) with the secondorder piecewise linear reconstruction method (PLM). The time integration is carried out by the second-order RungeKutta method with Courant-Friedrich-Lewy number of 0.1. The computational domain is resolved with the mesh number of 128 for [0.9, 30] R∗ in the radial direction and 128 for [0, π] in the polar direction. We employ a non-uniform mesh in the radial direction, where the radial grid size is proportional to the radius. The fiducial value of the grid size ratio ∆r(i + 1)/∆r(i) is 1.02 so that the smallest cell size is 0.05, where i stands for the grid index. In this paper, we consider the cases with Ω∗ = [0.05, 0.07, 0.12, 0.16, 0.23, 0.35, 0.46] s−1, which correpsonds to ∼ 5-50 % of the mass shedding limit. In terms of the inner ghost cell’s density and pressure, we carefully prescribe their values to achieve a specific thermally-driven wind mass loss rate (see Sec. 2.2). Initially, we distribute a cold and homogeneous gas throughout the entire computational domain and inject the thermally-driven wind from the designated launching region. As the thermally-driven outflow reaches the outer boundary, we initiate an aligned dipole field at the inner boundary, facilitating the transformation of the wind into a rotating magnetic wind (see Sec. 2.3). 2.2. Wind launching region We initialize our simulation with a cold, homogeneous, isotropic and non-magnetized atmosphere, and set up a “wind launching region” [2] with a width of D near the WD surface, where the mass is injected to the computational domain to mimic the mass loading due to the carbon burning around the surface of massive WD merger product. To do that, we implement an isotropic relaxation function for both matter and energy source terms to update density and pressure in wind launching region: where ρ∗ and p∗ correspond to the density and pressure at the outer edge of the wind launching region. The actual value of the relaxation timescale τ is chosen to satisfy the condition, 2.3. Rotating magnetic wind The launched gas will then corotate with the rotating magnetic field, and the magnetic torque, which depends on the resultant magnetospheric structure and the polar angle, can also contribute to the wind acceleration in addition to the thermal pressure gradient. As a result, we expect a rotating magnetic wind to start blowing in an angle dependent manner, and relax to a quasi-steady state when it reaches to the outer boundary. We simulate the rotating magnetic wind for a few 10 × the spin period after turning on the magnetic field. [2] Note that this is originally called damping layer in the context of accreting stellar system (see Takasao et al. 2019) This paper is available on arxiv under CC 4.0 license. Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Abstract and Intro Setup Setup Result Result Summary and Discussion Summary and Discussion Appendix Appendix A. Dual Energy Formalism A. Dual Energy Formalism B. Convergence of Results B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime C. Change of the Mass Loss Rate in MHD Regime References References 2. SETUP We conduct a series of numerical simulations of a rotating magnetic wind from a massive WD merger product with a stable nuclear burning occurring at the near surface region. We first describe the general numerical setup including the governing equations, the Riemann solver, the mesh decomposition, and the boundary conditions in Sec. 2.1. We then describe the source term that represents the injection of mass and internal energy at the near surface nuclear burning region in Sec. 2.2. Finally, we elaborate on setups related to magnetic fields. 2.1. Magnetohydrodynamic (MHD) equations Magnetohydrodynamic (MHD) equations We numerically integrate ideal MHD equations with central gravity; We use the HLLD approximate Riemann solver for the MHD equations (Miyoshi & Kusano 2005) with the secondorder piecewise linear reconstruction method (PLM). The time integration is carried out by the second-order RungeKutta method with Courant-Friedrich-Lewy number of 0.1. The computational domain is resolved with the mesh number of 128 for [0.9, 30] R∗ in the radial direction and 128 for [0, π] in the polar direction. We employ a non-uniform mesh in the radial direction, where the radial grid size is proportional to the radius. The fiducial value of the grid size ratio ∆r( i + 1)/∆r( i ) is 1.02 so that the smallest cell size is 0.05, where i stands for the grid index. i i i In this paper, we consider the cases with Ω∗ = [0.05, 0.07, 0.12, 0.16, 0.23, 0.35, 0.46] s−1, which correpsonds to ∼ 5-50 % of the mass shedding limit. In terms of the inner ghost cell’s density and pressure, we carefully prescribe their values to achieve a specific thermally-driven wind mass loss rate (see Sec. 2.2). Initially, we distribute a cold and homogeneous gas throughout the entire computational domain and inject the thermally-driven wind from the designated launching region. As the thermally-driven outflow reaches the outer boundary, we initiate an aligned dipole field at the inner boundary, facilitating the transformation of the wind into a rotating magnetic wind (see Sec. 2.3). 2.2. Wind launching region Wind launching region We initialize our simulation with a cold, homogeneous, isotropic and non-magnetized atmosphere, and set up a “wind launching region” [2] with a width of D near the WD surface, where the mass is injected to the computational domain to mimic the mass loading due to the carbon burning around the surface of massive WD merger product. To do that, we implement an isotropic relaxation function for both matter and energy source terms to update density and pressure in wind launching region: where ρ∗ and p∗ correspond to the density and pressure at the outer edge of the wind launching region. The actual value of the relaxation timescale τ is chosen to satisfy the condition, 2.3. Rotating magnetic wind Rotating magnetic wind The launched gas will then corotate with the rotating magnetic field, and the magnetic torque, which depends on the resultant magnetospheric structure and the polar angle, can also contribute to the wind acceleration in addition to the thermal pressure gradient. As a result, we expect a rotating magnetic wind to start blowing in an angle dependent manner, and relax to a quasi-steady state when it reaches to the outer boundary. We simulate the rotating magnetic wind for a few 10 × the spin period after turning on the magnetic field. [2] Note that this is originally called damping layer in the context of accreting stellar system (see Takasao et al. 2019)

Magnetic Wind From a Massive White Dwarf Merger: Setup

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan;
(2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan;
(3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan;
(4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan;
(5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Setup Result Summary and Discussion Appendix A. Dual Energy Formalism B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime References B. CONVERGENCE OF RESULTS The convergence of our rotating magnetic wind solutions against both mesh resolution and the size of wind launching region have been confirmed. We show the results for our fiducial model (B1.5e6Ω0.23) in Fig. 5. In the top panel we increase the spatial resolution for 4 times both along the radial and latitudinal direction, while in the bottom panel we change the thickness of wind launching region from D = 0.6 R∗ (fiducial value we are using, corresponding to 9 cells) to D = 0.3 R∗ (which corresponds to 5 cells). We check the time evolution of the spindown torque T for both changes, and zoom into the first few eruptive peaks to show the difference clearly. We find that the time-averaged value as well as the power-law trend converge with respect to both the spatial resolution and the size of the wind launching region, but the time variability vary. This is due to the fact that the reconnections in our simulations are mainly modulated by numerical resistivities. This paper is available on arxiv under CC 4.0 license. Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Abstract and Intro Setup Setup Result Result Summary and Discussion Summary and Discussion Appendix Appendix A. Dual Energy Formalism A. Dual Energy Formalism B. Convergence of Results B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime C. Change of the Mass Loss Rate in MHD Regime References References B. CONVERGENCE OF RESULTS The convergence of our rotating magnetic wind solutions against both mesh resolution and the size of wind launching region have been confirmed. We show the results for our fiducial model (B1.5e6Ω0.23) in Fig. 5. In the top panel we increase the spatial resolution for 4 times both along the radial and latitudinal direction, while in the bottom panel we change the thickness of wind launching region from D = 0.6 R∗ (fiducial value we are using, corresponding to 9 cells) to D = 0.3 R∗ (which corresponds to 5 cells). We check the time evolution of the spindown torque T for both changes, and zoom into the first few eruptive peaks to show the difference clearly. We find that the time-averaged value as well as the power-law trend converge with respect to both the spatial resolution and the size of the wind launching region, but the time variability vary. This is due to the fact that the reconnections in our simulations are mainly modulated by numerical resistivities.

Magnetic Wind From a Massive White Dwarf Merger: Convergence of Results

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan;
(2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan;
(3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan;
(4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan;
(5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Setup Result Summary and Discussion Appendix A. Dual Energy Formalism B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime References 3. RESULT Table. 3 shows a summary of our simulation. A model BxΩy corresponds to the case with B∗ = x and Ω∗ = y in the cgs unit. When the rotating magnetic wind becomes quasi-steady, it can be characterized by the mass loss rate wind luminosity and spindown torque estimated at the outer boundary. As we show later, the strength of rotating magnetic winds can be characterized by a dimensionless parameter Hereafter we take B1.5e6Ω0.23 with σ = 34.3 as the fiducial model, and first show the multi-dimensional structure of the rotating magnetic wind in Sec. 3.1. We then investigate the time variability of the system primarily focusing on the impacts of quasi-periodic eruption along with the equatorial plane in Sec. 3.2. Finally, we show how the time-averaged spin-down torque scales with system parameters in Sec. 3.3. 3.1. Anisotropic wind structure In the equatorial direction (80◦ ≲ θ ≲ 100◦), magnetic fields are closed at small radii, forming a corotating magnetosphere. Beyond the last closed loop, the magnetic field lines are open with a predominant toroidal component, having opposite polarities with respect to the equatorial plane. The transition of the magnetic field configuration is mediated by reconnection occurring at around the tip of the last closed loop, or the Y point. As can be observed from the top-right panel of Fig. 1, the plasma beta in this transition region is higher than those along the open magnetic fields, implying that the gas is trapped mainly by magnetic tensions. In this high plasma-beta region sandwiched by low plasma beta regions, gases are pinched and radially accelerated in the reconnection region, eventually become supersonic at around r ∼ 5 R∗. The latitudinal angle dependence of the wind at the outer boundary is illustrated in Fig. 2, where the gray shaded regions represent the dynamical range of radial velocity (top-left), luminosity (top-right), torque (bottom-left), and mass loss rate (bottom-right). As described in the previous paragraphs, radial velocities in the near-equatorial direction can reach and transiently exceed the Michel velocity (represented by the horizontal dotted line) during eruptions caused by reconnection at the Y-point. Consequently, the wind luminosity, dominated by the radial kinetic term, also exhibits a sharp peak in the equatorial direction. On the other hand, the torque is primarily exerted by corotation with the magnetic fields and reaches its peak slightly off the equatorial plane (θ ∼ 85◦), corresponding to the edge of the concave shape of the Alfven radius. 3.2. Time variability The acceleration of the rotating magnetic wind in the equatorial direction occurs in a time-variable manner, associated with magnetic reconnection at the Y-point. Consequently, the overall flux of mass, energy, and angular momentum from the central WD can also vary with time. Fig. 3 displays the time evolution of the mass loss rate (M˙ ), luminosity (L), and torque (T) in our fiducial model. All quantities are normalized by their time-averaged values. The lower panel of Fig. 3, which provides a long-term perspective, reveals a recurrent eruptive behavior. A recurrent cycle consists of pre-eruption, reconnection, post-eruption phases: In the pre-eruption phase, gases injected into the near-equatorial plane become trapped within the closed field lines. Due to the centrifugal force, the gases accumulate at the tip of the last closed loop, resulting in a continuous decrease in plasma beta in that region. When the centrifugal force acting on the accumulated gases exceeds the tension of the closed magnetic fields, the tip of the closed zone starts expanding radially and is subsequently ejected as a plasmoid through reconnection. Such a plasmoid can be observed at r ∼ 4 - 5 R∗ in Fig. 1. Afterwards, the cycle returns to the pre-eruption phase and restores the gases within the closed magnetic field lines. This type of recurrent eruptions has been known as slingshot prominence in the context of magnetically-active rapidly-rotating stars (e.g., Ferreira 2000; Townsend & Owocki 2005; Jardine & Collier Cameron 2019). The upper panel of Fig. 3 focuses on the fluxes during a rotation period (t = 15-16 [2π/Ω∗]), as also depicted in Fig. 2. In comparison to the pre- and post-eruption phases, represented by the purple and red lines, respectively, the observed fluxes of mass, energy, and angular momentum consistently increase as the erupted plasmoids reach the outer boundary, indicated by the green lines. Notably, the magnetic torque significantly contributes to the overall torque increase during the eruption phase and plays a dominant role in the central WD’s spin-down. We note that the specifics of reconnection dynamics, such as the frequency of recurrent eruptions and the resulting time evolution of mass, energy, and angular momentum fluxes, may be influenced by our numerical parameters, including spatial resolution (which governs numerical resistivity) and the width of the wind launching region. However, we have verified that the time-averaged values of wind velocities, mass loss rate, luminosity, and torque have all reached convergence concerning the spatial resolution in our simulations and the width of the wind launching region (see Appendix B). 3.3. Scaling relation of the spin-down torque Here we consider how the spin-down torque of rotating magnetic wind depends on the system parameters based on our numerical results. As we show in the previous sub-sections, the time-averaged torque is essentially determined by the magnetic torque exerted on the gases at the tip of the last closed field lines, or the Y-point, where the field configuration is still roughly compatible with the rotating dipole. In this case, the (electro)magnetic torque at the Y point can be estimated as [3] In relativistic MHD regime, speed of light c is conventionally used as the characteristic speed of the system (e.g., see the definition of σ0 in Bucciantini et al. 2006). This paper is available on arxiv under CC 4.0 license. Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Abstract and Intro Setup Setup Result Result Summary and Discussion Summary and Discussion Appendix Appendix A. Dual Energy Formalism A. Dual Energy Formalism B. Convergence of Results B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime C. Change of the Mass Loss Rate in MHD Regime References References 3. RESULT Table. 3 shows a summary of our simulation. A model BxΩy corresponds to the case with B∗ = x and Ω∗ = y in the cgs unit. When the rotating magnetic wind becomes quasi-steady, it can be characterized by the mass loss rate wind luminosity and spindown torque estimated at the outer boundary. As we show later, the strength of rotating magnetic winds can be characterized by a dimensionless parameter Hereafter we take B1.5e6Ω0.23 with σ = 34.3 as the fiducial model, and first show the multi-dimensional structure of the rotating magnetic wind in Sec. 3.1. We then investigate the time variability of the system primarily focusing on the impacts of quasi-periodic eruption along with the equatorial plane in Sec. 3.2. Finally, we show how the time-averaged spin-down torque scales with system parameters in Sec. 3.3. 3.1. Anisotropic wind structure Anisotropic wind structure In the equatorial direction (80◦ ≲ θ ≲ 100◦), magnetic fields are closed at small radii, forming a corotating magnetosphere. Beyond the last closed loop, the magnetic field lines are open with a predominant toroidal component, having opposite polarities with respect to the equatorial plane. The transition of the magnetic field configuration is mediated by reconnection occurring at around the tip of the last closed loop, or the Y point. As can be observed from the top-right panel of Fig. 1, the plasma beta in this transition region is higher than those along the open magnetic fields, implying that the gas is trapped mainly by magnetic tensions. In this high plasma-beta region sandwiched by low plasma beta regions, gases are pinched and radially accelerated in the reconnection region, eventually become supersonic at around r ∼ 5 R∗. The latitudinal angle dependence of the wind at the outer boundary is illustrated in Fig. 2, where the gray shaded regions represent the dynamical range of radial velocity (top-left), luminosity (top-right), torque (bottom-left), and mass loss rate (bottom-right). As described in the previous paragraphs, radial velocities in the near-equatorial direction can reach and transiently exceed the Michel velocity (represented by the horizontal dotted line) during eruptions caused by reconnection at the Y-point. Consequently, the wind luminosity, dominated by the radial kinetic term, also exhibits a sharp peak in the equatorial direction. On the other hand, the torque is primarily exerted by corotation with the magnetic fields and reaches its peak slightly off the equatorial plane (θ ∼ 85◦), corresponding to the edge of the concave shape of the Alfven radius. 3.2. Time variability Time variability The acceleration of the rotating magnetic wind in the equatorial direction occurs in a time-variable manner, associated with magnetic reconnection at the Y-point. Consequently, the overall flux of mass, energy, and angular momentum from the central WD can also vary with time. Fig. 3 displays the time evolution of the mass loss rate (M˙ ), luminosity (L), and torque (T) in our fiducial model. All quantities are normalized by their time-averaged values. The lower panel of Fig. 3, which provides a long-term perspective, reveals a recurrent eruptive behavior. A recurrent cycle consists of pre-eruption, reconnection, post-eruption phases: In the pre-eruption phase, gases injected into the near-equatorial plane become trapped within the closed field lines. Due to the centrifugal force, the gases accumulate at the tip of the last closed loop, resulting in a continuous decrease in plasma beta in that region. When the centrifugal force acting on the accumulated gases exceeds the tension of the closed magnetic fields, the tip of the closed zone starts expanding radially and is subsequently ejected as a plasmoid through reconnection. Such a plasmoid can be observed at r ∼ 4 - 5 R∗ in Fig. 1. Afterwards, the cycle returns to the pre-eruption phase and restores the gases within the closed magnetic field lines. This type of recurrent eruptions has been known as slingshot prominence in the context of magnetically-active rapidly-rotating stars (e.g., Ferreira 2000; Townsend & Owocki 2005; Jardine & Collier Cameron 2019). The upper panel of Fig. 3 focuses on the fluxes during a rotation period (t = 15-16 [2π/Ω∗]), as also depicted in Fig. 2. In comparison to the pre- and post-eruption phases, represented by the purple and red lines, respectively, the observed fluxes of mass, energy, and angular momentum consistently increase as the erupted plasmoids reach the outer boundary, indicated by the green lines. Notably, the magnetic torque significantly contributes to the overall torque increase during the eruption phase and plays a dominant role in the central WD’s spin-down. We note that the specifics of reconnection dynamics, such as the frequency of recurrent eruptions and the resulting time evolution of mass, energy, and angular momentum fluxes, may be influenced by our numerical parameters, including spatial resolution (which governs numerical resistivity) and the width of the wind launching region. However, we have verified that the time-averaged values of wind velocities, mass loss rate, luminosity, and torque have all reached convergence concerning the spatial resolution in our simulations and the width of the wind launching region (see Appendix B). 3.3. Scaling relation of the spin-down torque Scaling relation of the spin-down torque Here we consider how the spin-down torque of rotating magnetic wind depends on the system parameters based on our numerical results. As we show in the previous sub-sections, the time-averaged torque is essentially determined by the magnetic torque exerted on the gases at the tip of the last closed field lines, or the Y-point, where the field configuration is still roughly compatible with the rotating dipole. In this case, the (electro)magnetic torque at the Y point can be estimated as [3] In relativistic MHD regime, speed of light c is conventionally used as the characteristic speed of the system (e.g., see the definition of σ0 in Bucciantini et al. 2006).

Magnetic Wind From a Massive White Dwarf Merger: Result

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan;
(2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan;
(3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan;
(4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan;
(5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Setup Result Summary and Discussion Appendix A. Dual Energy Formalism B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime References 4. SUMMARY AND DISCUSSION Hence, even if the currently observed wind of WD J005311 is a rotating magnetic one and continues to blow for a Kelvin-Helmholtz timescale of the central WD, which is ∼ 1, 000-10, 000, yr, the spin-down will be negligible. When the carbon burning in the near-surface region ceases, the mass loss rate will significantly decrease, which increases the dimensionless parameter σ. The rotating magnetic wind will then become relativistic and eventually enter the force-free regime without significantly spinning down the WD. In this case, the remnant WD may serve as a non-thermal radiation source, or or the so-called WD pulsar (e.g., Kashiyama et al. 2011). Finally, we address some caveats in our numerical simulations. We have implemented a simple prescription for the near-surface carbon burning region as source terms (Eqs. 13 and 14), referred to as the wind launching region. However, the actual near-surface carbon burning region should be convective, and can be affected by the strong magnetic field. The structure of the convective region, the resulting wind launch, and its chemical composition would also be influenced by the radiative transfer. For accurate multi-wavelength spectrum calculations, it is desirable to conduct a comprehensive radiative MHD simulation that covers from the carbon burning layer to the photosphere radius. Also, we only investigate the aligned rotating dipole magnetic fields in this paper, while a more complicated field configuration such as oblique or off-centered dipole may be realized for the remnant WD system. Finally, the deformation of the central WD due to its rapid rotation and anisotropic carbon burning can alter the observed properties as well. We save the investigations into the above topics for our future work. This paper is available on arxiv under CC 4.0 license. Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Abstract and Intro Setup Setup Result Result Summary and Discussion Summary and Discussion Appendix Appendix A. Dual Energy Formalism A. Dual Energy Formalism B. Convergence of Results B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime C. Change of the Mass Loss Rate in MHD Regime References References 4. SUMMARY AND DISCUSSION Hence, even if the currently observed wind of WD J005311 is a rotating magnetic one and continues to blow for a Kelvin-Helmholtz timescale of the central WD, which is ∼ 1, 000-10, 000, yr, the spin-down will be negligible. When the carbon burning in the near-surface region ceases, the mass loss rate will significantly decrease, which increases the dimensionless parameter σ. The rotating magnetic wind will then become relativistic and eventually enter the force-free regime without significantly spinning down the WD. In this case, the remnant WD may serve as a non-thermal radiation source, or or the so-called WD pulsar (e.g., Kashiyama et al. 2011). Finally, we address some caveats in our numerical simulations. We have implemented a simple prescription for the near-surface carbon burning region as source terms (Eqs. 13 and 14), referred to as the wind launching region. However, the actual near-surface carbon burning region should be convective, and can be affected by the strong magnetic field. The structure of the convective region, the resulting wind launch, and its chemical composition would also be influenced by the radiative transfer. For accurate multi-wavelength spectrum calculations, it is desirable to conduct a comprehensive radiative MHD simulation that covers from the carbon burning layer to the photosphere radius. Also, we only investigate the aligned rotating dipole magnetic fields in this paper, while a more complicated field configuration such as oblique or off-centered dipole may be realized for the remnant WD system. Finally, the deformation of the central WD due to its rapid rotation and anisotropic carbon burning can alter the observed properties as well. We save the investigations into the above topics for our future work.

Magnetic Wind From a Massive White Dwarf Merger: Summary and Discussion

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan;
(2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan;
(3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan;
(4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan;
(5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Setup Result Summary and Discussion Appendix A. Dual Energy Formalism B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime References ABSTRACT Keywords: white dwarfs — stars: winds, outflows — stars: rotation 1. INTRODUCTION Consequences of a merger of massive white dwarfs (WDs) are of great astrophysical importance. It may explode as a Type Ia supernova in particular when the binary constitutes of carbon-oxygen WDs with a total mass exceeding the Chandrasekhar limit (Webbink 1984; Iben & Tutukov 1984). Instead, if a super-Chandrasekhar oxygen-neon core is synthesized after the merger, it may collapse into a neutron star (NS) (Nomoto & Iben 1985; Saio & Nomoto 2004). Such a merger induced collapse has gotten attention as a scenario for the formation of peculiar type of neutron stars, e.g., sources of fast radio bursts (e.g., Kashiyama & Murase 2017; Kremer et al. 2021; Kirsten et al. 2022; Lu et al. 2022). On the other hand, the expansion velocity of the wind observed in WD J005311 significantly surpasses the escape velocity of a WD with a typical mass. This suggests that the wind is either thermally driven, originating from a superor near-Chandrasekhar mass WD, or magnetically driven due to the rapid rotation and strong magnetic field of the WD. In the former case, the wind velocity will be (Parker 1965): while in the latter case, the maximum wind velocity along the equatorial plane is (Weber & Davis 1967; Michel 1969): The wind is so fast that it catches up and clashes into the surrounding supernova ejecta, forming a wind termination shock, which is observed as an inner X-ray nebula (Oskinova et al. 2020; Ko et al. 2023). The X-ray nebula is still in its infancy; given the observed angular size, it is only a few tens of years old (Ko et al. 2023). Subsequent observations may reveal the time variability and anisotropy of the wind, which is generally expected for a rotating magnetic wind but has not been explored in this context. These properties of the wind can also be linked to the mass-loss and spindown rates of the central WD, which are important in determining the fate of the central WD: whether it eventually collapses into a neutron star, and if so, how rapidly rotating and strongly magnetized the neutron star would be. Here we model a system like WD J005311 by numerically constructing a 2D axisymmetric wind solution driven by rotating dipole, with implementing a wind launching region that mimics the near-surface carbon burning region. We investigate the wind structure together with its time evolution (i.e., how the mass, energy and angular momentum loss rate from the system evolves with time), and the scaling of the spin-down torque with respect to system parameters such as surface magnetic field, rotation frequency and mass loss rate. This paper is organized as follows. We introduce our setup in Sec. 2, including numerical details. In Sec. 3, we show our results on wind structure, time evolution and scaling of spin-down torque. Finally, we discuss several implications and applications on observational results in Sec. 4. This paper is available on arxiv under CC 4.0 license. Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Yici Zhong, Department of Physics, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan; (2) Kazumi Kashiyama, Research Center for the Early Universe, Graduate School of Science, University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU,WPI), The University of Tokyo, Chiba 277-8582, Japan; (3) Shinsuke Takasao, Department of Earth and Space Science, Graduate School of Science, Osaka University, Toyonaka, Osaka 560-0043, Japan; (4) Toshikazu Shigeyama, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Astronomy, School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan; (5) Kotaro Fujisawa, Research Center for the Early Universe (RESCEU), School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan and Department of Liberal Arts, Tokyo University of Technology, Ota-ku, Tokyo 144-0051, Japan. Table of Links Abstract and Intro Abstract and Intro Setup Setup Result Result Summary and Discussion Summary and Discussion Appendix Appendix A. Dual Energy Formalism A. Dual Energy Formalism B. Convergence of Results B. Convergence of Results C. Change of the Mass Loss Rate in MHD Regime C. Change of the Mass Loss Rate in MHD Regime References References ABSTRACT Keywords : white dwarfs — stars: winds, outflows — stars: rotation Keywords 1. INTRODUCTION Consequences of a merger of massive white dwarfs (WDs) are of great astrophysical importance. It may explode as a Type Ia supernova in particular when the binary constitutes of carbon-oxygen WDs with a total mass exceeding the Chandrasekhar limit (Webbink 1984; Iben & Tutukov 1984). Instead, if a super-Chandrasekhar oxygen-neon core is synthesized after the merger, it may collapse into a neutron star (NS) (Nomoto & Iben 1985; Saio & Nomoto 2004). Such a merger induced collapse has gotten attention as a scenario for the formation of peculiar type of neutron stars, e.g., sources of fast radio bursts (e.g., Kashiyama & Murase 2017; Kremer et al. 2021; Kirsten et al. 2022; Lu et al. 2022). On the other hand, the expansion velocity of the wind observed in WD J005311 significantly surpasses the escape velocity of a WD with a typical mass. This suggests that the wind is either thermally driven, originating from a superor near-Chandrasekhar mass WD, or magnetically driven due to the rapid rotation and strong magnetic field of the WD. In the former case, the wind velocity will be (Parker 1965): while in the latter case, the maximum wind velocity along the equatorial plane is (Weber & Davis 1967; Michel 1969): The wind is so fast that it catches up and clashes into the surrounding supernova ejecta, forming a wind termination shock, which is observed as an inner X-ray nebula (Oskinova et al. 2020; Ko et al. 2023). The X-ray nebula is still in its infancy; given the observed angular size, it is only a few tens of years old (Ko et al. 2023). Subsequent observations may reveal the time variability and anisotropy of the wind, which is generally expected for a rotating magnetic wind but has not been explored in this context. These properties of the wind can also be linked to the mass-loss and spindown rates of the central WD, which are important in determining the fate of the central WD: whether it eventually collapses into a neutron star, and if so, how rapidly rotating and strongly magnetized the neutron star would be. Here we model a system like WD J005311 by numerically constructing a 2D axisymmetric wind solution driven by rotating dipole, with implementing a wind launching region that mimics the near-surface carbon burning region. We investigate the wind structure together with its time evolution (i.e., how the mass, energy and angular momentum loss rate from the system evolves with time), and the scaling of the spin-down torque with respect to system parameters such as surface magnetic field, rotation frequency and mass loss rate. This paper is organized as follows. We introduce our setup in Sec. 2, including numerical details. In Sec. 3, we show our results on wind structure, time evolution and scaling of spin-down torque. Finally, we discuss several implications and applications on observational results in Sec. 4.

Magnetic Wind From a Massive White Dwarf Merger: Abstract and Intro

Propchain, a leading Proptech player in the real estate sector, has announced the successful exit of its first property, Sixty7 Boulevard, listed on its Real Estate investment platform, Prop.com. Originally centered on the global real estate market, Propchain's property investment platform has strategically shifted its focus to target the Dubai real estate market. This change is driven by increasing interest from global investors in the city's rapidly-growing real estate sector. Situated in the heart of Downtown Dubai, Sixty7 Boulevard is a luxurious Triplex Sky Mansion acquired, managed, and leased by the Propchain team. This property is located in the prestigious Boulevard Point building and is directly connected to the world-renowned Dubai Mall. The Sky Mansion boasts an extraordinary view that overlooks nearly 200 degrees of the Emirate and is located in the hub of tourism, business, and entertainment in Downtown Dubai. Within a span of 10 months, the property efficiently completed its full investment lifecycle, culminating in a profitable exit with returns exceeding 11% for investors in less than a year. Moreover, Propchainhas revealed plans to initiate an open-market buyback using the revenue generated from Sixty7 Boulevard. If executed, this milestone holds a significant importance for over 10,000 token holders currently holding the native token, $PROPC. Propchain's latest initiative is driven by a vision to establish a brand identity synonymous with trust and innovation in the digital real estate market. The company aims to streamline the real estate investment process and enhance accessibility for retail investors worldwide. Notably, Prop.com integrates digital asset payments through Binance Pay, enabling swift transactions with minimal fees, all powered by blockchain technology. This key development also highlights Propchain's commitment to simplifying user interactions and democratizing real estate investing on a global scale, thereby bridging the gap between the traditional world and Web 3.0. About Propchain Propchain leads the way in real estate investment platforms, placing consumer needs at the forefront by providing effortless access to tokenized assets and a user-friendly digital interface for asset management. It aims to revolutionize the real estate industry through the widespread adoption of blockchain technology, facilitating improved market dynamics, transparency, and long-term sustainability. Propchain's journey is marked by significant milestones, strategic focus, and innovative real estate strategies. With its dedication to digitally empowering the real estate value chain through investing and strategic positioning in the global market, Propchain is set to redefine the real estate investment landscape and continue its path of success. This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. Propchain, a leading Proptech player in the real estate sector, has announced the successful exit of its first property, Sixty7 Boulevard, listed on its Real Estate investment platform, Prop.com. Originally centered on the global real estate market, Propchain's property investment platform has strategically shifted its focus to target the Dubai real estate market. This change is driven by increasing interest from global investors in the city's rapidly-growing real estate sector. Situated in the heart of Downtown Dubai, Sixty7 Boulevard is a luxurious Triplex Sky Mansion acquired, managed, and leased by the Propchain team. This property is located in the prestigious Boulevard Point building and is directly connected to the world-renowned Dubai Mall. The Sky Mansion boasts an extraordinary view that overlooks nearly 200 degrees of the Emirate and is located in the hub of tourism, business, and entertainment in Downtown Dubai. Within a span of 10 months, the property efficiently completed its full investment lifecycle, culminating in a profitable exit with returns exceeding 11% for investors in less than a year. Moreover, Propchain has revealed plans to initiate an open-market buyback using the revenue generated from Sixty7 Boulevard. If executed, this milestone holds a significant importance for over 10,000 token holders currently holding the native token, $PROPC. Propchain Propchain's latest initiative is driven by a vision to establish a brand identity synonymous with trust and innovation in the digital real estate market. The company aims to streamline the real estate investment process and enhance accessibility for retail investors worldwide. Notably, Prop.com integrates digital asset payments through Binance Pay, enabling swift transactions with minimal fees, all powered by blockchain technology. This key development also highlights Propchain's commitment to simplifying user interactions and democratizing real estate investing on a global scale, thereby bridging the gap between the traditional world and Web 3.0. About Propchain Propchain leads the way in real estate investment platforms, placing consumer needs at the forefront by providing effortless access to tokenized assets and a user-friendly digital interface for asset management. It aims to revolutionize the real estate industry through the widespread adoption of blockchain technology, facilitating improved market dynamics, transparency, and long-term sustainability. Propchain's journey is marked by significant milestones, strategic focus, and innovative real estate strategies. With its dedication to digitally empowering the real estate value chain through investing and strategic positioning in the global market, Propchain is set to redefine the real estate investment landscape and continue its path of success. This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

Propchain Exits First Property 'Sixty7 Boulevard', Initiating Massive Utility For Token Holders

WOW Summit Dubai 2023, the World of WEB3 Summit, recently concluded with resounding success at the opulent Atlantis the Royal in Dubai. This event showcased an extraordinary lineup of speakers and esteemed sponsors, leaving an indelible mark on the world of blockchain and Web3 technology. , Global CEO of WOW Summit, expressed his enthusiasm, stating, Ivan Ivanov "WOW Summit Dubai 2023 has exceeded our wildest expectations. It was a landmark gathering that brought together Web3 enthusiasts, industry leaders, and government officials to shape the future of blockchain technology." The event featured some amazing panel discussions and keynotes that illuminated the path forward for blockchain and Web3 technology. The Summit featured an array of captivating panel discussions and keynote presentations. Among the standout topics were, Exploring the Fusion of AI, Metaverse, Gaming, Fashion, and NFTs, Global Strategies for Amplifying Revenue: Unlocking the Potential of Corporate Blockchain Providers, Early-Stage Funding Opportunities in Web3 Projects and Acceleration, Current State of Decentralized Media, Advancements in Web3 Protocols: Pioneering the Path to Innovation and Progress and several others. The event's sponsors, Farcana, Unicoin, Fastex, demonstrated their unwavering commitment to fostering innovation in the blockchain industry. Their visionary leadership and strategic expertise set the stage for transformative discussions on the potential of blockchain. Our sponsors were represented at the event as speakers and boosters in the exhibition hall. This exemplified their commitment to advancing the blockchain industry. Among the sponsors of the event we note such companies as: Darwinbit, ChainUp, Sastana, Beezfi (BizTrip), P2PBet,  Hacken, ICP, EXOLO. Unicoin, a next-generation cryptocurrency, stands out from its predecessors by embracing transparency, SEC compliance, and being backed by a diversified asset portfolio, including real estate and equity in high-growth companies. In contrast, Farcana, a Dubai-based AAA game development studio, is in the process of creating a game bearing the same name. Farcana's unique 4v4, ability-based arena shooter redefines the gaming experience with its innovative 4-role system, strategic gameplay, and full integration of Web3 technology, all while maintaining the high-quality standards associated with AAA gaming. Fastex is a complete Web3-driven ecosystem that introduces diverse centralized and decentralised products and solutions, including Fasttoken (FTN), Fastex Exchange, Fastexverse, Fastex Pay, and ftNFT Marketplace. Driven by constant changes in the world of technologies, the Fastex ecosystem always thinks one step ahead and aims to bring businesses and communities closer to Web3 technologies, making them more accessible than ever. Joining as speakers were also a group of outstanding individuals contributing significantly to the payments industry on Blockchain instead, including (Darwinbit), (Trust Wallet), (Hacken), (P2P Labs), and (Kinetex Network). Their support underscored the collaborative spirit of WOW Summit Dubai 2023. Jeff Zhao Eowyn Chen Igor Bershadskiy Marat Salimov Tigran Bolshoi The event featured distinguished speakers, including (Animoca Brands), (Dubai Blockchain Centre), (Director at EMARATSEC, Co-chair at the WEF global future council, Director for Center at Cyber Security New York University AD), (MENA Fintech Association), (Circle), (Chainanalysis), (Crypto Valley Partners), (UNICOIN), (Farcana), (Oracle), and other luminaries who shared profound insights and valuable discussions. Yat Siu Dr. Marwan Alzarouni Dr. Hoda Alkhzaimi Nameer Khan Miriam Kiwan Mohamed Issa Sam Katiela Julian Sperring-Toy Islam Shazhaev Joy John Prominent figures such as , , , , also graced the event, adding to its prestige. Michael Terpin Gurvinder Ahluwalia Christian Gleich Nick Spanos Mansoor Madhavji The Summit was honored by the presence of distinguished guests and esteemed media personalities, including , the esteemed from Moongames, as well as the notable presence of and (GuyWay events). Sheikh Ali Rashed Ali Saeed Al Maktoum Carl Runefelt Davinci Jeremie Guy Yanpolskiy The results of the WOW Summit Dubai Startup competition serves as a glittering showcase, highlighting the brilliant innovations and rising stars within the dynamic realms of blockchain and Web3 technology. From a pool of over a hundred spirited startup contenders, the selection of the top 10 was an inclusive and decentralized process, driven by the vibrant community using Cyrator (available at cyrator.com). This online platform became the epicenter of independent decentralized reviews, inquiries, and profound insights, all thoughtfully validated, and endorsed by esteemed experts. These well-considered deliberations are closely scrutinized by a committee of discerning investors. They're thrilled to introduce the distinguished winner of their Startup competition, hailing all the way from France, the brilliant minds behind the tokenized investment fund named Petale. This remarkable achievement has garnered the attention of MMPro Trust and its esteemed investors, who are now contemplating an investment of up to $1 million in the Petale project. Additionally, the project is set to embark on a series of meetings with tier-1 investment funds in Dubai. In an added boost of support, the Petale project has secured three months of invaluable market-making assistance, comprehensive listing maintenance, and expert trade strategy management courtesy of Market Making Pro, all as a well-deserved reward for emerging triumphant in the WOW Summit Startup Competition. This accomplishment underlines WOW Summit's steadfast dedication not only to recognizing exceptional talent but also to providing a vital launchpad for entrepreneurial aspirations. Furthermore, their victorious startups have not only earned the prestigious accolade but have also been generously rewarded with a slew of prizes from industry leaders such as AWS and various other esteemed partners. The WOW GROWTH program has also extended its nurturing hand to the top 10 finalists, offering a three-month acceleration program complete with comprehensive business development support and guidance on investor relations. This support will span across regions of interest, including Asia (HK Hub), the MENA region (UAE Hub), and Europe (Swiss Hub). In a groundbreaking collaboration with the Internet Computer Protocol (ICP), WOW Summit and GROWTH have launched an exciting Ideathon program, designed to cater to companies in their early stages, enabling them to test their innovative concepts and find the perfect tech team to bring these ideas to life. The Ideathon is now open for participation throughout the months of October and November 2023, while the forthcoming hackathon is scheduled to take place during the WOW Summit in Hong Kong 2024. The exclusive media zone, featuring moderators from Ana Solana (JETA agency) and Adel Bhurtun from Web3TV, provided a platform for in-depth coverage and analysis of the event's key moments. WOW Summit Dubai 2023's art zone showcased an impressive array of digital and NFT artists. Amrita Sethi, the event's headliner, crafted five unique works and is recognized as the UAE's first NFT artist, as well as a top-tier Physical and Digital Artist. For the WOW Summit, Amrita Sethi unveiled her latest masterpiece series titled "Art and Tech" aiBYTEs, representing a captivating evolution of her distinctive style. In a remarkable fusion of art and technology, she collaborated with ChatGPT to craft a poetic narrative that envisions how the transition from Web2 to Web3 will inspire our world. Subsequently, she harnessed the creative power of Midjourney to transform this narrative into stunning visual imagery. Vesa, a renowned digital art pioneer for over 15 years, is considered one of the initial artists to delve into crypto art and NFTs. His notable awards include NFT Artist of the Year (AIBC Summit, 2023) and top Web3 Artists accolades from L’Officiel Arabia. Naama Pozniak, the CEO of Paz Holding, Inc., and LetzGetPhygital, stood out as a Web3 Educator, NFT Artist, and multifaceted professional known for her contributions to the art world. WOW Summit Dubai 2023 lived up to its promise as an unmissable Web3 event that will undoubtedly shape the future of blockchain technology. Attendees were treated to a unique experience filled with knowledge sharing, networking opportunities, and exploration of cutting-edge developments in the Web3 ecosystem. WOW Summit is now gearing up for their Hong Kong edition in 2024, scheduled for March 26-27. Secure your super now. early bird tickets About WOW Summit: WOW Summit is a leading global Web3 event that unites distinguished industry titans, esteemed government officials, visionary funds, venture capitalists, NFT and digital artists, entrepreneurs, and multinational corporations. The Summit drives the innovative trajectory of Web3, covering cutting-edge trends and innovations in technology. It explores themes including the Web2 - Web3 transition, CBDCs, regulatory landscapes, asset tokenization, and the societal impact of blockchain and DLT technologies. Hosted by GuyWay, powered by MarketMakingPro, and co-organized by Uvecon.vc and Quantum Leap Strategy, WOW Summit has a history of hosting distinguished speakers.

WOW Summit Dubai 2023: A Massive Success Shaping the Future of Blockchain Technology

Companies are generating an ocean full of data, with marketing teams swimming in customer insights and finance departments navigating through intricate transactions. And let’s not even talk about how enormous spreadsheet files generated by cybersecurity teams are. Unfortunately, spreadsheet platforms like Microsoft Excel and Google Sheets can’t handle big data spreadsheet files with millions or billions of rows. As of this writing, the . Whereas, Google Sheets has a . maximum row limit of Excel is 1,048,576 maximum cell limit of 10 million One of the best ways to smartly analyze big data spreadsheets without causing your browser to crash or your computer to run out of memory is using Gigasheet. Recently, I interviewed , the Co-founder of , a big data spreadsheet platform that allows its users to upload and analyze gigantic-sized spreadsheets packed with millions or billions or rows. Jason Hines Gigasheet What is your company in 2–5 words? The big data spreadsheet. Why is now the time for your company to exist? Spreadsheet platforms like Excel, Airtable, Smartsheet, and Google Sheets are not built for handling big data. These tools are incredibly powerful and offer tons of useful capabilities, but because of the limited capabilities that restrict users from working with huge datasets. That’s where Gigasheet is a game-changer. We have built this platform for users looking for something more powerful than Excel and Google Sheets. We want users to get insights from big data without having to write code or set up databases. You shouldn’t need a dedicated Data Science team or a Computer Science degree to get answers from really big datasets. And that’s what our sole focus is. Since spreadsheets are second-nature to most professionals, we didn’t want to reinvent the wheel with a new product with the same functionality as a sheet. Instead, we decided to simplify spreadsheets for huge datasets. With Gigasheet, we offer data science capabilities in a lite platform with features like data enrichment, grouping, filtering, and much more. In a line, we combine the power of big data with the convenience of spreadsheets to work seamlessly with large datasets. What do you love about your team, and why are you the ones to solve this problem? I worked with cybersecurity analysts and revenue teams for a long time in my career. I realized that the volume of the data they handled was so large and complicated that they had to go through too much hassle to export and import it into a database. Besides, not everyone had database skills. So, they had to wait for other teams to support them in the research process, creating lengthy dependencies. That was the core problem statement we wanted to solve. My first-hand experience of working with these analysts and observing their problems in real-time helped me build Gigasheet as a powerful solution for working with large datasets, minus the hassle. If you weren’t building your startup, what would you be doing? Wow, that’s a good question. To be honest, since I committed to building Gigasheet, I haven’t even considered doing anything else. If I wasn’t doing this, I guess I’d probably be building another company or helping someone else do it. At the moment, how do you measure success? What are your metrics? I believe the goal of a venture-backed startup like ours is to fund our growth. So, we’re measuring success based on the platform’s utility for our end-users and our ability to go forward with our product roadmap as planned. In a few sentences, what do you offer to whom? We offer a big data spreadsheet platform with several use cases and advanced capabilities. We serve users from multiple industries and roles, including eCommerce, cybersecurity, marketing, sales, analysts, and more. What’s most exciting about your traction to date? Just the sheer number of users and data we’re processing is kind of mindblowing. We recently processed our 5 trillionth data point and have more than 30,000 users on Gigasheet today. It’s wild to think about it, but we’re processing, on average, about 200,000 cells of data every second. Where do you think your growth will be next year? We've recently launched APIs to help users connect other systems to Gigasheet. This makes Gigasheet a powerful solution for enterprises, particularly heavy-duty applications like Snowflake or Salesforce. You can automate everything possible on the platform. So, whether you want to upload your data on a simpler interface, schedule import/export, or clean and inspect it, it's all possible with our enterprise API. We're also launching shared workspaces for teams. Multiple users from the same company use Gigasheet for collaboration on big files. That motivated us to expand beyond the single-user interface and add the shared workspace functionality to help teams work together seamlessly. Another cool thing on our radar is introducing more enrichments with our predefined partners. So, users can enrich massive data at scale without any coding skills. Tell us about your first paying customer and revenue expectations over the next year. Our first paying customer was an accountant in Canada. We never spoke to them, but it seems like they were successful. Each month we’ve been adding more customers, which is great, but our primary focus remains on building out more features in our product for 2023. What’s your biggest threat? As a startup, there are always 1,000 ways to die. The biggest threats are probably existential factors that are outside of our control - stability of financial markets and things like economic factors. As Paul Graham has said, “Startups rarely die in mid keystroke.” So, we keep building.

Beyond Excel and Google Sheets: Innovations in Handling Massive Spreadsheets Amidst the Big Data Rev

Most people who invest in cryptocurrency understand that it's a . Even so, it can feel devastating if and when you experience a massive loss. How are you supposed to cope with such a big downturn? somewhat volatile and risky investment And how should it reshape your investment strategy in the future? Objectively Analyze the Situation First, try to objectively analyze the situation as best you can. While the shock of the loss might feel devastating at this moment, it's important to see this as a learning opportunity. Study the following, at minimum, to build better takeaways you can use in your future investment endeavors: Why and how did you originally invest in this cryptocurrency? Did you closely adhere to a carefully crafted strategy, investing an amount of money you were comfortable losing? Or was this more of a reckless, impulsive decision based on encouragement from less than reputable sources of financial information? Your original investment decision. Losses are sometimes acceptable, and even expected, in the context of a broadly useful investment strategy. It's also possible that you made a mistake with your initial investment. Why did the value of your chosen cryptocurrency drop? This can help you in a few different ways. First, it can help you learn from these events so you can better apply those lessons to your future investment choices. The reason for the drop. Second, this may contextualize your losses; if this is only a temporary downswing, there's no reason to be upset about it. Third, it can help you feel more comfortable with your own status as an investor; if nobody saw this drop coming, there's nothing you could have done to prevent experiencing this loss. Is there anything you could have done to minimize your losses? Should you have invested less initially? Should you have sold when the downturn first started? Potential actions you could have taken. Should you have practiced better portfolio diversification so the loss wouldn't sting as much? Finally, take a look at the current state of your position. How many cryptocurrencies are you currently holding, and what is this cryptocurrency poised to do in the future? Do you believe in the long-term value of this asset? Do you think it's worth holding? The current state of your position. Get the Support You Need Dealing with a massive monetary loss can be extremely stressful, so it's important to get the support you need. A psychotherapist could be exactly what you need to navigate this stressful and confusing time. Together with your therapist, you can explore your emotional responses to this event, underlying issues that may be complicating these losses, and healthy practices that can put you in a better state of mind. Therapy/counseling. It's also important to reach out to family members and friends for extra support. If you're not comfortable doing so, you don't have to disclose your losses specifically to them; just ask them to hang out because you need the extra support. Family bonds and friendships. If you're struggling financially, there may be resources that can help you. Consider talking to a credit counselor, a financial advisor, or someone close to you that you trust with financial issues about your options. Financial support. Practice Healthy Coping Strategies From moment to moment, you may feel things like stress, shame, and anger toward your loss. It's important to proactively manage these emotions in a healthy way if you want to preserve your mental health and the health of your relationships. It's tempting to beat yourself up for foolish decisions you made in the past or fret about what your future is going to look like. But when you feel overwhelmed, it's important to focus exclusively on the present moment. Focus on the present moment. Do what you can to relax. Take a warm bath, practice deep breathing, use mindfulness meditation, or journal to soothe your racing mind. Practice relaxation strategies. Focus on a hobby or activity you love so you can spend less time worrying. Distract yourself. Even little efforts of self-care, like cleaning the house, can boost your mood and confidence. Take care of yourself. Avoid Logical Fallacies It's also important to avoid certain logical fallacies during this time, as these can drive you to make irrational and negatively consequential decisions. For example, can lead you to believe that this downturn won't be repeated in the near future, prompting you to invest more in what could be a failing asset. the gambler’s fallacy Investing more could be the right choice, but you need to make it for the right reasons. The sunk cost fallacy is also important to avoid. This fallacy makes people more likely to invest in something they've already heavily invested in as a way to make up for their existing losses. Capitalize on Your Losses Nobody actively seeks a capital loss, but losses can work in your favor in some contexts. Notably, you can claim a cryptocurrency loss on your taxes, potentially giving you a tax advantage. If you had $10,000 in gains from selling a stock, but you lost $10,000 on a cryptocurrency investment, you can negate your gains and minimize the taxes you pay, accordingly. Remember the Purpose of Cryptocurrency It can also be helpful to remember the true purpose of cryptocurrency. These days, people often treat crypto as if it's an equity investment akin to company stocks. But in reality, it's designed to be used as a currency. In this context, valuation changes are less important; you can still use your crypto as a form of payment. Focus on What’s Next Finally, spend some time focusing on what comes next. What are the next steps you want to take and how are you going to take them? Options include: If you're bearish about the future of this cryptocurrency, consider cutting your losses and selling the rest of your position. Cutting your losses. If you're bullish about the future of this cryptocurrency, you may want to double down, investing even more in this asset. Do so with caution. Doubling down. If you're feeling frustrated with your loss and skittish about your future as an investor, you can also take this time to rebalance your portfolio. Increase or decrease your holdings in various assets to more accurately align with your current risk profile and investment goals. Rebalancing. No matter what, experiencing a major loss in the crypto market is stressful and devastating. But with the right coping strategies and a healthy mindset, you can bounce back from this loss and come back stronger than ever.

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