To kick off his participation at the World Leaders Climate Action Summit at the United Nations Climate Change Conference (COP29) in Baku, Azerbaijan, the Honourable Steven Guilbeault, Minister of Environment and Climate Change, provided the following statement to launch GAIA, a new finance platform ...

During the World Leaders Climate Action Summit at COP29, Minister Guilbeault announces major Canadian-led climate finance platform - Canada.ca

GAIA

gaia

GaiaNet offers a powerful AI-driven chat interface that makes it easy to interact with various models for different purposes. Whether you need assistance with coding, want to write an essay, or require help with a specific task, GaiaNet can help. Here’s a step-by-step guide on how to use GaiaNet Chat. Step 1: Accessing GaiaNet Chat To start using GaiaNet Chat, navigate to GaiaNet Chat on your web browser. You’ll be greeted with a clean, user-friendly interface. Step 2: Starting a New Chat Click on the “New Chat” button to initiate a conversation. This will open a new chat window where you can type your queries. Step 3: Selecting a Node GaiaNet uses various nodes for different types of tasks. For instance, if you need help with Python programming, you might want to select a Python-specific node. You can search for the desired node using the search bar. Click on the dropdown menu under “Select a Node.”
Type in the keyword related to your task (e.g., “Python”).
Choose the appropriate node from the list. Step 4: Asking a Question Type your question or request into the chat box. For example, if you want to convert temperatures in Python, you could ask: “Please write a Python script to convert Celsius to Fahrenheit.” Step 5: Receiving a Response GaiaNet will process your request and provide a detailed response. This might include code snippets, explanations, or step-by-step instructions depending on your query. Step 6: Interacting With the Response You can interact further with the response by asking follow-up questions or requesting modifications. For example, you could ask GaiaNet to refine the code or provide additional details. “Improve this script” Step 7: Start New Chat & Clearing Conversations If you want to start a new conversation or clear previous chats, click on the “Clear Conversations” button located on the left-hand side of the interface. Additional Tips Save Important Responses: You can save important responses by copying the text and storing it in a document. Explore Different Nodes: Experiment with different nodes to see which one best suits your needs. AI Agents are available such as Chemistry, Law, Medicine, Finance, and many more. Provide Clear Instructions: When asking for help, be as specific as possible to get the most accurate response. Using GaiaNet Chat is a straightforward way to leverage AI for a variety of tasks. With its intuitive interface and powerful nodes, you can get the assistance you need quickly and efficiently. Give it a try, and see how it can help you with your next project! Written by Zulfanbaswedan GaiaNet offers a powerful AI-driven chat interface that makes it easy to interact with various models for different purposes. Whether you need assistance with coding, want to write an essay, or require help with a specific task, GaiaNet can help. Here’s a step-by-step guide on how to use GaiaNet Chat. Step 1: Accessing GaiaNet Chat To start using GaiaNet Chat, navigate to GaiaNet Chat on your web browser. You’ll be greeted with a clean, user-friendly interface. GaiaNet Chat Step 2: Starting a New Chat Click on the “New Chat” button to initiate a conversation. This will open a new chat window where you can type your queries. Step 3: Selecting a Node GaiaNet uses various nodes for different types of tasks. For instance, if you need help with Python programming, you might want to select a Python-specific node. You can search for the desired node using the search bar. Click on the dropdown menu under “Select a Node.” Type in the keyword related to your task (e.g., “Python”). Choose the appropriate node from the list. Click on the dropdown menu under “Select a Node.” Type in the keyword related to your task (e.g., “Python”). Choose the appropriate node from the list. Step 4: Asking a Question Type your question or request into the chat box. For example, if you want to convert temperatures in Python, you could ask: “Please write a Python script to convert Celsius to Fahrenheit.” “Please write a Python script to convert Celsius to Fahrenheit.” Step 5: Receiving a Response GaiaNet will process your request and provide a detailed response. This might include code snippets, explanations, or step-by-step instructions depending on your query. Step 6: Interacting With the Response You can interact further with the response by asking follow-up questions or requesting modifications. For example, you could ask GaiaNet to refine the code or provide additional details. “Improve this script” “Improve this script” Step 7: Start New Chat & Clearing Conversations If you want to start a new conversation or clear previous chats, click on the “Clear Conversations” button located on the left-hand side of the interface. Additional Tips Save Important Responses: You can save important responses by copying the text and storing it in a document. Save Important Responses : You can save important responses by copying the text and storing it in a document. Save Important Responses Explore Different Nodes: Experiment with different nodes to see which one best suits your needs. AI Agents are available such as Chemistry, Law, Medicine, Finance, and many more. Explore Different Nodes : Experiment with different nodes to see which one best suits your needs. AI Agents are available such as Chemistry, Law, Medicine, Finance, and many more. Explore Different Nodes Provide Clear Instructions: When asking for help, be as specific as possible to get the most accurate response. Provide Clear Instructions : When asking for help, be as specific as possible to get the most accurate response. Provide Clear Instructions Using GaiaNet Chat is a straightforward way to leverage AI for a variety of tasks. With its intuitive interface and powerful nodes, you can get the assistance you need quickly and efficiently. Give it a try, and see how it can help you with your next project! Written by Zulfanbaswedan

How to Use GaiaNet Chat: A Step-by-Step Guide

SAN FRANCISCO, CA, June 4, 2024 — GaiaNet, the pioneering decentralized AI infrastructure project that aims to disrupt central AI inferencing servers like ChatGPT, today announced the launch of its Beta product. The launch follows the completion of the Alpha testing phase, during which the platform successfully handled a tremendous volume of daily requests on Telegram, Discord and X. The Beta release focuses on the ease of setting up a GaiaNet node, ensuring that users, from individuals to businesses, can effortlessly integrate into the network. With a user-friendly interface, GaiaNet simplifies the process, making its innovative solutions accessible to users of all technical levels. The commencement of beta testing marks a significant step forward in GaiaNet’s commitment to building a more inclusive and equitable AI ecosystem. With plans to roll out more functionalities in 2024, the platform is on the brink of redefining the boundaries of AI, making it more accessible, data bias-resistant, collaborative, and privacy-centric. Early Adopters Campaign To celebrate the Beta launch, GaiaNet invites the community to join the interactive campaigns on X, Discord, Telegram, and Warpcast. GaiaNet has a community and user-oriented philosophy; therefore, early users and community members can look forward to exclusive benefits. By actively setting up nodes and interacting with GaiaNet agents across different nodes, users can join the beta product testing and potentially unlock special rewards in the future. More details will be revealed soon. The Alpha phase demonstrated GaiaNet’s capability to decentralize AI interaction and application. With an impressive daily request volume, GaiaNet has validated its approach and is ready to scale with the Beta launch. This milestone underscores the demand for decentralized AI solutions and sets the stage for broader adoption. GaiaNet's progress has been marked by significant milestones, including a strategic partnership with UC Berkeley FHL Vive Center announced earlier this year. This collaboration aims to introduce decentralized AI teaching assistant technology into more education courses, leveraging AI inference power on a distributed Gaia Network. Additionally, GaiaNet raised $10 million in seed funding, announced on May 28, 2024. This funding fuels the mission to revolutionize AI interactions and applications across various sectors. Join the Revolution GaiaNet is dedicated to revolutionizing the AI landscape by decentralizing AI agent software and providing a fair, transparent, and secure environment. GaiaNet’s network of edge nodes enables decentralized AI interactions, empowering individuals and businesses to harness AI's power in innovative ways. The Beta launch represents a significant step in the mission to redefine AI interaction, and everyone is welcome to join the campaigns and be part of this transformative journey. For more information about the Beta launch and to participate in our community campaigns, visit www.gaianet.ai and follow us on X @GaiaNet_AI. About GaiaNet GaiaNet stands as a trailblazer in decentralized AI technology, dedicated to reshaping the tech industry with a focus on user privacy, transparency, and control. Our cutting-edge open network infrastructure empowers users by ensuring privacy and censorship resistance in daily AI activities through a dynamic network of peer-to-peer edge nodes. This framework fosters the creation and collaboration of innovative AI business ecosystems, benefiting both private data holders and developers. GaiaNet aims to revolutionize the user experience with AI agents, seamlessly introducing transformative changes while preserving the intuitive technology and satisfaction currently existing in the Web2 era. Website: www.gaianet.ai Github: https://github.com/GaiaNet-AI X: @GaiaNet_AI This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here. SAN FRANCISCO, CA, June 4, 2024 — GaiaNet, the pioneering decentralized AI infrastructure project that aims to disrupt central AI inferencing servers like ChatGPT, today announced the launch of its Beta product. The launch follows the completion of the Alpha testing phase, during which the platform successfully handled a tremendous volume of daily requests on Telegram, Discord and X. The Beta release focuses on the ease of setting up a GaiaNet node, ensuring that users, from individuals to businesses, can effortlessly integrate into the network. With a user-friendly interface, GaiaNet simplifies the process, making its innovative solutions accessible to users of all technical levels. The commencement of beta testing marks a significant step forward in GaiaNet’s commitment to building a more inclusive and equitable AI ecosystem. With plans to roll out more functionalities in 2024, the platform is on the brink of redefining the boundaries of AI, making it more accessible, data bias-resistant, collaborative, and privacy-centric. Early Adopters Campaign To celebrate the Beta launch, GaiaNet invites the community to join the interactive campaigns on X, Discord, Telegram, and Warpcast. GaiaNet has a community and user-oriented philosophy; therefore, early users and community members can look forward to exclusive benefits. By actively setting up nodes and interacting with GaiaNet agents across different nodes, users can join the beta product testing and potentially unlock special rewards in the future. More details will be revealed soon. The Alpha phase demonstrated GaiaNet’s capability to decentralize AI interaction and application. With an impressive daily request volume, GaiaNet has validated its approach and is ready to scale with the Beta launch. This milestone underscores the demand for decentralized AI solutions and sets the stage for broader adoption. GaiaNet's progress has been marked by significant milestones, including a strategic partnership with UC Berkeley FHL Vive Center announced earlier this year. This collaboration aims to introduce decentralized AI teaching assistant technology into more education courses, leveraging AI inference power on a distributed Gaia Network. Additionally, GaiaNet raised $10 million in seed funding, announced on May 28, 2024. This funding fuels the mission to revolutionize AI interactions and applications across various sectors. Join the Revolution GaiaNet is dedicated to revolutionizing the AI landscape by decentralizing AI agent software and providing a fair, transparent, and secure environment. GaiaNet’s network of edge nodes enables decentralized AI interactions, empowering individuals and businesses to harness AI's power in innovative ways. The Beta launch represents a significant step in the mission to redefine AI interaction, and everyone is welcome to join the campaigns and be part of this transformative journey. For more information about the Beta launch and to participate in our community campaigns, visit www.gaianet.ai and follow us on X @GaiaNet_AI. www.gaianet.ai About GaiaNet GaiaNet stands as a trailblazer in decentralized AI technology, dedicated to reshaping the tech industry with a focus on user privacy, transparency, and control. Our cutting-edge open network infrastructure empowers users by ensuring privacy and censorship resistance in daily AI activities through a dynamic network of peer-to-peer edge nodes. This framework fosters the creation and collaboration of innovative AI business ecosystems, benefiting both private data holders and developers. GaiaNet aims to revolutionize the user experience with AI agents, seamlessly introducing transformative changes while preserving the intuitive technology and satisfaction currently existing in the Web2 era. Website: www.gaianet.ai Github: https://github.com/GaiaNet-AI X: @GaiaNet_AI www.gaianet.ai https://github.com/GaiaNet-AI This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

GaiaNet Announces Beta Product Launch Following Successful Alpha Phase

Climate Tech, Emerging Tech - October 9, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “Startups of The Year” award, featuring the most promising and innovative companies in the Climate Tech startup ecosystem. The list, compiled by the HackerNoon team, showcases 30 startups making significant contributions and driving innovation in the Climate Tech industry. https://youtu.be/XOpG6B4AKPU?embedable=true Nominations are open - learn more here. You can nominate your company as the Startup of The Year in the Climate Tech industry here. The Startups in the Climate Tech industry nominated for Startups of The Year 2024 include: Matteco


IDEALERS B2B PVT LTD


Terrenity


HIJAU (c/o. PT Investasi Hijau Selaras)


Undesert Corporation


Waterly


Felicidad


Tracco


seeng LTD


Tree++ (Tree Plus Plus)


LEAP for Climate


Aatral ESP


ÁCARA CLIMATE


RenTech Global Solutions


VALKYRIE SOLAR SOLUTIONS


Alder Green Solutions


H2next


Eurasia Natural History Association


Climate Change Writers


Global Cerah


Tasteme


Virya Energy


Zetin Solar Technology Kenya


R.Flo


Ocergy


CENmat


Achelous Pure Metal Co. Ltd.


GoNetZero


Silogic Technology


Gaia First “We are thrilled to recognize the top startups in the Climate Tech industry and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO. “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” Why It Pays Off to Be Nominated Startups of The Year 2024 is a 100% community-driven voting event recognizing startups transforming technology and the world for the better. Starting October 1st, 2024, the internet can nominate and vote for the best ventures in their city and industry. People can nominate their favorite startups until October 31st, and vote once per day per award for who they think should be Startup of The Year up to March 31st, 2025. Winners will be announced in April 2025, after a comprehensive evaluation by the HackerNoon team. Apart from validation from the world's greenest tech publication, all nominees get free interviews relevant to their region and industry. They will also receive curated startup-friendly packages and a free version of their very own Evergreen Tech Company News Page on HackerNoon. In sum, being nominated gives you major credibility as one of the top startups globally and an expert in your industry, meaning even without winning, you still gain tons of exposure. Nominations are open - learn more here. You can nominate your company as the Startup of The Year in the Climate Tech industry here. About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries will participate in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many stories have been written about these daring and rising startups. The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. Visit our FAQ page to learn more. Download our design assets here. Check out the Startups of The Year Merch Shop here. HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated startup-friendly packages to solve your marketing challenges. Meet our sponsors: Wellfound: Join the #1 global, startup-focused community. At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months, to build and scale your company with one powerful tool. Get your offer now! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Get started for free. Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection, businesses can grow from a small operation to an enterprise by harnessing insights at every stage. Algolia: Algolia NeuralSearch is the world's only AI end-to-end Search and Discovery Platform combining powerful keyword and natural language processing in a single API. Climate Tech, Emerging Tech - October 9, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “Startups of The Year” award, featuring the most promising and innovative companies in the Climate Tech startup ecosystem. Climate Tech, Emerging Tech - October 9, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “Startups of The Year” award, featuring the most promising and innovative companies in the Climate Tech startup ecosystem. Climate Tech , Emerging Tech - October 9, 2024 Tech - October 9, 2024 - HackerNoon, the independent technology publishing platform, is pleased to announce the nominees for its annual “ Startups of The Year ” award, featuring the most promising and innovative companies in the Startups of The Year startup ecosystem. The list, compiled by the HackerNoon team, showcases 30 startups making significant contributions and driving innovation in the Climate Tech industry. https://youtu.be/XOpG6B4AKPU?embedable=true https://youtu.be/XOpG6B4AKPU?embedable=true Nominations are open - learn more here. You can nominate your company as the Startup of The Year in the Climate Tech industry here. Nominations are open - learn more here . You can nominate your company as the Startup of The Year in the Climate Tech industry here . here Startup of The Year in the Climate Tech industry here Startup of The Year in the Climate Tech industry here The Startups in the Climate Tech industry nominated for Startups of The Year 2024 include: Startups in the Climate Tech industry nominated Startups in the Climate Tech industry Startups in the Climate Tech industry Matteco IDEALERS B2B PVT LTD Terrenity HIJAU (c/o. PT Investasi Hijau Selaras) Undesert Corporation Waterly Felicidad Tracco seeng LTD Tree++ (Tree Plus Plus) LEAP for Climate Aatral ESP ÁCARA CLIMATE RenTech Global Solutions VALKYRIE SOLAR SOLUTIONS Alder Green Solutions H2next Eurasia Natural History Association Climate Change Writers Global Cerah Tasteme Virya Energy Zetin Solar Technology Kenya R.Flo Ocergy CENmat Achelous Pure Metal Co. Ltd. GoNetZero Silogic Technology Gaia First Matteco Matteco IDEALERS B2B PVT LTD IDEALERS B2B PVT LTD Terrenity Terrenity HIJAU (c/o. PT Investasi Hijau Selaras) HIJAU (c/o. PT Investasi Hijau Selaras) Undesert Corporation Undesert Corporation Waterly Waterly Felicidad Felicidad Tracco Tracco seeng LTD seeng LTD Tree++ (Tree Plus Plus) Tree++ (Tree Plus Plus) LEAP for Climate LEAP for Climate Aatral ESP Aatral ESP ÁCARA CLIMATE ÁCARA CLIMATE RenTech Global Solutions RenTech Global Solutions VALKYRIE SOLAR SOLUTIONS VALKYRIE SOLAR SOLUTIONS Alder Green Solutions Alder Green Solutions H2next H2next Eurasia Natural History Association Eurasia Natural History Association Climate Change Writers Climate Change Writers Global Cerah Global Cerah Tasteme Tasteme Virya Energy Virya Energy Zetin Solar Technology Kenya Zetin Solar Technology Kenya R.Flo R.Flo Ocergy Ocergy CENmat CENmat Achelous Pure Metal Co. Ltd. Achelous Pure Metal Co. Ltd. GoNetZero GoNetZero Silogic Technology Silogic Technology Gaia First Gaia First “We are thrilled to recognize the top startups in the Climate Tech industry and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO. “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” “We are thrilled to recognize the top startups in the Climate Tech industry and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO. “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” “We are thrilled to recognize the top startups in the Climate Tech industry and celebrate their achievements,” said David Smooke, HackerNoon Founder & CEO . “Starting and sustaining a company is difficult. We’re honored to showcase their work and impact.” David Smooke, HackerNoon Founder & CEO Why It Pays Off to Be Nominated Startups of The Year 2024 is a 100% community-driven voting event recognizing startups transforming technology and the world for the better. Starting October 1st, 2024, the internet can nominate and vote for the best ventures in their city and industry. People can nominate their favorite startups until October 31st , and vote once per day per award for who they think should be Startup of The Year up to March 31st, 2025. Winners will be announced in April 2025, after a comprehensive evaluation by the HackerNoon team. Startups of The Year 2024 nominate their favorite startups until October 31st nominate their favorite startups Apart from validation from the world's greenest tech publication, all nominees get free interviews relevant to their region and industry. They will also receive curated startup-friendly packages and a free version of their very own Evergreen Tech Company News Page on HackerNoon. get free interviews startup-friendly packages startup-friendly packages Evergreen Tech Company News Evergreen Tech Company News In sum, being nominated gives you major credibility as one of the top startups globally and an expert in your industry, meaning even without winning, you still gain tons of exposure. Nominations are open - learn more here. You can nominate your company as the Startup of The Year in the Climate Tech industry here. Nominations are open - learn more here . You can nominate your company as the Startup of The Year in the Climate Tech industry here . here Startup of The Year in the Climate Tech industry here Startup of The Year in the Climate Tech industry here About HackerNoon’s Startups of The Year Startups of The Year 2024 is HackerNoon’s flagship community-driven event celebrating startups, technology, and the spirit of innovation. Currently in its third iteration, the prestigious Internet award recognizes and celebrates tech startups of all shapes and sizes. This year, over 150,000 entities across 4200+ cities, 6 continents, and 100+ industries will participate in a bid to be crowned the best startup of the year! Millions of votes have been cast over the past few years, and many stories have been written about these daring and rising startups. Startups of The Year 2024 Startups of The Year 2024 many stories many stories The winners will get a free interview on HackerNoon and an Evergreen Tech Company News page. free interview on HackerNoon Evergreen Tech Company News Evergreen Tech Company News Visit our FAQ page to learn more. FAQ FAQ Download our design assets here . here here Check out the Startups of The Year Merch Shop here . here here HackerNoon’s Startups of The Year is a branding opportunity unlike any other. Whether your goal is brand awareness or lead generation, HackerNoon has curated startup-friendly packages to solve your marketing challenges. startup-friendly packages startup-friendly packages Meet our sponsors: Meet our sponsors: Meet our sponsors: Wellfound: Join the #1 global, startup-focused community . At Wellfound, we're not just a job board—we're the place where top startup talent and the world's most exciting companies connect to build the future. Wellfound: Join the #1 global, startup-focused community Join the #1 global, startup-focused community Notion: Notion is trusted and loved by thousands of startups as their connected workspace—from building product roadmaps to tracking fundraising. Try Notion with unlimited AI, FREE for up to 6 months , to build and scale your company with one powerful tool. Get your offer now ! Notion: Try Notion with unlimited AI, FREE for up to 6 months Get your offer now ! Hubspot: If you’re looking for a smart CRM platform that meets the needs of small businesses, look no further than HubSpot. Seamlessly connect your data, teams and customers in one easy-to-use scalable platform that grows with your business. Get started for free . Hubspot: Get started for free Get started for free Bright Data: Startups that leverage public web data can make faster, data-driven decisions, giving them a competitive edge. With Bright Data’s scalable web data collection , businesses can grow from a small operation to an enterprise by harnessing insights at every stage. Bright Data: Bright Data’s scalable web data collection Bright Data’s scalable web data collection Algolia: Algolia NeuralSearch is the world's only AI end-to-end Search and Discovery Platform combining powerful keyword and natural language processing in a single API. Algolia: AI end-to-end Search and Discovery Platform AI end-to-end Search and Discovery Platform

Startups of The Year 2024: 3,246 Startups Nominated in the Climate Tech Industry

የ2024 የአመቱ ጅምር፡ 3,246 ጅምር በአየር ንብረት ቴክ ኢንዱስትሪ ውስጥ ተመርጠዋል።

Стартапы 2024 года: 3246 стартапаў, намінаваных у індустрыі кліматычных тэхналогій

Startupy roku 2024: 3 246 nominovaných startupů v odvětví Climate Tech

Startups del año 2024: 3246 startups nominadas en la industria de la tecnología climática

Startups do ano 2024: 3.246 startups nomeadas na industria da tecnoloxía climática

Startupovi godine 2024.: 3246 startupova nominiranih u industriji klimatskih tehnologija

Startup dell'anno 2024: 3.246 startup nominate nel settore Climate Tech

2024年のスタートアップ・オブ・ザ・イヤー：気候技術業界で3,246社のスタートアップがノミネート

წლის სტარტაპები 2024: 3246 სტარტაპი ნომინირებულია კლიმატის ტექნოლოგიების ინდუსტრიაში

2024 жылдың стартаптары: климаттық технологиялар индустриясында 3 246 стартап ұсынылды

Startups of the Year 2024: 3 246 startupov nominovaných v odvetví klimatických technológií

Các công ty khởi nghiệp của năm 2024: 3.246 công ty khởi nghiệp được đề cử trong ngành công nghệ khí hậu

Thermodynamic Limits Around M-dwarf Stars: Acknowledgements

How AI and Blockchain are Converging: A Look into IVS Crypto 2024's Innovative Approach

এআই এবং ব্লকচেইন কীভাবে একত্রিত হচ্ছে: IVS ক্রিপ্টো 2024-এর উদ্ভাবনী পদ্ধতির দিকে একটি নজর

Wie KI und Blockchain zusammenwachsen: Ein Blick auf den innovativen Ansatz von IVS Crypto 2024

Cómo convergen la IA y Blockchain: una mirada al enfoque innovador de IVS Crypto 2024

Comment l'IA et la blockchain convergent : un aperçu de l'approche innovante d'IVS Crypto 2024

एआई और ब्लॉकचेन कैसे एक दूसरे से जुड़ रहे हैं: आईवीएस क्रिप्टो 2024 के अभिनव दृष्टिकोण पर एक नज़र

AIとブロックチェーンの融合: IVS Crypto 2024の革新的なアプローチを検証

AI와 블록체인이 융합되는 방식: IVS Crypto 2024의 혁신적인 접근 방식 살펴보기

Como a IA e o Blockchain estão convergindo: uma análise da abordagem inovadora do IVS Crypto 2024

Как ИИ и блокчейн объединяются: взгляд на инновационный подход IVS Crypto 2024

Yapay Zeka ve Blockchain Nasıl Birleşiyor: IVS Crypto 2024'ün Yenilikçi Yaklaşımına Bir Bakış

AI và Blockchain đang hội tụ như thế nào: Nhìn vào phương pháp tiếp cận đổi mới của IVS Crypto 2024

人工智能与区块链如何融合：了解 IVS Crypto 2024 的创新方法

Authors:
(1) Youn Kil Jung, Korea Astronomy and Space Science Institute, University of Science and Technology, and The KMTNet Collaboration;
(2) Cheongho Han, Department of Physics, Chungbuk National University and The KMTNet Collaboration;
(3) Andrzej Udalski, Warsaw University Observatory and The OGLE Collaboration;
(4) Andrew Gould, Korea Astronomy and Space Science Institute, Department of Astronomy, Ohio State University, Max-Planck-Institute for Astronomy and The KMTNet Collaboration;
(5) Jennifer C. Yee, Center for Astrophysics | Harvard & Smithsonian and The KMTNet Collaboration;
(6) Michael D. Albrow, University of Canterbury, Department of Physics and Astronomy;
(7) Sun-Ju Chung, Korea Astronomy and Space Science Institute and University of Science and Technology;
(8) Kyu-Ha Hwang, Korea Astronomy and Space Science Institute;
(9) Yoon-Hyun Ryu, Korea Astronomy and Space Science Institute;
(10) In-Gu Shin, Korea Astronomy and Space Science Institute;
(11) Yossi Shvartzvald, Department of Particle Physics and Astrophysics, Weizmann Institute of Science;
(12) Wei Zhu, Canadian Institute for Theoretical Astrophysics, University of Toronto;
(13) Weicheng Zang, Department of Astronomy, Tsinghua University;
(14) Sang-Mok Cha, Korea Astronomy and Space Science Institute and 2School of Space Research, Kyung Hee University;
(15) Dong-Jin Kim, Korea Astronomy and Space Science Institute;
(16) Hyoun-Woo Kim, Korea Astronomy and Space Science Institute;
(17) Seung-Lee Kim, Korea Astronomy and Space Science Institute and University of Science and Technology;
(18) Chung-Uk Lee, Korea Astronomy and Space Science Institute and University of Science and Technology;
(19) Dong-Joo Lee, Korea Astronomy and Space Science Institute;
(20) Yongseok Lee, Korea Astronomy and Space Science Institute and School of Space Research, Kyung Hee University;
(21) Byeong-Gon Park, Korea Astronomy and Space Science Institute and University of Science and Technology;
(22) Richard W. Pogge, Department of Astronomy, Ohio State University;
(23) Przemek Mroz, Warsaw University Observatory and Division of Physics, Mathematics, and Astronomy, California Institute of Technology;
(24) Michal K. Szymanski, Warsaw University Observatory;
(25) Jan Skowron, Warsaw University Observatory;
(26) Radek Poleski, Warsaw University Observatory and Department of Astronomy, Ohio State University;
(27) Igor Soszynski, Warsaw University Observatory;
(28) Pawel Pietrukowicz, Warsaw University Observatory;
(29) Szymon Kozlowski, Warsaw University Observatory;
(30) Krzystof Ulaczyk, Department of Physics, University of Warwick, Gibbet;
(31) Krzysztof A. Rybicki, Warsaw University Observatory;
(32) Patryk Iwanek, Warsaw University Observatory;
(33) Marcin Wrona, Warsaw University Observatory. Table of Links Abstract and Intro
Observation
Light Curve Analysis
Physical Parameters
Microlensing Planets in the (log s, log q) plane
Summary and Conclusions
References REFERENCES Alard, C., & Lupton, Robert H. 1998, ApJ, 503, 325 Alcock, C., Allsman, R. A., Axelrod, T. S., et al. 1995, ApJ, 445, 133 Albrow, M. D. 2017, MichaelDAlbrow/pyDIA: Initial release on github, V1.0.0, Zenodo, doi:10.5281/zenodo.268049 Albrow, M. D., Horne, K., Bramich, D. M., et al. 2009, MNRAS, 397, 2099 Beaulieu, J.-P., Bennett, D. P., Fouqu´e, P., et al. 2006, Nature, 439, 437 Bennett, D.P., Rhie, S.H., Nikolaev, S. et al. 2010, ApJ, 713, 837 Bennett, D. P., Sumi, T., Bond, I. A., et al. 2012, ApJ, 757, 119 Bensby, T., Yee, J. C., Feltzing, S., et al. 2013, A&A, 549, 147 Bessell, M. S., & Brett, J. M. 1988, PASP, 100, 1134 Bond, I. A., Abe, F., Dodd, R. J. 2001, MNRAS, 327, 868 Bond, I.A., Udalski, A., Jaroszy´nski, M. et al. 2004, ApJ, 606, L155 Dominik, M. 1998, A&A, 329, 361 Dominik, M. 1999, A&A, 349, 108 Dong, S., Gould, A., Udalski, A. et al. 2009, ApJ, 695, 970 Gaia Collaboration, Brown, A. G. A., Vallenari, A., et al. 2018, A&A, 616, 1 Gaia Collaboration, Prusti, T., de Bruijne, J. H. J., et al. 2016, A&A, 595, A1 Gaudi, B.S. 1998, ApJ, 506, 533 Gaudi, B. S. 2012, ARA&A, 50, 411 Gaudi, B.S., Bennett, D.P., Udalski, A. et al. 2008, Science, 319, 927 Gould, A. 1992, ApJ, 392, 442 Gould, A. 1997, in Variables Stars and the Astrophysical Returns of the Microlensing Surveys, ed. R. Ferlet, J.-P. Maillard, & B. Raban (Gif-sur-Yvette, France: Editions Frontieres), 125 Gould, A. 2000, ApJ, 542, 785 Gould, A. & Gaucherel, C. 1997, ApJ, 477, 580 Gould, A., & Loeb, A. 1992, ApJ, 396, 104 Gould, A., Dong, S., Gaudi, B. S., et al. 2010, ApJ, 720, 1073 Gould, A., Udalski, A., Shin, I.-G. et al. 2014, Science, 345, 46 Griest, K., & Safizadeh, N. 1998, ApJ, 500, 37 Han, C., & Gould, A. 1995, ApJ, 447, 53 Han, C., & Gould, A. 2003, ApJ, 592, 172 Han, C., Udalski, A., Gould, A., et al. 2017, AJ, 154, 133 Han, C., Udalski, A., Gould, A., et al. 2020, AJ, 159, 91 Holtzman, J. A., Watson, A. M., Baum, W. A., et al. 1998, AJ, 115, 1946 Hwang, K.-H., Ryu, Y.-H., Kim, H.-W., et al. 2019, AJ, 157, 23 Hwang, K.-H., Udalski, A., Shvartzvald, Y., et al. 2018, AJ, 155, 20 Ida, S., & Lin, D. N. C. 2004, ApJ, 616, 567 Jung, Y. K., Gould, A., Udalski, A, et al. 2019, AJ, 158, 28 Jung, Y. K., Udalski, A., Gould, A., et al. 2018, AJ, 155, 219 Jung, Y. K., Udalski, A., Sumi, T., et al. 2015, ApJ, 798, 123 Jung, Y. K., Udalski, A., Yee, J. C., et al. 2017, AJ, 153, 129 Han, C. 2006, ApJ, 638, 1080 Kayser, R., Refsdal S., & Stabell, R. 1986, A&A, 166, 36 Kennedy, G. M., & Kenyon, S. J. 2008, ApJ, 673, 502 Kervella, P., Bersier, D., Mourard, D., et al. 2004a, A&A, 428, 587 Kervella, P., Th´evenin, F., Di Folco, E., & S´egransan, D. 2004b, A&A, 426, 297 Kim, D.-J., Kim, H.-W., Hwang, K.-H., et al. 2018, AJ, 155, 76 Kim, S.-L., Lee, C.-U., Park, B.-G., et al. 2016, JKAS, 49, 37 Nataf, D. M., Gould, A., Fouqu´e, P., et al. 2013, ApJ, 769, 88 Paczy´nski, B. 1986, ApJ, 304, 1 Pecaut, M. J., & Mamajek, E. E. 2013, ApJS, 208, 9 Poleski, R., Skowron, J., Udalski, A., et al. 2014, ApJ, 795, 42 Poleski, R., Suzuki, D., Udalski, A., et al. 2020, AJ, 159, 261 Poleski, R., Udalski, A., Bond, I. A., et al. 2017, A&A, 604A, 103 Rattenbury, N. J., Bennett, D. P., Sumi, T., et al. 2015, MNRAS, 454, 946 Rhie, S. H., Bennett, D. P., Becker, A. C., et al. 2000, ApJ, 533, 378 Robin, A. C., Reyl´e, C., Derri´ere, S., & Picaud, S. 2003, A&A, 409, 523 Schneider, P., & Weiss, A. 1986, A&A, 164, 237 Schneider, P., & Weiss, A. 1987, A&A, 171, 49 Skowron, J., Udalski, A., Poleski, R., et al. 2016, ApJ, 820, 4 Skowron, J., Ryu, Y.-H., Hwang, K.-H., et al. 2018, AcA, 68, 43 Sumi, T., Bennett, D. P., Bond, I. A., et al. 2013, ApJ, 778, 150 Sumi, T., Udalski, A., Bennett, D. P., et al. 2016, ApJ, 825, 112 Suzuki, D., Bennett, D. P., Udalski, A., et al. 2018, AJ, 155, 263 Szyma´nski, M. K., Udalski, A., Soszy´nski, I., et al. 2011, AcA, 61, 83 Tomaney, A.B. & Crotts, A.P.S. 1996, AJ, 112, 2872 Udalski, A. 2003, Acta Astron., 53, 291 Udalski, A., Szyma´nski, M., Ka lu˙zny, J., Kubiak, M., & Mateo, M. 1992, AcA, 42, 253 Udalski, A., Szyma´nski, M. K., & Szyma´nski, G. 2015, AcA, 65, 1 Udalski, A., Jaroszy´nski, M., Paczy´nski, B., et al. 2005, ApJ, 628, L109 Wo´zniak, P. R. 2000, AcA, 50, 42 Yee, J. C., Shvartzvald, Y., Gal-Yam, A., et al. 2012, ApJ, 755, 102 Yee, J. C., Zang, W., Udalski, A., et al. 2021, arXiv:2101.04696 Yoo, J., DePoy, D. L., Gal-Yam, A., et al. 2004, ApJ, 603, 139 This paper is available on arxiv under CC0 1.0 DEED license. Authors: (1) Youn Kil Jung, Korea Astronomy and Space Science Institute, University of Science and Technology, and The KMTNet Collaboration; (2) Cheongho Han, Department of Physics, Chungbuk National University and The KMTNet Collaboration; (3) Andrzej Udalski, Warsaw University Observatory and The OGLE Collaboration; (4) Andrew Gould, Korea Astronomy and Space Science Institute, Department of Astronomy, Ohio State University, Max-Planck-Institute for Astronomy and The KMTNet Collaboration; (5) Jennifer C. Yee, Center for Astrophysics | Harvard & Smithsonian and The KMTNet Collaboration; (6) Michael D. Albrow, University of Canterbury, Department of Physics and Astronomy; (7) Sun-Ju Chung, Korea Astronomy and Space Science Institute and University of Science and Technology; (8) Kyu-Ha Hwang, Korea Astronomy and Space Science Institute; (9) Yoon-Hyun Ryu, Korea Astronomy and Space Science Institute; (10) In-Gu Shin, Korea Astronomy and Space Science Institute; (11) Yossi Shvartzvald, Department of Particle Physics and Astrophysics, Weizmann Institute of Science; (12) Wei Zhu, Canadian Institute for Theoretical Astrophysics, University of Toronto; (13) Weicheng Zang, Department of Astronomy, Tsinghua University; (14) Sang-Mok Cha, Korea Astronomy and Space Science Institute and 2School of Space Research, Kyung Hee University; (15) Dong-Jin Kim, Korea Astronomy and Space Science Institute; (16) Hyoun-Woo Kim, Korea Astronomy and Space Science Institute; (17) Seung-Lee Kim, Korea Astronomy and Space Science Institute and University of Science and Technology; (18) Chung-Uk Lee, Korea Astronomy and Space Science Institute and University of Science and Technology; (19) Dong-Joo Lee, Korea Astronomy and Space Science Institute; (20) Yongseok Lee, Korea Astronomy and Space Science Institute and School of Space Research, Kyung Hee University; (21) Byeong-Gon Park, Korea Astronomy and Space Science Institute and University of Science and Technology; (22) Richard W. Pogge, Department of Astronomy, Ohio State University; (23) Przemek Mroz, Warsaw University Observatory and Division of Physics, Mathematics, and Astronomy, California Institute of Technology; (24) Michal K. Szymanski, Warsaw University Observatory; (25) Jan Skowron, Warsaw University Observatory; (26) Radek Poleski, Warsaw University Observatory and Department of Astronomy, Ohio State University; (27) Igor Soszynski, Warsaw University Observatory; (28) Pawel Pietrukowicz, Warsaw University Observatory; (29) Szymon Kozlowski, Warsaw University Observatory; (30) Krzystof Ulaczyk, Department of Physics, University of Warwick, Gibbet; (31) Krzysztof A. Rybicki, Warsaw University Observatory; (32) Patryk Iwanek, Warsaw University Observatory; (33) Marcin Wrona, Warsaw University Observatory. Authors: Authors: (1) Youn Kil Jung, Korea Astronomy and Space Science Institute, University of Science and Technology, and The KMTNet Collaboration; (2) Cheongho Han, Department of Physics, Chungbuk National University and The KMTNet Collaboration; (3) Andrzej Udalski, Warsaw University Observatory and The OGLE Collaboration; (4) Andrew Gould, Korea Astronomy and Space Science Institute, Department of Astronomy, Ohio State University, Max-Planck-Institute for Astronomy and The KMTNet Collaboration; (5) Jennifer C. Yee, Center for Astrophysics | Harvard & Smithsonian and The KMTNet Collaboration; (6) Michael D. Albrow, University of Canterbury, Department of Physics and Astronomy; (7) Sun-Ju Chung, Korea Astronomy and Space Science Institute and University of Science and Technology; (8) Kyu-Ha Hwang, Korea Astronomy and Space Science Institute; (9) Yoon-Hyun Ryu, Korea Astronomy and Space Science Institute; (10) In-Gu Shin, Korea Astronomy and Space Science Institute; (11) Yossi Shvartzvald, Department of Particle Physics and Astrophysics, Weizmann Institute of Science; (12) Wei Zhu, Canadian Institute for Theoretical Astrophysics, University of Toronto; (13) Weicheng Zang, Department of Astronomy, Tsinghua University; (14) Sang-Mok Cha, Korea Astronomy and Space Science Institute and 2School of Space Research, Kyung Hee University; (15) Dong-Jin Kim, Korea Astronomy and Space Science Institute; (16) Hyoun-Woo Kim, Korea Astronomy and Space Science Institute; (17) Seung-Lee Kim, Korea Astronomy and Space Science Institute and University of Science and Technology; (18) Chung-Uk Lee, Korea Astronomy and Space Science Institute and University of Science and Technology; (19) Dong-Joo Lee, Korea Astronomy and Space Science Institute; (20) Yongseok Lee, Korea Astronomy and Space Science Institute and School of Space Research, Kyung Hee University; (21) Byeong-Gon Park, Korea Astronomy and Space Science Institute and University of Science and Technology; (22) Richard W. Pogge, Department of Astronomy, Ohio State University; (23) Przemek Mroz, Warsaw University Observatory and Division of Physics, Mathematics, and Astronomy, California Institute of Technology; (24) Michal K. Szymanski, Warsaw University Observatory; (25) Jan Skowron, Warsaw University Observatory; (26) Radek Poleski, Warsaw University Observatory and Department of Astronomy, Ohio State University; (27) Igor Soszynski, Warsaw University Observatory; (28) Pawel Pietrukowicz, Warsaw University Observatory; (29) Szymon Kozlowski, Warsaw University Observatory; (30) Krzystof Ulaczyk, Department of Physics, University of Warwick, Gibbet; (31) Krzysztof A. Rybicki, Warsaw University Observatory; (32) Patryk Iwanek, Warsaw University Observatory; (33) Marcin Wrona, Warsaw University Observatory. Table of Links Abstract and Intro Observation Light Curve Analysis Physical Parameters Microlensing Planets in the (log s, log q) plane Summary and Conclusions References Abstract and Intro Abstract and Intro Observation Observation Light Curve Analysis Light Curve Analysis Physical Parameters Physical Parameters Microlensing Planets in the (log s , log q ) plane Microlensing Planets in the (log s s , log q q ) plane Summary and Conclusions Summary and Conclusions References References REFERENCES Alard, C., & Lupton, Robert H. 1998, ApJ, 503, 325 Alcock, C., Allsman, R. A., Axelrod, T. S., et al. 1995, ApJ, 445, 133 Albrow, M. D. 2017, MichaelDAlbrow/pyDIA: Initial release on github, V1.0.0, Zenodo, doi:10.5281/zenodo.268049 Albrow, M. D., Horne, K., Bramich, D. M., et al. 2009, MNRAS, 397, 2099 Beaulieu, J.-P., Bennett, D. P., Fouqu´e, P., et al. 2006, Nature, 439, 437 Bennett, D.P., Rhie, S.H., Nikolaev, S. et al. 2010, ApJ, 713, 837 Bennett, D. P., Sumi, T., Bond, I. A., et al. 2012, ApJ, 757, 119 Bensby, T., Yee, J. C., Feltzing, S., et al. 2013, A&A, 549, 147 Bessell, M. S., & Brett, J. M. 1988, PASP, 100, 1134 Bond, I. A., Abe, F., Dodd, R. J. 2001, MNRAS, 327, 868 Bond, I.A., Udalski, A., Jaroszy´nski, M. et al. 2004, ApJ, 606, L155 Dominik, M. 1998, A&A, 329, 361 Dominik, M. 1999, A&A, 349, 108 Dong, S., Gould, A., Udalski, A. et al. 2009, ApJ, 695, 970 Gaia Collaboration, Brown, A. G. A., Vallenari, A., et al. 2018, A&A, 616, 1 Gaia Collaboration, Prusti, T., de Bruijne, J. H. J., et al. 2016, A&A, 595, A1 Gaudi, B.S. 1998, ApJ, 506, 533 Gaudi, B. S. 2012, ARA&A, 50, 411 Gaudi, B.S., Bennett, D.P., Udalski, A. et al. 2008, Science, 319, 927 Gould, A. 1992, ApJ, 392, 442 Gould, A. 1997, in Variables Stars and the Astrophysical Returns of the Microlensing Surveys, ed. R. Ferlet, J.-P. Maillard, & B. Raban (Gif-sur-Yvette, France: Editions Frontieres), 125 Gould, A. 2000, ApJ, 542, 785 Gould, A. & Gaucherel, C. 1997, ApJ, 477, 580 Gould, A., & Loeb, A. 1992, ApJ, 396, 104 Gould, A., Dong, S., Gaudi, B. S., et al. 2010, ApJ, 720, 1073 Gould, A., Udalski, A., Shin, I.-G. et al. 2014, Science, 345, 46 Griest, K., & Safizadeh, N. 1998, ApJ, 500, 37 Han, C., & Gould, A. 1995, ApJ, 447, 53 Han, C., & Gould, A. 2003, ApJ, 592, 172 Han, C., Udalski, A., Gould, A., et al. 2017, AJ, 154, 133 Han, C., Udalski, A., Gould, A., et al. 2020, AJ, 159, 91 Holtzman, J. A., Watson, A. M., Baum, W. A., et al. 1998, AJ, 115, 1946 Hwang, K.-H., Ryu, Y.-H., Kim, H.-W., et al. 2019, AJ, 157, 23 Hwang, K.-H., Udalski, A., Shvartzvald, Y., et al. 2018, AJ, 155, 20 Ida, S., & Lin, D. N. C. 2004, ApJ, 616, 567 Jung, Y. K., Gould, A., Udalski, A, et al. 2019, AJ, 158, 28 Jung, Y. K., Udalski, A., Gould, A., et al. 2018, AJ, 155, 219 Jung, Y. K., Udalski, A., Sumi, T., et al. 2015, ApJ, 798, 123 Jung, Y. K., Udalski, A., Yee, J. C., et al. 2017, AJ, 153, 129 Han, C. 2006, ApJ, 638, 1080 Kayser, R., Refsdal S., & Stabell, R. 1986, A&A, 166, 36 Kennedy, G. M., & Kenyon, S. J. 2008, ApJ, 673, 502 Kervella, P., Bersier, D., Mourard, D., et al. 2004a, A&A, 428, 587 Kervella, P., Th´evenin, F., Di Folco, E., & S´egransan, D. 2004b, A&A, 426, 297 Kim, D.-J., Kim, H.-W., Hwang, K.-H., et al. 2018, AJ, 155, 76 Kim, S.-L., Lee, C.-U., Park, B.-G., et al. 2016, JKAS, 49, 37 Nataf, D. M., Gould, A., Fouqu´e, P., et al. 2013, ApJ, 769, 88 Paczy´nski, B. 1986, ApJ, 304, 1 Pecaut, M. J., & Mamajek, E. E. 2013, ApJS, 208, 9 Poleski, R., Skowron, J., Udalski, A., et al. 2014, ApJ, 795, 42 Poleski, R., Suzuki, D., Udalski, A., et al. 2020, AJ, 159, 261 Poleski, R., Udalski, A., Bond, I. A., et al. 2017, A&A, 604A, 103 Rattenbury, N. J., Bennett, D. P., Sumi, T., et al. 2015, MNRAS, 454, 946 Rhie, S. H., Bennett, D. P., Becker, A. C., et al. 2000, ApJ, 533, 378 Robin, A. C., Reyl´e, C., Derri´ere, S., & Picaud, S. 2003, A&A, 409, 523 Schneider, P., & Weiss, A. 1986, A&A, 164, 237 Schneider, P., & Weiss, A. 1987, A&A, 171, 49 Skowron, J., Udalski, A., Poleski, R., et al. 2016, ApJ, 820, 4 Skowron, J., Ryu, Y.-H., Hwang, K.-H., et al. 2018, AcA, 68, 43 Sumi, T., Bennett, D. P., Bond, I. A., et al. 2013, ApJ, 778, 150 Sumi, T., Udalski, A., Bennett, D. P., et al. 2016, ApJ, 825, 112 Suzuki, D., Bennett, D. P., Udalski, A., et al. 2018, AJ, 155, 263 Szyma´nski, M. K., Udalski, A., Soszy´nski, I., et al. 2011, AcA, 61, 83 Tomaney, A.B. & Crotts, A.P.S. 1996, AJ, 112, 2872 Udalski, A. 2003, Acta Astron., 53, 291 Udalski, A., Szyma´nski, M., Ka lu˙zny, J., Kubiak, M., & Mateo, M. 1992, AcA, 42, 253 Udalski, A., Szyma´nski, M. K., & Szyma´nski, G. 2015, AcA, 65, 1 Udalski, A., Jaroszy´nski, M., Paczy´nski, B., et al. 2005, ApJ, 628, L109 Wo´zniak, P. R. 2000, AcA, 50, 42 Yee, J. C., Shvartzvald, Y., Gal-Yam, A., et al. 2012, ApJ, 755, 102 Yee, J. C., Zang, W., Udalski, A., et al. 2021, arXiv:2101.04696 Yoo, J., DePoy, D. L., Gal-Yam, A., et al. 2004, ApJ, 603, 139 This paper is available on arxiv under CC0 1.0 DEED license. This paper is available on arxiv under CC0 1.0 DEED license. available on arxiv

Two Microlensing Planets through Planetary-Caustic Channel: References

প্ল্যানেটারি-কস্টিক চ্যানেলের মাধ্যমে দুটি মাইক্রোলেনসিং গ্রহ: তথ্যসূত্র

Zwei Mikrolinsenplaneten durch den planetar-kaustischen Kanal: Referenzen

Dos planetas con microlentes a través del canal cáustico planetario: referencias

Deux planètes à microlentille via un canal planétaire-caustique : références

ग्रहीय-कास्टिक चैनल के माध्यम से दो माइक्रोलेंसिंग ग्रह: संदर्भ

惑星-コースティックチャネルを通した2つのマイクロレンズ効果を持つ惑星: 参考文献

행성 가성 채널을 통한 두 개의 미세 렌즈 행성: 참고 자료

Dois planetas microlentes através do canal cáustico-planetário: referências

Две микролинзирующие планеты через планетарно-каустический канал: ссылки

Gezegensel-Kostik Kanal Üzerinden İki Mikro Mercekleme Gezegeni: Referanslar

Hai hành tinh vi thấu kính thông qua Kênh ăn da hành tinh: Tài liệu tham khảo

通过行星焦散通道观察两颗微透镜行星：参考文献

Authors:
(1) Youn Kil Jung, Korea Astronomy and Space Science Institute, University of Science and Technology, and The KMTNet Collaboration;
(2) Cheongho Han, Department of Physics, Chungbuk National University and The KMTNet Collaboration;
(3) Andrzej Udalski, Warsaw University Observatory and The OGLE Collaboration;
(4) Andrew Gould, Korea Astronomy and Space Science Institute, Department of Astronomy, Ohio State University, Max-Planck-Institute for Astronomy and The KMTNet Collaboration;
(5) Jennifer C. Yee, Center for Astrophysics | Harvard & Smithsonian and The KMTNet Collaboration;
(6) Michael D. Albrow, University of Canterbury, Department of Physics and Astronomy;
(7) Sun-Ju Chung, Korea Astronomy and Space Science Institute and University of Science and Technology;
(8) Kyu-Ha Hwang, Korea Astronomy and Space Science Institute;
(9) Yoon-Hyun Ryu, Korea Astronomy and Space Science Institute;
(10) In-Gu Shin, Korea Astronomy and Space Science Institute;
(11) Yossi Shvartzvald, Department of Particle Physics and Astrophysics, Weizmann Institute of Science;
(12) Wei Zhu, Canadian Institute for Theoretical Astrophysics, University of Toronto;
(13) Weicheng Zang, Department of Astronomy, Tsinghua University;
(14) Sang-Mok Cha, Korea Astronomy and Space Science Institute and 2School of Space Research, Kyung Hee University;
(15) Dong-Jin Kim, Korea Astronomy and Space Science Institute;
(16) Hyoun-Woo Kim, Korea Astronomy and Space Science Institute;
(17) Seung-Lee Kim, Korea Astronomy and Space Science Institute and University of Science and Technology;
(18) Chung-Uk Lee, Korea Astronomy and Space Science Institute and University of Science and Technology;
(19) Dong-Joo Lee, Korea Astronomy and Space Science Institute;
(20) Yongseok Lee, Korea Astronomy and Space Science Institute and School of Space Research, Kyung Hee University;
(21) Byeong-Gon Park, Korea Astronomy and Space Science Institute and University of Science and Technology;
(22) Richard W. Pogge, Department of Astronomy, Ohio State University;
(23) Przemek Mroz, Warsaw University Observatory and Division of Physics, Mathematics, and Astronomy, California Institute of Technology;
(24) Michal K. Szymanski, Warsaw University Observatory;
(25) Jan Skowron, Warsaw University Observatory;
(26) Radek Poleski, Warsaw University Observatory and Department of Astronomy, Ohio State University;
(27) Igor Soszynski, Warsaw University Observatory;
(28) Pawel Pietrukowicz, Warsaw University Observatory;
(29) Szymon Kozlowski, Warsaw University Observatory;
(30) Krzystof Ulaczyk, Department of Physics, University of Warwick, Gibbet;
(31) Krzysztof A. Rybicki, Warsaw University Observatory;
(32) Patryk Iwanek, Warsaw University Observatory;
(33) Marcin Wrona, Warsaw University Observatory. Table of Links Abstract and Intro
Observation
Light Curve Analysis
Physical Parameters
Microlensing Planets in the (log s, log q) plane
Summary and Conclusions
References 4. Physical Parameters The bulge VD is modeled based on stars in the Gaia catalog (Gaia Collaboration et al. 2016, 2018). That is, we first find red giant stars in the catalog within 2 arcmin centered on the event location. We then derive their mean velocity and its dispersion in Galactocentric Cartesian coordinates (x, y, z) as defined in Han & Gould (1995). This paper is available on arxiv under CC0 1.0 DEED license. Authors: (1) Youn Kil Jung, Korea Astronomy and Space Science Institute, University of Science and Technology, and The KMTNet Collaboration; (2) Cheongho Han, Department of Physics, Chungbuk National University and The KMTNet Collaboration; (3) Andrzej Udalski, Warsaw University Observatory and The OGLE Collaboration; (4) Andrew Gould, Korea Astronomy and Space Science Institute, Department of Astronomy, Ohio State University, Max-Planck-Institute for Astronomy and The KMTNet Collaboration; (5) Jennifer C. Yee, Center for Astrophysics | Harvard & Smithsonian and The KMTNet Collaboration; (6) Michael D. Albrow, University of Canterbury, Department of Physics and Astronomy; (7) Sun-Ju Chung, Korea Astronomy and Space Science Institute and University of Science and Technology; (8) Kyu-Ha Hwang, Korea Astronomy and Space Science Institute; (9) Yoon-Hyun Ryu, Korea Astronomy and Space Science Institute; (10) In-Gu Shin, Korea Astronomy and Space Science Institute; (11) Yossi Shvartzvald, Department of Particle Physics and Astrophysics, Weizmann Institute of Science; (12) Wei Zhu, Canadian Institute for Theoretical Astrophysics, University of Toronto; (13) Weicheng Zang, Department of Astronomy, Tsinghua University; (14) Sang-Mok Cha, Korea Astronomy and Space Science Institute and 2School of Space Research, Kyung Hee University; (15) Dong-Jin Kim, Korea Astronomy and Space Science Institute; (16) Hyoun-Woo Kim, Korea Astronomy and Space Science Institute; (17) Seung-Lee Kim, Korea Astronomy and Space Science Institute and University of Science and Technology; (18) Chung-Uk Lee, Korea Astronomy and Space Science Institute and University of Science and Technology; (19) Dong-Joo Lee, Korea Astronomy and Space Science Institute; (20) Yongseok Lee, Korea Astronomy and Space Science Institute and School of Space Research, Kyung Hee University; (21) Byeong-Gon Park, Korea Astronomy and Space Science Institute and University of Science and Technology; (22) Richard W. Pogge, Department of Astronomy, Ohio State University; (23) Przemek Mroz, Warsaw University Observatory and Division of Physics, Mathematics, and Astronomy, California Institute of Technology; (24) Michal K. Szymanski, Warsaw University Observatory; (25) Jan Skowron, Warsaw University Observatory; (26) Radek Poleski, Warsaw University Observatory and Department of Astronomy, Ohio State University; (27) Igor Soszynski, Warsaw University Observatory; (28) Pawel Pietrukowicz, Warsaw University Observatory; (29) Szymon Kozlowski, Warsaw University Observatory; (30) Krzystof Ulaczyk, Department of Physics, University of Warwick, Gibbet; (31) Krzysztof A. Rybicki, Warsaw University Observatory; (32) Patryk Iwanek, Warsaw University Observatory; (33) Marcin Wrona, Warsaw University Observatory. Authors: Authors: (1) Youn Kil Jung, Korea Astronomy and Space Science Institute, University of Science and Technology, and The KMTNet Collaboration; (2) Cheongho Han, Department of Physics, Chungbuk National University and The KMTNet Collaboration; (3) Andrzej Udalski, Warsaw University Observatory and The OGLE Collaboration; (4) Andrew Gould, Korea Astronomy and Space Science Institute, Department of Astronomy, Ohio State University, Max-Planck-Institute for Astronomy and The KMTNet Collaboration; (5) Jennifer C. Yee, Center for Astrophysics | Harvard & Smithsonian and The KMTNet Collaboration; (6) Michael D. Albrow, University of Canterbury, Department of Physics and Astronomy; (7) Sun-Ju Chung, Korea Astronomy and Space Science Institute and University of Science and Technology; (8) Kyu-Ha Hwang, Korea Astronomy and Space Science Institute; (9) Yoon-Hyun Ryu, Korea Astronomy and Space Science Institute; (10) In-Gu Shin, Korea Astronomy and Space Science Institute; (11) Yossi Shvartzvald, Department of Particle Physics and Astrophysics, Weizmann Institute of Science; (12) Wei Zhu, Canadian Institute for Theoretical Astrophysics, University of Toronto; (13) Weicheng Zang, Department of Astronomy, Tsinghua University; (14) Sang-Mok Cha, Korea Astronomy and Space Science Institute and 2School of Space Research, Kyung Hee University; (15) Dong-Jin Kim, Korea Astronomy and Space Science Institute; (16) Hyoun-Woo Kim, Korea Astronomy and Space Science Institute; (17) Seung-Lee Kim, Korea Astronomy and Space Science Institute and University of Science and Technology; (18) Chung-Uk Lee, Korea Astronomy and Space Science Institute and University of Science and Technology; (19) Dong-Joo Lee, Korea Astronomy and Space Science Institute; (20) Yongseok Lee, Korea Astronomy and Space Science Institute and School of Space Research, Kyung Hee University; (21) Byeong-Gon Park, Korea Astronomy and Space Science Institute and University of Science and Technology; (22) Richard W. Pogge, Department of Astronomy, Ohio State University; (23) Przemek Mroz, Warsaw University Observatory and Division of Physics, Mathematics, and Astronomy, California Institute of Technology; (24) Michal K. Szymanski, Warsaw University Observatory; (25) Jan Skowron, Warsaw University Observatory; (26) Radek Poleski, Warsaw University Observatory and Department of Astronomy, Ohio State University; (27) Igor Soszynski, Warsaw University Observatory; (28) Pawel Pietrukowicz, Warsaw University Observatory; (29) Szymon Kozlowski, Warsaw University Observatory; (30) Krzystof Ulaczyk, Department of Physics, University of Warwick, Gibbet; (31) Krzysztof A. Rybicki, Warsaw University Observatory; (32) Patryk Iwanek, Warsaw University Observatory; (33) Marcin Wrona, Warsaw University Observatory. Table of Links Abstract and Intro Observation Light Curve Analysis Physical Parameters Microlensing Planets in the (log s, log q) plane Summary and Conclusions References Abstract and Intro Abstract and Intro Observation Observation Light Curve Analysis Light Curve Analysis Physical Parameters Physical Parameters Microlensing Planets in the (log s , log q ) plane Microlensing Planets in the (log s s , log q q ) plane Summary and Conclusions Summary and Conclusions References References 4. Physical Parameters The bulge VD is modeled based on stars in the Gaia catalog (Gaia Collaboration et al. 2016, 2018). That is, we first find red giant stars in the catalog within 2 arcmin centered on the event location. We then derive their mean velocity and its dispersion in Galactocentric Cartesian coordinates ( x, y, z ) as defined in Han & Gould (1995). x, y, z This paper is available on arxiv under CC0 1.0 DEED license. This paper is available on arxiv under CC0 1.0 DEED license. available on arxiv

Two Microlensing Planets through Planetary-Caustic Channel: Physical Parameters

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Colliding Magnetospheres in The Young High-Eccentricity Binary DQ Tau:Acknowledgments and References

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Konstantin V. Getman, Department of Astronomy & Astrophysics, Pennsylvania State University;
(2) Agnes Kospal, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences, E¨otv¨os Lor´and Research Network (ELKH), MTA Centre of
Excellence, Max Planck Institute for Astronomy, and ELTE E¨otv¨os Lor´and University, Institute of Physics;
(3) Nicole Arulanantham, Space Telescope Science Institute;
(4) Dmitry A. Semenov, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences;
(5) Grigorii V. Smirnov-Pinchukov, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences;
(6) Sierk E. van Terwisga, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences. Table of Links Abstract and Intro
X-ray Observations and Data Extraction
Flare Analyses
Comparison with X-ray Flares from Young Stars
Discussion
Conclusions
Acknowledgments and References ABSTRACT DQ Tau is a unique young high-eccentricity binary system that exhibits regular magnetic reconnection flares and pulsed accretion near periastron. We conducted NuSTAR, Swift, and Chandra observations during the July 30, 2022 periastron to characterize X-ray, near-ultraviolet (NUV), and optical flaring emissions. Our findings confirm the presence of X-ray super-flares accompanied by substantial NUV and optical flares, consistent with previous discoveries of periastron flares in 2010 and 2021. These observations, supported by new evidence, strongly establish the magnetosphere collision mechanism as the primary driver of magnetic energy release during DQ Tau’s periastron flares. The energetics of the observed X-ray super-flares remain consistent across the three periastrons, indicating recurring energy sources during each passage, surpassing the capabilities of single stars. The observed flaring across multiple bands supports the Adams et al. model for magnetosphere interaction in eccentric binaries. Evidence from modeling and past and current observations suggests that both the mm/X-ray periastron flares and tentatively, the magnetic reconnection-related components of the optical/NUV emissions, conform to the classical solar/stellar non-thermal thick-target model, except for the distinctive magnetic energy source. However, our NuSTAR observations suffered from high background levels, hindering the detection of anticipated non-thermal hard X-rays. Furthermore, we report serendipitous discovery of X-ray super-flares occurring away from periastron, potentially associated with interacting magnetospheres. The current study is part of a broader multi-wavelength campaign, which is planned to investigate the influence of DQ Tau’s stellar radiation on gas-phase ion chemistry within its circumbinary disk. Keywords: Pre-main sequence stars (1290) — Spectroscopic binary stars (1557) — X-ray stars (1823) — Stellar magnetic fields (1610) — Optical flares (1166) — Ultraviolet transient sources (1854) —- Stellar x-ray flares (1637) — Solar x-ray flares (1816) — Solar flares (1496) — Stellar flares (1603) — Protoplanetary disks (1300) 1. INTRODUCTION DQ Tau is a nearby (D = 195 pc; Gaia Collaboration et al. 2023), non-eclipsing, double-lined spectro scopic binary system, consisting of two pre-main sequence (PMS) stars of equal mass (0.6 M⊙) and equal radius (2 R⊙) (Mathieu et al. 1997; Czekala et al. 2016; Pouilly et al. 2023). These stars exhibit spectral types within the range of M0 to K7. The rotational periods of the primary and secondary components are 3 days (K´osp´al et al. 2018) and 4.5 days (Pouilly et al. in prep.), respectively. The orbital period measures 15.8 days. DQ Tau boasts a highly eccentric orbit (e ∼ 0.6) and displays an exceptionally small periastron separation, measuring only about 8 −10 stellar radii (Mathieu et al. 1997; Czekala et al. 2016; Pouilly et al. 2023). Furthermore, the binary components of DQ Tau harbor relatively strong surface magnetic fields, estimated at around 2.5 kG, which give rise to formidable magnetospheres (Pouilly et al. 2023, Pouilly et al. in prep.). Surrounding DQ Tau is a protoplanetary disk of average size (≤ 100 au), complete with a small 0.3 au cavity (Czekala et al. 2016; K´osp´al et al. 2018; Ballering & Eisner 2019). Large optical and UV brightenings primarily occur at orbital phase (Φ = 0.8 − 1.2), and they are mainly attributed to the pulsed accretion of disk material onto the binary components (Tofflemire et al. 2017; K´osp´al et al. 2018; Muzerolle et al. 2019; Fiorellino et al. 2022). However, far-UV (FUV) observations of DQ Tau with the Cosmic Origins Spectrograph onboard HST (HST-COS) showed no correlation between the orbital phase of the binary and the C IV flux, a tracer of mass accretion rate, indicating that some component of the behavior is stochastic (Ardila et al. 2015). The system exhibits powerful mm/X-ray flares coinciding with periastron passage, attributed to collisions between the magnetospheres of the binary components. The evidence supporting the magnetsophere collision hypothesis includes the recurrence of synchrotron mmband flaring during 4 periastron encounters (Salter et al. 2008, 2010), the recurrence of soft X-ray flaring in 2 periastron encounters (Getman et al. 2011, 2022a), the timing and energy relationships between the mm and X-ray flares, and the consistency observed between the flare loop size and binary separation (Salter et al. 2010; Getman et al. 2011). Several other young binary systems with high eccentricities have been reported to exhibit enhanced levels of either X-ray, optical/mm, or radio emissions near their periastron passages. Notable examples include ϵ Lupi (Das et al. 2023), a collective study of four binaries (Parenago 523, RX J1622.7-2325 Nw, UZ Tau E, and HD 152404) conducted by Getman et al. (2016), UZ Tau E (K´osp´al et al. 2011), and V773 Tau A (Massi et al. 2008; Adams et al. 2011). In these systems, magnetosphere collision has been proposed as a primary mechanism responsible for generating the magnetic reconnection energy that drives these events. Modelling studies have shown that PMS X-rays have strong impact on disk ionization and chemistry (Glassgold et al. 2000; Alexander et al. 2014). But most studies assume continuous irradiation without considering the high-amplitude variations in flux and spectrum due to super-flares. A few time-dependent calculations show that disk ionization may respond to sudden large Xray flares (Rab et al. 2017; Waggoner & Cleeves 2022). This may already have been seen. One empirical report of ionization variability has emerged: the H13CO+ abundance of IM Lup’s disk jumped up and down by a factor of 2.5 over months (Cleeves et al. 2017). However, since no concurrent X-ray observations were conducted, the exact cause cannot be definitively ascribed to X-ray flaring. The occurrence of large X-ray flares in young stars is relatively rare and unpredictable, displaying a stochastic nature (Getman & Feigelson 2021). However, the presence of predictable X-ray super-flares and accretion outbursts in close proximity to periastron passage makes DQ Tau an extraordinary laboratory for investigating the influence of stellar radiation on the gas-phase ion chemistry within its disk. To achieve this, we conducted a single X-ray observation using the NuSTAR telescope, along with multiple short-duration observations using the Swift telescope in the X-ray, UV, and optical wavelengths. These observations were strategically timed near a specific periastron passage of DQ Tau, taking place in July-August 2022. Additionally, we captured multiple snapshots of the non-periastron portion of DQ Tau’s orbit using the Chandra X-ray telescope. However, we encountered unfavorable weather conditions that limited our ALMA observations to a single short session near periastron. The results from this ALMA observation will be presented in a forthcoming paper. Meanwhile, building upon the X-ray/UV/optical data acquired in 2022 and the previously obtained X-ray/mm data (Salter et al. 2010; Getman et al. 2011, 2022a), our current study is dedicated to further investigating the origins and energetic properties of X-ray flares, along with their corresponding near-ultraviolet (NUV) and optical flare counterparts, observed within the remarkable young binary system DQ Tau. The structure of the paper is outlined as follows: Section 2 provides a detailed description of the data reduction and reduction procedures employed for X-ray, UV, and optical analyses. In Section 3, we present the detection of flares and examine their spectral properties. Section 4 offers a comparison between the X-ray periastron flares observed in DQ Tau and super-flares observed in numerous other PMS stars. Finally, Section 5 delves into a discussion surrounding the origin and energetics of the X-ray flares, as well as their associated NUV and optical counterparts. This paper is available on arxiv under CC 4.0 license. Authors: (1) Konstantin V. Getman, Department of Astronomy & Astrophysics, Pennsylvania State University; (2) Agnes Kospal, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences, E¨otv¨os Lor´and Research Network (ELKH), MTA Centre of Excellence, Max Planck Institute for Astronomy, and ELTE E¨otv¨os Lor´and University, Institute of Physics; (3) Nicole Arulanantham, Space Telescope Science Institute; (4) Dmitry A. Semenov, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences; (5) Grigorii V. Smirnov-Pinchukov, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences; (6) Sierk E. van Terwisga, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Konstantin V. Getman, Department of Astronomy & Astrophysics, Pennsylvania State University; (2) Agnes Kospal, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences, E¨otv¨os Lor´and Research Network (ELKH), MTA Centre of Excellence, Max Planck Institute for Astronomy, and ELTE E¨otv¨os Lor´and University, Institute of Physics; (3) Nicole Arulanantham, Space Telescope Science Institute; (4) Dmitry A. Semenov, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences; (5) Grigorii V. Smirnov-Pinchukov, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences; (6) Sierk E. van Terwisga, Konkoly Observatory, Research Centre for Astronomy and Earth Sciences. Table of Links Abstract and Intro X-ray Observations and Data Extraction Flare Analyses Comparison with X-ray Flares from Young Stars Discussion Conclusions Acknowledgments and References Abstract and Intro Abstract and Intro X-ray Observations and Data Extraction X-ray Observations and Data Extraction Flare Analyses Flare Analyses Comparison with X-ray Flares from Young Stars Comparison with X-ray Flares from Young Stars Discussion Discussion Conclusions Conclusions Acknowledgments and References Acknowledgments and References ABSTRACT DQ Tau is a unique young high-eccentricity binary system that exhibits regular magnetic reconnection flares and pulsed accretion near periastron. We conducted NuSTAR, Swift, and Chandra observations during the July 30, 2022 periastron to characterize X-ray, near-ultraviolet (NUV), and optical flaring emissions. Our findings confirm the presence of X-ray super-flares accompanied by substantial NUV and optical flares, consistent with previous discoveries of periastron flares in 2010 and 2021. These observations, supported by new evidence, strongly establish the magnetosphere collision mechanism as the primary driver of magnetic energy release during DQ Tau’s periastron flares. The energetics of the observed X-ray super-flares remain consistent across the three periastrons, indicating recurring energy sources during each passage, surpassing the capabilities of single stars. The observed flaring across multiple bands supports the Adams et al. model for magnetosphere interaction in eccentric binaries. Evidence from modeling and past and current observations suggests that both the mm/X-ray periastron flares and tentatively, the magnetic reconnection-related components of the optical/NUV emissions, conform to the classical solar/stellar non-thermal thick-target model, except for the distinctive magnetic energy source. However, our N u STAR observations suffered from high background levels, hindering the detection of anticipated non-thermal hard X-rays. Furthermore, we report serendipitous discovery of X-ray super-flares occurring away from periastron, potentially associated with interacting magnetospheres. The current study is part of a broader multi-wavelength campaign, which is planned to investigate the influence of DQ Tau’s stellar radiation on gas-phase ion chemistry within its circumbinary disk. u Keywords : Pre-main sequence stars (1290) — Spectroscopic binary stars (1557) — X-ray stars (1823) — Stellar magnetic fields (1610) — Optical flares (1166) — Ultraviolet transient sources (1854) —- Stellar x-ray flares (1637) — Solar x-ray flares (1816) — Solar flares (1496) — Stellar flares (1603) — Protoplanetary disks (1300) Keywords 1. INTRODUCTION DQ Tau is a nearby (D = 195 pc; Gaia Collaboration et al. 2023), non-eclipsing, double-lined spectro scopic binary system, consisting of two pre-main sequence (PMS) stars of equal mass (0.6 M⊙) and equal radius (2 R⊙) (Mathieu et al. 1997; Czekala et al. 2016; Pouilly et al. 2023). These stars exhibit spectral types within the range of M0 to K7. The rotational periods of the primary and secondary components are 3 days (K´osp´al et al. 2018) and 4.5 days (Pouilly et al. in prep.), respectively. The orbital period measures 15.8 days. DQ Tau boasts a highly eccentric orbit (e ∼ 0.6) and displays an exceptionally small periastron separation, measuring only about 8 −10 stellar radii (Mathieu et al. 1997; Czekala et al. 2016; Pouilly et al. 2023). Furthermore, the binary components of DQ Tau harbor relatively strong surface magnetic fields, estimated at around 2.5 kG, which give rise to formidable magnetospheres (Pouilly et al. 2023, Pouilly et al. in prep.). Surrounding DQ Tau is a protoplanetary disk of average size (≤ 100 au), complete with a small 0.3 au cavity (Czekala et al. 2016; K´osp´al et al. 2018; Ballering & Eisner 2019). Large optical and UV brightenings primarily occur at orbital phase (Φ = 0.8 − 1.2), and they are mainly attributed to the pulsed accretion of disk material onto the binary components (Tofflemire et al. 2017; K´osp´al et al. 2018; Muzerolle et al. 2019; Fiorellino et al. 2022). However, far-UV (FUV) observations of DQ Tau with the Cosmic Origins Spectrograph onboard HST (HST-COS) showed no correlation between the orbital phase of the binary and the C IV flux, a tracer of mass accretion rate, indicating that some component of the behavior is stochastic (Ardila et al. 2015). The system exhibits powerful mm/X-ray flares coinciding with periastron passage, attributed to collisions between the magnetospheres of the binary components. The evidence supporting the magnetsophere collision hypothesis includes the recurrence of synchrotron mmband flaring during 4 periastron encounters (Salter et al. 2008, 2010), the recurrence of soft X-ray flaring in 2 periastron encounters (Getman et al. 2011, 2022a), the timing and energy relationships between the mm and X-ray flares, and the consistency observed between the flare loop size and binary separation (Salter et al. 2010; Getman et al. 2011). Several other young binary systems with high eccentricities have been reported to exhibit enhanced levels of either X-ray, optical/mm, or radio emissions near their periastron passages. Notable examples include ϵ Lupi (Das et al. 2023), a collective study of four binaries (Parenago 523, RX J1622.7-2325 Nw, UZ Tau E, and HD 152404) conducted by Getman et al. (2016), UZ Tau E (K´osp´al et al. 2011), and V773 Tau A (Massi et al. 2008; Adams et al. 2011). In these systems, magnetosphere collision has been proposed as a primary mechanism responsible for generating the magnetic reconnection energy that drives these events. Modelling studies have shown that PMS X-rays have strong impact on disk ionization and chemistry (Glassgold et al. 2000; Alexander et al. 2014). But most studies assume continuous irradiation without considering the high-amplitude variations in flux and spectrum due to super-flares. A few time-dependent calculations show that disk ionization may respond to sudden large Xray flares (Rab et al. 2017; Waggoner & Cleeves 2022). This may already have been seen. One empirical report of ionization variability has emerged: the H13CO+ abundance of IM Lup’s disk jumped up and down by a factor of 2.5 over months (Cleeves et al. 2017). However, since no concurrent X-ray observations were conducted, the exact cause cannot be definitively ascribed to X-ray flaring. The occurrence of large X-ray flares in young stars is relatively rare and unpredictable, displaying a stochastic nature (Getman & Feigelson 2021). However, the presence of predictable X-ray super-flares and accretion outbursts in close proximity to periastron passage makes DQ Tau an extraordinary laboratory for investigating the influence of stellar radiation on the gas-phase ion chemistry within its disk. To achieve this, we conducted a single X-ray observation using the N u STAR telescope, along with multiple short-duration observations using the Swift telescope in the X-ray, UV, and optical wavelengths. These observations were strategically timed near a specific periastron passage of DQ Tau, taking place in July-August 2022. Additionally, we captured multiple snapshots of the non-periastron portion of DQ Tau’s orbit using the Chandra X-ray telescope. However, we encountered unfavorable weather conditions that limited our ALMA observations to a single short session near periastron. The results from this ALMA observation will be presented in a forthcoming paper. u Meanwhile, building upon the X-ray/UV/optical data acquired in 2022 and the previously obtained X-ray/mm data (Salter et al. 2010; Getman et al. 2011, 2022a), our current study is dedicated to further investigating the origins and energetic properties of X-ray flares, along with their corresponding near-ultraviolet (NUV) and optical flare counterparts, observed within the remarkable young binary system DQ Tau. The structure of the paper is outlined as follows: Section 2 provides a detailed description of the data reduction and reduction procedures employed for X-ray, UV, and optical analyses. In Section 3, we present the detection of flares and examine their spectral properties. Section 4 offers a comparison between the X-ray periastron flares observed in DQ Tau and super-flares observed in numerous other PMS stars. Finally, Section 5 delves into a discussion surrounding the origin and energetics of the X-ray flares, as well as their associated NUV and optical counterparts.

Colliding Magnetospheres in The Young High-Eccentricity Binary DQ Tau: Abstract and Intro

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