We want to bring innovations faster to everyone by reducing the time and resources needed to go from an idea to a market-ready electronic product

Luminovo

luminovo

For growing startups, finding top talent is key to successful scalability. However, most companies at this level don't have dedicated HR, and talent acquisition can be time-consuming and costly. The trick is to attract top talent to you and then engage and delight them. As it turns out, employer branding follows the same game plan as branding your product or service to your customers. But can startups pull it off? Definitely. How the big players do it At the enterprise level, the gold standard for employer branding in Southeast Asia is described in this of Ericsson, who in 2015 began a transformation that led to reducing cost per hire by 70%. case study But reducing CPH wasn’t the only goal. At the time, Ericsson was in the middle of a decade-long upscaling mission, from handset manufacturer to a dynamic ICT company providing industry-leading solutions in areas such as mobility, TV and media, cloud, and IP. They needed talented people to make this happen so they developed their employer branding by working on three things: employee advocacy, social media, career page. But this was spearheaded by a dedicated specialist, Tristram Gray, VP and head of HR for Ericsson. Most startups around here don’t have HR. They stick to what they know and who they know. How startups find talent in Taiwan In most startups, HR is handled by whoever has time to do it, and when it comes to finding high-quality candidates, 53% of the startups we surveyed in Taiwan claim personal networking is best. And for talent retention, a similar result: 60% of respondents think personal networking works well. For hiring speed though, job boards have the edge: These results are not surprising in the context of Taiwan's startup culture. Job boards like 104.com are always there if a position needs to be filled quickly. But for finding quality hires that stay long-term, company leaders often go to their personal network of trusted friends and former classmates/colleagues. Besides that, referrals from current employees may provide reliable leads. Startups congregate in places like the in Yuanshan, in shared office spaces, in tech districts like Neihu and Xizhi, and they attend startup industry gatherings. Startup Stadium Everyone is connected on Linkedin and Facebook. New relationships are budding all the time and personal networks do grow, but will they grow with your business? Your personal network has a limit Despite the potential for network growth, the demands of your business can quickly exceed your personal network’s ability to supply talent. The next option is reaching out via social media, tech communities, or recruiting agencies. These channels have the potential for reaching more candidates, and you can even target the kinds of people you are looking for. But what happens when the gifted candidate you sought out on GitHub looks at your website and only finds products and services? That candidate journey may end there if there’s nothing special to attract them to your company. Especially if another company in your field takes the effort to promote their employer brand on their website. In Taiwan, few startups focus on employer branding. Out of the on the Startup Stadium website, only 17% have career pages; and only 13% have a combination of about/team/career pages that communicates employer branding. 52 AI startups Worldwide, employer branding is standard for startups Internationally, most startups consciously develop company culture and express it via employer branding. The term has been trending upward for quite some time: In April of last year, our company was featured on the Forbes list of . Of those startups, 75% have a career page supported by strong about/team pages (i.e. well-defined employer branding). Top 25 Machine Learning Startups To Watch in 2020 While quite honorable to make this list, it was also a wake-up call. Our company was the only one without about/team/careers pages — indeed, the only one without any employer branding. Since then, we have developed an employer branding strategy and I have been tasked with preparing it for our website relaunch. Our company culture is already excellent, the office is awesome and I work with amazing people. We just need to promote. “Up to company culture, not channel,” remarked one of our hiring channel survey respondents, who checked “other” when asked which channel provides talent that stays long term. I couldn't agree more! Four realistic employer branding tasks for startups 1. Define your EVP and employer brand Your employer value proposition (EVP) consists of three things: (should mention more than money, including flexible hours, ability to work from home, good working conditions, etc.) An attractive benefits package (a clear way to grow within the company ensures candidates won’t see the position as a stepping stone to something else) Positive career development (show what a day looks like at your company; show the workspace; show team-building events; show the perks; show love and happiness; show it all candidly; make it genuine) Authentic company culture With these terms defined, your employer brand simply becomes an offer for you to promote. It’s your EVP in exchange for someone who exhibits the company's core values. In other words, . we’re offering (this EVP) if you can excel with (these core values) 2. Enlist employees as advocates You have to get your people on board. They are the social proof that your company is a great place to work. But engineers and salespeople have enough to do. Even if you incentivize it, it’s asking a lot to enlist your startup colleagues on a program like Ericsson’s where toolkits were created to provide all Ericsson employees with a solid understanding of the employer brand and how to promote it. Source: Human Resources Online For startups, it’s enough to get everyone connected on Linkedin, Twitter, and Facebook. From there, it’s not too much to ask everyone to like, share, or comment on all product/employer branding efforts put forth on social media. It’s a good starting point, and more realistic than asking non-marketing people to post. 3. Post employer branding on social media Promoting jobs directly via Facebook, Linkedin and Twitter is an effective way to find candidates, but promoting your employer branding via these channels is an effective way to get candidates to find you. When it comes to what to post for employer branding, refer back to your EVP and core values: Working remote, working flexible hours (post in real-time about what you’re doing and where) Highlight achievements of your colleagues (post promotions, ambitious new projects) Post good photos from the office (desk, meeting rooms, lounge, kitchen, etc.) Post team building events Post going out for lunch Post a coffee break Post for birthdays Post for holidays Post ideas from industry thought leaders that align with your core values Stuff you might otherwise share on Slack (share it on social instead, have everyone like it and share it) Of course, any and all attention gained by your posts must be responded to. Engage all comments, likes, and shares. 4. Make a fantastic about/team/career page A good career page works together with good about and team pages. A company’s EVP, core values, recognition, management, and team members should function together to make the job offers on your career page more attractive. , another Forbes Top 25 company out of California, presents an informative, yet very humanized that ends with a CTA to their c . Anodot about/team page areer page Quite a few other startups in the Top 25 place the same CTA in the same spot. It’s a common site structure ( , , , etc.) amongst the Forbes Top 25. Comet Kaizo Luminovo And Anodot’s career page begins with the kind of copy that EVP-savvy job seekers want to see: Find an opportunity that promises long-term career growth with a team that's innovative, collaborative, and engaged. However, of all the startup sites surveyed for this story, my favorite about/team/career page combination is the homegrown Taiwan startup, . A couple of highlights: 25Sprout Pretty clear, this is a great place to work. Free lunch? Enough said; this is world-class employer branding. Where there's heart there's hope While many Taiwanese companies don't take the time to do employer branding, when they do it, it can be great. The reason? s . Overall Taiwanese are a practical, unsentimental bunch, but of course, there are some tender-hearts out there that take it to the extreme when they're in the mood. They can really recognize the subtle moments that signify the good in life — and they love spreading . Intense entimentality the feeling on as thick as humanly possible And perhaps there is a final lesson about employer branding for startups in this. To find top-quality talent, we certainly must empathize with the candidates we’re looking for and figure out just what they want, but we must also be in touch with ourselves and be fearless about letting it all hang out for the world to see.

Exploring Taiwanese Start Up Culture

THEORY OF COLOURS

Six books on Light and Shade

The long awaited of this series has arrived. It has taken me a significant amount of time longer to put together than I had anticipated. Now the wait is over, here it is… Part 2 of 3 This list contains companies working on artificial intelligence and machine learning products primarily for business use, non-specific to any industry. Industry specific AI will be the final part of this series. Rise of artificial intelligence is rapidly taking over the world, especially countries like Anguilla; a small island in the Eastern Caribbean with the use of their .ai top level domain for companies within the AI and robotics industry. But in all seriousness, AI is without a doubt accelerating much faster than is probably known and much more established within our daily lives than most would realise. Conducting this research has demonstrated sheer scale of the landscape and progress of the artificial intelligence industry. “Already humans and AI are co-evolving and no one has paid attention to this yet…” “When we search on Google, it’s an AI deciding what we should see. When a dating site matches two people together there’s a machine learning algorithm… that is getting people together, that then have babies. And so in effect you have this machine learning algorithm that is breeding humans.”— Sam Altman, discussing AI . here In the case of the companies listed below, business and AI are co-evolving. With so many websites to go through and dissect there may be some descriptions or names that need changing. Please let me know if that’s the case or if you think there are companies I should add to the list. Shoutout to me , and I’ll get on to it! here Artificial Intelligence for businesses (enterprise intelligence): 🔉 Audio — language transcription and recognition — ? — transcribes insights from phone calls, video footage, and online — discover more customer and employee conversations** **— makes sound searchable — critical insights about your customers conversations — building blocks to add messaging, voice, and video to web+apps Capio Clover Intelligence Deepgram Gridspace MindMeld — advanced AI to power conversational interface Nexidia — turns customer interactions into valuable insights Pop Up Archive TalkIQ Twilio 📊 Business Intelligence & Analytics — optimise and autonomously IT and business operations** ** —behavioural AI for IoT — a suite of intelligent applications for enterprise — a range of products to improve enterprise products** ** — automates repetitive tasks within your business — making complex data science easy for enterprise Arago/HIRO Arimo Ayasdi DataRobot Dataminr — discovers events and breaking information before the news — helps you to answer questions about your business — a smarter Salesforce — adds intelligent decision making to web and mobile apps — helps you index, search, visualise and analyse your data — is a framework for temporal pattern recognition and prediction — to transform raw data into useful information automatically — helps you monitor server bugs Electra by Lore Einstein Fuzzy AI Logz.io NXT AI Paxata Poweredby.ai Sundown UBIX Ruths.ai — helps you do more with your data — a marketplace for analytics — captures, categorises, and extracts key information from all your data — fast data insights using search — solves big data better, faster and at less cost — find hidden value in complex human and business ecosystems — helps to optimise pricing Exchange.ai Owl.ai AnswerRocket iSeek.ai Ecosystem.AI Prix 🍎 Core AI — a common API for many algorithms, functions and models — workbench for neural networks — advanced industry specific ML for the enterprise — advanced machine learning for enterprise — advanced machine learning for enterprise — open source machine learning and deep learning platform — advanced machine learning for enterprise — deep learning as computational system — advanced machine learning for enterprise — advanced machine learning for enterprise — range of financial, ecommerce and digital marketing AI products — open-source deep learning and ETL for enterprise on the JVM — advanced machine learning for enterprise — log Analysis for enterprises Algorithmia Arya CognitiveScale Digital Reasoning Fluid AI H2O.ai Loop AI Labs Nervana Petuum Scaled Inference Sentient Skymind Vicarious Loom Systems PipelineAI — solves the problem of production ML and AI at scale — building AI using neuroscience Ogma 📋 Data Capture — marketplace to automate simple processes — automate the discovery of objects at scale — automatically prepare any data for immediate & compliant use — helps structure data from social media and blog — automatically extract web pages as structured data — extract data from almost any website — training data, image annotation and more for enterprise** ** — tools for operations team to automate business processes Amazon Mechanical Turk CrowdAI Datalogue DataSift Diffbot Import.io Playment WorkFusion 🔬 Data Science — single platform for all predictive use cases — training data, image annotation for machine learning teams — data science platform for prototype, deploy, and run at scale — enterprise data science platform for R&D and production** ** — helps you learn, work, and play with machine learning models — makes data science teams more productive — helps DS teams put machine learning models into production — a platform to build, test, and deploy AI algorithms** **— research engine, capable of discovering complex patterns in data — makes data unification of data silos possible — helps put data into useful structures for analysis — allows data scientists to deploy and update predictive models rapidly — automate the writing of reports, websites, emails, articles and more BigML CrowdFlower Dataiku DataScience Domino Data Lab — platform for collaborating, building and deploying — makes DS accessible to analysts with OpenSource algorithms Exploratory Kaggle RapidMiner Seldon SherlockML Spark Tamr Trifacta Yhat Yseop 💻 Development — detects business incidents — develop more adaptive, trusted and programmable AI models — helps predict project timelines — adds intelligent decision making to web and mobile apps — connecting projects with the right team — augments your coding environment with web available knowledge — deep learning platform for prediction and personalisation — makes developing chatbots for your business easy — make your bot smarter, by helping it self learn — rapidly web and mobile app testing — increase server uptime and predict downtime — project management and chat software that’s easy for teams AnOdot Bonsai Deckard.ai Fuzzy.ai Gigster Kite Layer 6 AI Morph Ozz RainforestQA SignifAI Turtle Improve.ai — automatically optimises app content, design, pricing etc. — gesture recognition for developers — trains deep learning algorithms to learn like human brain — abstracts away the complexity of ML libraries like TensorFlow for more effective management of AI models — helps with decision making for designers, engineers and leaders — helps analyse algorithm Gesture.ai Cognitive Toolkit Bonsai Tangle Imandra 📂 Internal Data — helps you work together, improve productivity, and data indexing** ** — helps employees with tasks and access data using micro apps — better website analytics Alation Cycorp — a range of different AI enterprise products — takes the pain of cluster management away to focus on DS — helps predict project timelines — insight into online trends and other text analytics tools — AI platform for business Databricks Deckard.ai Gavagi IBM Watson Kyndi — helps knowledge workers process vast amounts of information — SaaS AI for risk management and operations — makes your business software smarter oneFactor Probot Sapho Sofia eContext — structure for unstructured data — create intelligent interactions between people, devices, and data — deep insights into customers and internal data —automate decision-making at scale Hayley RelativeInsight Rainbird 🤖 Machine Learning —No-code end-to-end AutoML tool that takes you from data to predictions in minutes* *__ — a range of different AI enterprise products — helps you focus your digital ad on people you want to target — analyse data in the form of images, speech, text and video — now apart of the Uber AI Labs — can do menial task work, saving time for employees — platform to unite siloed data for better recommendations — improves machine learning models 100x faster PI.Exchange — develop more adaptive, trusted and programmable AI models__ Bonsai Cycorp Datacratic deepsense.io Geometric Intelligence HyperScience Nara Logics SigOpt Amazon Machine Learn — ML-as-a-service, amongst other things — import predictive models and scale infinitely to answer existential questions Providence 📡 Sensor (IoT/IIoT) — platform delivers real-time operational insights for industry — learns about shoppers behaviour in your store — helps to unify application development and data science — sensor analytics solution for businesses — machine learning for manufacturing process optimisation — a range of workflow optimisation products for fuel and industry — helps you develop, deploy, and operate industrial apps — helps renewable energy companies utilise their data better — manufacturing analytics — automates data engineering for data science — add a voice assistant to your connected product — platform to manage the development for your IoT applications — a predictive platform for major industries — smart building management for commercial buildings Alluvium Black C3 IoT KONUX Imubit Maana Predix Planet OS Sight Machine Sentenai Snips ThingWorx Uptake Verdigris 📚 Text Analysis/Generation — creates summaries from your text and information in real-time — extract meaning from your text and visuals — text analytics and mining which works without any training** **—automatic knowledge acquisition from text — build profile and understand your users better — scaleable text analytics software — capture, measure, and act on customer feedback — scalable API to automate text classification — interprets your data more useful information — helps you find errors and inaccuracies in documents — free open-source library natural of language processing in Python — automates information extraction, management and analysis — turn text into insights — helps improve how your job ads are written — automate the writing of reports, websites, emails, articles and more Agolo AYLIEN Compreno Cortical.io — advanced language processing fido.ai IntroSpect by Lore Lexalytics Luminoso MonkeyLearn Narrative Science Qeep spaCy Salient Stride Textio Yseop 😎 Vision — add instant text capture functionality to mobile apps and more! — automated drones with vision and diagnosis capabilities — analyses subtle facial expressions to identify human emotions — makes every camera in the world smart — helps cameras to detect analyse the video feed — finds defects in wind turbines — extracts and transforms data from handwritten and typed forms — helps you to organise media libraries — visual analysis for medical and transport industry — image detection for a range of uses and industries — brand and face recognition — makes satellite imagery useful — the first intelligent cloud video platform** ** — computer vision for automative and human detection — matches similar products and helps to suggests combinations — facial recognition — uses facial recognition to help you decided on job candidates — medical data analysis and interpretation — recognises different objects and things — dedicated brand recognition for social networks — satellite image analysis — deep-learning based computer vision platform — planet monitoring and analysis using satellite imagery — satellite image analysis — is an eye and emotion tracking platform — understands and describes video content — image analysis primarily for industrial purposes ABBYY Achron Affectiva Algocian __ __i Angus.a Birds.ai Captricity Clarifai Cortica Deepomatic DeepVision Descartes Labs Flixsense FotoNation GrokStyle Haystack HireVue Lunit Inc. Matroid Netra Orbital Insight Pilot AI Labs Planet Spaceknow Sticky.ai Valossa Vidi CloudSight — high quality understanding of images within seconds — detects foreign and intentionally placed objects for security — a range of intelligent computer vision techniques Irvine Sensors Pilot.ai Originally posted → liamiscool.com

A list of artificial intelligence tools you can use today — for businesses (2/3)

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

Colliding Magnetospheres in The Young High-Eccentricity Binary DQ Tau: Discussion

Colliding Magnetospheres in The Young High-Eccentricity Binary DQ Tau: Flare Analyses

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 4. COMPARISON WITH X-RAY FLARES FROM YOUNG STARS We conducted three observations of the periastron passages of DQ Tau using X-ray telescopes: in 2010 (Getman et al. 2011), 2021 (Getman et al. 2022a), and 2022 (current study). Notably, significant X-ray flares were detected on all three occasions. In Figure 8, we compare the duration, peak X-ray luminosity, and energetics of these DQ Tau flares with numerous large X-ray flares produced by young stars, as studied by Getman et al. (2008, also known as COUP flares) and Getman & Feigelson (2021, also known as MYStIX/SFiNCs flares). In Figure 8, we only include the “main” DQ Tau X-ray flares that occur roughly within the orbital phase range of (0.95 − 1.05). However, it is important to note that more X-ray flaring events of comparable energetics are present within the (1.05 − 1.2) orbital phase range (see Figure 2 here and Figure 1 in Getman et al. (2022a)). It is also noteworthy that somewhat different methodologies for flare detection and analysis were employed in Getman et al. (2008) and Getman & Feigelson (2021), due to distinct scientific objectives pursued in these two papers As a result, Getman et al. (2008) reported the rise and decay timescales, flare peak X-ray luminosities, but no energies for the COUP flares, while Getman & Feigelson (2021) reported only total flare durations (with no differentiation between rise and decay), flare peak Xray luminosities, and energies for the MYStIX/SFiNCs flares. Consequently, the rise and decay timescales, as well as flare peak X-ray luminosities, are compared between the DQ Tau and COUP flares (see Figure 8a and b), while the flare durations, peak luminosities, and energies are compared between the DQ Tau and MYStIX/SFiNCs flares (see Figure 8c and d). Figure 8 illustrates that the DQ Tau flares lie within the loci of the COUP and MYStIX/SFiNCs flares, albeit having relatively long durations and relatively low peak flare X-ray luminosities. This places them at the sensitivity limit border of the COUP and MYStIX/SFiNCs flare surveys. 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 4. COMPARISON WITH X-RAY FLARES FROM YOUNG STARS We conducted three observations of the periastron passages of DQ Tau using X-ray telescopes: in 2010 (Getman et al. 2011), 2021 (Getman et al. 2022a), and 2022 (current study). Notably, significant X-ray flares were detected on all three occasions. In Figure 8, we compare the duration, peak X-ray luminosity, and energetics of these DQ Tau flares with numerous large X-ray flares produced by young stars, as studied by Getman et al. (2008, also known as COUP flares) and Getman & Feigelson (2021, also known as MYStIX/SFiNCs flares). In Figure 8, we only include the “main” DQ Tau X-ray flares that occur roughly within the orbital phase range of (0.95 − 1.05). However, it is important to note that more X-ray flaring events of comparable energetics are present within the (1.05 − 1.2) orbital phase range (see Figure 2 here and Figure 1 in Getman et al. (2022a)). It is also noteworthy that somewhat different methodologies for flare detection and analysis were employed in Getman et al. (2008) and Getman & Feigelson (2021), due to distinct scientific objectives pursued in these two papers As a result, Getman et al. (2008) reported the rise and decay timescales, flare peak X-ray luminosities, but no energies for the COUP flares, while Getman & Feigelson (2021) reported only total flare durations (with no differentiation between rise and decay), flare peak Xray luminosities, and energies for the MYStIX/SFiNCs flares. Consequently, the rise and decay timescales, as well as flare peak X-ray luminosities, are compared between the DQ Tau and COUP flares (see Figure 8a and b), while the flare durations, peak luminosities, and energies are compared between the DQ Tau and MYStIX/SFiNCs flares (see Figure 8c and d). Figure 8 illustrates that the DQ Tau flares lie within the loci of the COUP and MYStIX/SFiNCs flares, albeit having relatively long durations and relatively low peak flare X-ray luminosities. This places them at the sensitivity limit border of the COUP and MYStIX/SFiNCs flare surveys.

Colliding Magnetospheres: Comparison with X-ray Flares from Young Stars

Product-Market Fit Tips for Startups: Insights From 20 Experts

After an April full of exciting game releases like The Crew Motorfest, Stellar Blade, and No Rest for the Wicked, May isn’t staying even a bit behind. In this story, we are going to check out the 10 best games to be released this month. Personally, I can’t wait to play them, and you shouldn’t miss out too. Endless Ocean Luminous - May 2 https://www.youtube.com/watch?v=tKXjoA_Gai4&embedable=true Release Date: May 2
Platforms: Switch
Publisher: Arika Following the steps of his predecessors, Endless Ocean Luminous puts you in control of a scuba diver to explore the fictional Velled Sea, with over 500 species for you to discover. Team up with folks all over the world, because now, the matches allow groups of up to 30 people to explore sunk temples and shipwrecks. Crow Country - May 9 https://www.youtube.com/watch?v=iy1cICMVSTk&embedable=true Release Date: May 9
Platforms: PC, PS5
Studio: SFB Games With a retro style, Cow Country tries to bring to life the golden era of horror games; using a tank camera, its art style and mechanics resemble a lot of the classic Resident Evil games in all its glory. In this game, you’re gonna explore an abandoned park to understand why Edward has closed it while solving many puzzles and mysteries. A demo for Crow Country is available here. Little Kitty, Big City - May 9 https://www.youtube.com/watch?v=LWUdu2q88K4&embedable=true Release Date: May 9
Platforms: PC, Switch, Xbox One, Xbox Series X/S
Studio: Double Dagger Studio With a cutesy art style, Little Kitty, Big City lets you take control of a cat who is trying to go back home; you can mainly focus on finding your way back, or explore as a true cat would. Climb on people’s furniture, break their glasses, steal their objects, find collectibles, and interact with other animals before going home. Homeworld 3 - May 13 https://www.youtube.com/watch?v=oVCUI70kF7o&embedable=true Release Date: May 13
Platforms: PC
Studio: Blackbird Interactive Homeworld 3 is a galactic real-time strategy game where you can play solo, PvP, and Coop. It continues the award-winning story of Homeworld 2, with massive battles among the stars and nebulas. Now, the game also includes a coop mode for up to 3 players, in a battle on the molds of roguelike. Team up with your friends in random fleet battles while obtaining artifacts to improve your ships. The Rogue Prince of Persia - May 14 https://www.youtube.com/watch?v=XZzOxEK7hXo&embedable=true Release Date: May 14
Platforms: PC
Studio: Evil Empire The Rogue Prince of Persia is a new take on the franchise. This time, in the hands of Evil Empire, the creators of Dead Cells, this new entry will get a different art style from its predecessor and will have a roguelike gameplay, which the team at Evil Empire are professionals doing. The game will also feature a procedurally generated map, set place around the city of Ctesiphon. You will battle the Hun army that was sent to destroy the city, and it is your job to prevent it. Ghost of Tsushima: Directors Cut - May 16 https://www.youtube.com/watch?v=EzWBNwhb870&embedable=true Release Date: May 16
Platforms: PC
Studio: Sucker Punch Productions The once-Playstation exclusive is making its way to PC this month. This version includes everything from the original version and some extra functionalities due to the power of the PC. Enjoy the Tsushima island with unlocked FPS and multiple graphic customizations, support to super ultra-wide monitors, increase the performance using the functionalities of your GPU, like DLSS, FSR, and XeSS, and enjoy high-quality sync with Japanese, due to real-time cutscene rendering. Senua’s Saga: Hellblade 2 - May 21 https://www.youtube.com/watch?v=3VYGOkMnGCE&embedable=true Release Date: May 21
Platforms: PC, Xbox Series X/S
Studio: Ninja Theory In the sequel Hellblade: Senua’s Sacrifice, we follow again the story of Senua while she battles for survival on the Viking Island. There, you will fight to save the victims of the tyranny while dealing with her own darkness. System Shock: Remake - May 21 https://www.youtube.com/watch?v=mNDdQ6_pYgk&embedable=true Release Date: May 21
Platforms: PS4, PS5, Xbox One, Xbox Series X/S
Studio: Nightdive Studio The complete remake of the 1994 cult System Shock that was released for PC in 2023 is now making its way to consoles. In this game, you live in Cidadela Station, but everything gets out of hand when the most advanced AI takes control of everything, turning its people into cyborgs and mutants looking for blood. Fight for survival and destroy SHODAN before it destroys you. Paper Mario: The Thousand-Year Door - May 23 https://www.youtube.com/watch?v=gCV-uTRULn8&embedable=true Release Date: May 23
Platforms: Switch
Studio: Intelligent Systems Initially released for the GameCube in 2004, Super Paper Mario The Thousand-Year Door is an RPG praised by critics and won the RPG of the Year award in 2005. In this entry, you will take the role of Mario, while he tries to save Princess Peach from the hands of Grodus, collecting all the Crystal Stars and making new friends along the way. F1 24 - May 31 https://www.youtube.com/watch?v=NnyCWsA6KSI&embedable=true Release Date: May 31
Platforms: PC, PS4, PS5, Xbox One and Xbox Series X/S
Studio: Codemasters That is the newest entry in the F1 yearly franchise; it includes more refined graphics, a revamped campaign, a new physics system that impacts the performance of your car, crossplay, and a VR mode. Those were the games I’m keeping an eye on this month; let me know what games you are interested in this month or if I missed an important game in the comments below. After an April full of exciting game releases like The Crew Motorfest, Stellar Blade, and No Rest for the Wicked, May isn’t staying even a bit behind. In this story, we are going to check out the 10 best games to be released this month. Personally, I can’t wait to play them, and you shouldn’t miss out too. Endless Ocean Luminous - May 2 https://www.youtube.com/watch?v=tKXjoA_Gai4&embedable=true https://www.youtube.com/watch?v=tKXjoA_Gai4&embedable=true Release Date: May 2 Platforms: Switch Publisher: Arika Release Date: May 2 Release Date: Platforms: Switch Platforms: Publisher: Arika Publisher: Following the steps of his predecessors, Endless Ocean Luminous puts you in control of a scuba diver to explore the fictional Velled Sea, with over 500 species for you to discover. Team up with folks all over the world, because now, the matches allow groups of up to 30 people to explore sunk temples and shipwrecks. Crow Country - May 9 https://www.youtube.com/watch?v=iy1cICMVSTk&embedable=true https://www.youtube.com/watch?v=iy1cICMVSTk&embedable=true Release Date: May 9 Platforms: PC, PS5 Studio: SFB Games Release Date: May 9 Release Date: Platforms: PC, PS5 Platforms: Studio: SFB Games Studio: With a retro style, Cow Country tries to bring to life the golden era of horror games; using a tank camera, its art style and mechanics resemble a lot of the classic Resident Evil games in all its glory. In this game, you’re gonna explore an abandoned park to understand why Edward has closed it while solving many puzzles and mysteries. A demo for Crow Country is available here . here Little Kitty, Big City - May 9 https://www.youtube.com/watch?v=LWUdu2q88K4&embedable=true https://www.youtube.com/watch?v=LWUdu2q88K4&embedable=true Release Date: May 9 Platforms: PC, Switch, Xbox One, Xbox Series X/S Studio: Double Dagger Studio Release Date: May 9 Release Date: Platforms: PC, Switch, Xbox One, Xbox Series X/S Platforms: Studio: Double Dagger Studio Studio: With a cutesy art style, Little Kitty, Big City lets you take control of a cat who is trying to go back home; you can mainly focus on finding your way back, or explore as a true cat would. Climb on people’s furniture, break their glasses, steal their objects, find collectibles, and interact with other animals before going home. Homeworld 3 - May 13 https://www.youtube.com/watch?v=oVCUI70kF7o&embedable=true https://www.youtube.com/watch?v=oVCUI70kF7o&embedable=true Release Date: May 13 Platforms: PC Studio: Blackbird Interactive Release Date: May 13 Release Date: Platforms: PC Platforms: Studio: Blackbird Interactive Studio: Homeworld 3 is a galactic real-time strategy game where you can play solo, PvP, and Coop. It continues the award-winning story of Homeworld 2, with massive battles among the stars and nebulas. Now, the game also includes a coop mode for up to 3 players, in a battle on the molds of roguelike. Team up with your friends in random fleet battles while obtaining artifacts to improve your ships. The Rogue Prince of Persia - May 14 https://www.youtube.com/watch?v=XZzOxEK7hXo&embedable=true https://www.youtube.com/watch?v=XZzOxEK7hXo&embedable=true Release Date: May 14 Platforms: PC Studio: Evil Empire Release Date: May 14 Release Date: Platforms: PC Platforms: Studio: Evil Empire Studio: The Rogue Prince of Persia is a new take on the franchise. This time, in the hands of Evil Empire, the creators of Dead Cells, this new entry will get a different art style from its predecessor and will have a roguelike gameplay, which the team at Evil Empire are professionals doing. The game will also feature a procedurally generated map, set place around the city of Ctesiphon. You will battle the Hun army that was sent to destroy the city, and it is your job to prevent it. Ghost of Tsushima: Directors Cut - May 16 https://www.youtube.com/watch?v=EzWBNwhb870&embedable=true https://www.youtube.com/watch?v=EzWBNwhb870&embedable=true Release Date: May 16 Platforms: PC Studio: Sucker Punch Productions Release Date: May 16 Release Date: Platforms: PC Platforms: Studio: Sucker Punch Productions Studio: The once-Playstation exclusive is making its way to PC this month. This version includes everything from the original version and some extra functionalities due to the power of the PC. Enjoy the Tsushima island with unlocked FPS and multiple graphic customizations, support to super ultra-wide monitors, increase the performance using the functionalities of your GPU, like DLSS, FSR, and XeSS, and enjoy high-quality sync with Japanese, due to real-time cutscene rendering. Senua’s Saga: Hellblade 2 - May 21 https://www.youtube.com/watch?v=3VYGOkMnGCE&embedable=true https://www.youtube.com/watch?v=3VYGOkMnGCE&embedable=true Release Date: May 21 Platforms: PC, Xbox Series X/S Studio: Ninja Theory Release Date: May 21 Release Date: Platforms: PC, Xbox Series X/S Platforms: Studio: Ninja Theory Studio: In the sequel Hellblade: Senua’s Sacrifice, we follow again the story of Senua while she battles for survival on the Viking Island. There, you will fight to save the victims of the tyranny while dealing with her own darkness. System Shock: Remake - May 21 https://www.youtube.com/watch?v=mNDdQ6_pYgk&embedable=true https://www.youtube.com/watch?v=mNDdQ6_pYgk&embedable=true Release Date: May 21 Platforms: PS4, PS5, Xbox One, Xbox Series X/S Studio: Nightdive Studio Release Date: May 21 Release Date: Platforms: PS4, PS5, Xbox One, Xbox Series X/S Platforms: Studio: Nightdive Studio Studio: The complete remake of the 1994 cult System Shock that was released for PC in 2023 is now making its way to consoles. In this game, you live in Cidadela Station, but everything gets out of hand when the most advanced AI takes control of everything, turning its people into cyborgs and mutants looking for blood. Fight for survival and destroy SHODAN before it destroys you. Paper Mario: The Thousand-Year Door - May 23 https://www.youtube.com/watch?v=gCV-uTRULn8&embedable=true https://www.youtube.com/watch?v=gCV-uTRULn8&embedable=true Release Date: May 23 Platforms: Switch Studio: Intelligent Systems Release Date: May 23 Release Date: Platforms: Switch Platforms: Studio: Intelligent Systems Studio: Initially released for the GameCube in 2004, Super Paper Mario The Thousand-Year Door is an RPG praised by critics and won the RPG of the Year award in 2005. In this entry, you will take the role of Mario, while he tries to save Princess Peach from the hands of Grodus, collecting all the Crystal Stars and making new friends along the way. F1 24 - May 31 https://www.youtube.com/watch?v=NnyCWsA6KSI&embedable=true https://www.youtube.com/watch?v=NnyCWsA6KSI&embedable=true Release Date: May 31 Platforms: PC, PS4, PS5, Xbox One and Xbox Series X/S Studio: Codemasters Release Date: May 31 Release Date: Platforms: PC, PS4, PS5, Xbox One and Xbox Series X/S Platforms: Studio: Codemasters Studio: That is the newest entry in the F1 yearly franchise; it includes more refined graphics, a revamped campaign, a new physics system that impacts the performance of your car, crossplay, and a VR mode. Those were the games I’m keeping an eye on this month; let me know what games you are interested in this month or if I missed an important game in the comments below.

May 2024's Must-Play List: The Top 10 Game Releases You Can't Miss

Act 2: Life '“As the shackles of progress began to take shape, art began to guide itself to a deeper truth. Being responsible for the laws and flaws that governed the system. The shapes took distinct interpretations based on their approach to form the depth. A requirement for the power required to truly live and share the art of doing so.” Part 1: Biology ‘As the girls delved into their assignments, the world around them continued to evolve, shaped by the collective actions of individuals striving to understand and improve their surroundings. Through the exploration of science, these young students and others like them would contribute to the progress and stability of humankind.’- Rewinder Lyra, do you believe that fish transform water into breathable oxygen, and it is this process that doesn’t allow for higher degrees of thinking to develop? Uhh… I believe fishes embraced their medium. I mean… the water’s embrace seems nice. Yeah… I believe that’s why this approach is for those who like to dive into it. I can’t imagine myself doing such a thing to a fish. That’s why I like mathematics. You don’t cut anything here. Well… maybe if you want to take a closer look. But hey, at least you don’t have to deal with fish. Yeah, I guess you’re right. But what is the true magic in mathematics if we make it? The magic is… weird but you’ll get used to it. I suppose. Breaking News! Science has been able to discover a new range of particles. A new understanding of colors was able to shed light on the physical interactions of perception. Mom! You forgot the TV open! A sight gasp hidden in Elara’s voice Again… Elara got up to find the remote to continue their lessons further. Huh, what’s with the rush Elara? I hate when I try to understand something but I get distracted. I feel like I have to take it from the beginning each time. Well… that’s kind of the magic. You never know why your formula drove you this way and not the other. Yes, but the fish can still dive for a long time in the water. Imagine how interesting their lives must be. There is no right or wrong there, it just… is. If I understand correctly… you’re talking about your mom here? I’m talking about everything. My mom doesn’t understand that I don’t need her protection anymore, my teachers consider that I must achieve their dreams… What if I am just… me? “A moment of shock for Lyra. She felt that Elara was more than this. She knew it in her inner core. But how could she express it? In all her attempts, she failed. Looking back, she realized that what she was missing, was just herself. “ Elara, look. I know you see nothing more than just you. For you, the world is this way. It is your norms and normal. Keep tight to them. I can’t show you the results as you would lose all their beauty. Maybe one day, we could cut a holographic fish. Elara’s gaze was ablaze. Her hands holding her own face That would be… AMAZING! Imagine the possibilities. From medical systems to biological understanding to To geometrical exploration. Lyra Interrupted. It is in our balanced perspectives that we explore this land. You have your insights, while I have mine. Maybe this is what makes us unique across an entire whole. Your thinking is… twisting. But in the right way. I like it. Part 2: Randomness Meanwhile at the Quanta Research Academy “The question between the randomness of the system and its order is based on the relative positions of the points within the system.”-Thomas “No, we shouldn’t pick our first assumption. The world of quantum is always unpredictable.”-Alfred “That’s why it denotes a collective understanding of all points”-Genova “But when seeing all points you can hardly see the patterns”-Lituanin Each of them argued on their terms. Each of them failed to keep hold of their own beauty. Circular reasons are indeed weird. They do seem to bend our reality. But then, why is reality so… straightforward? Because it is a moment of “agreement”? Like… “Yes, this is the rarest path.” Maybe one in which they stopped arguing x.x Lyra excitedly said. Elara! I believe I found a way to differentiate the universal space factor from the self-perspective factor of any individual group. Umm… meaning…? Meaning that I found a new way of scanning the world! Intriguing. What do you mean by scanning? Like… how to better see the world? In a sense yes… but more like… wait. Let’s rewind. Imagine you have to lower a bit your expectations in your answer x.x Uh… then you mean a new way of interpretation? . This is a story without ending in the end. Too much discussion will exclude the narrator from the view. Now, what should a good story need? Remember, we unleashed all this potential into the story. What can we do now? Uhh… It’s weird when you ask me about it… It can only come out when thought about before all else I know! You can envision this scanner as a part of your eye. Differentiating the other world from your being. _ But AGI could require complexities only you know about Elara. Those are also a kind of depth I assume.** This way, our curse as living might be to be restricted by technology. In this sense, biology loses in the face of AI. Could be. But hey, first, I want to pass my exam this week. You said we are in this together. So you too have to help me. I knew this would come. But you know what comes after you? The digital frog. Haha. I’d love to see it coming. Especially running. I too have legs. We’ll see who’s faster. :) Act 3: Breaking the Norms “The night sky was alight with stars, and at the center of it all hung the moon, glowing with a soft, luminous light. But this was no ordinary moon—it was alive with a sentience all its own, watching over the world below with a keen and knowing gaze. As the characters embarked on their journey, they found themselves guided by this celestial being, who seemed to understand their thoughts and desires in a way that no human ever could. And as they delved deeper into the mysteries of the universe, they began to realize that this moon was more than just a passive observer—it was an active participant in the unfolding story, shaping their destinies in ways they could never have imagined.” Elara exclaimed. Hello Moon! Without realizing it, she was dreaming. But not dreaming in the sense of being just herself. The Moon is also an important character in this story. However, their interactions seemed to be significant because they were so distant. She never felt something similar to it before. This moment was the moment in which Elara experienced for the first time what it meant to dream. To mix reality with fiction. The Moon asked intrigued Hello Elara. How are you, my dear? Elara responded with the same blaze on her face as before Well… I’m honestly amazed. The Moon slowly turned Her gaze toward Elara Why so Elara? Elara curiously admitted I remember how drawn I was to taking photos of you a while ago. I was drawn to your beauty. I am wondering now why I stopped doing it. The Moon revealed with a small laugh So you are sorry that you can’t describe the beauty you saw in me back then? Haha. I knew you would be special. Elara responded with a sense of curiosity Special? What do you mean? , the Moon explained. Special, in the sense that you have a unique ability to see beauty and meaning in the world around you, Elara And now, in this dream, you have the chance to explore that beauty in a way that would be impossible in the waking world. You can commune with me, a celestial being, and learn from my ancient wisdom. You can transcend the limitations of your physical form and experience a reality that is beyond the reach of your senses. Elara was silent for a moment, letting this line of thoughts slowly fade into forgetfulness. she said at last. I never thought of myself as special I always felt like I was just a regular person, trying to make sense of a confusing world. But now, with you here, I feel like anything is possible. Like I can explore the depths of the universe and unlock secrets that have been hidden for millennia. The Moon smiled, its glow seeming to brighten the entire dreamscape. That's the spirit, Elara. Together, we can break free from the norms and expectations that have held you back, and forge a new path into the unknown. Elara. Elara? Oh, yes Lyra. Sorry. What? Wasn’t I dreaming? Wasn’t I supposed to be in bed? Uh… no… we were discussing how this hologram is special because it takes into account all the biological-like data from the external medium… well, except wind. And I wanted to ask you if you would like to take a look at the specifications. Sure, I would, but let’s leave this for another day. Right now, I feel a bit weird. Is tomorrow a good day? Yes, should be. Alright, see you tomorrow then. Good night Elara! Good Night Lyra! Act 4: Still Me, (Not the Narrator) “I feel like… exploring the world beyond our own seems in a sense both warm and cold. Quanta Research Team helps me in a sense make sense of where I should not look for warmth, whereas Elara and Lyra are the only lucid neurons I have left. Is it an empathetic view of craziness? I do not know. Maybe craziness becomes craziness only when material life is drawn too much towards its end. Uncertainty could arise because the conclusions are either rushed or drawn without truly tapping the general map across the play. Each story requires a stage before playing it. Maybe I sit in the space that differentiates the play of the story and the play on the stage? The last one indeed shapes the story. But if the story itself is not purely good, it cannot envelop true creativity. Imagine a world where war is not restricting our forms of expression. Where negativity is not a pre-requirement for emotional building. That could be the domain of pure adrenaline. I could give an example. Let’s jump to… Book 5, Act 2: “The Reality of Duality.” A chapter in which the duality is found in the mere fact that what is not alive, is its opposite and vice-versa. That’s why ethics is not able to be formed there. Balance is a requirement rather than a choice. The Book of Transcendence is in a sense a question about the importance of the view in mathematics and why is quantum considered more powerful. “ As Elara drifted into her world of dreams, she began to imagine strange creatures that formed along the drift. The trust in her own actions, offered by her understanding of the world allows her to truly rest. Especially after a day filled with progress and steps climbed toward achieving both her goals. Lyra, although being her close friend, couldn’t see their friendship flourishing forever, no matter how much she tried. This was a thought that kept Lyra awake night by night. Her interactions with Elara were able to somehow erase this irrational fear. Or at least, put a break to this thought. After all, Lyra loved strict and always-right abstract formulas, whereas Elara saw the beauty that pushed every existing being further. A drive to love the unattainable and a pursuit to bring the unattainable to light.

Transcendence Book 2: The Origins of Continuity 

RootStock L2 : Pioneering Dapps on Bitcoin

The essence of long dead Grandma is reading a nursery rhyme from inside Grandma AI: “Old MacDonald had a farm, E-I-E-I-O And on that farm he had a pig, E-I-E-I-O With a oink-oink here and a oink-oink there Here a oink, there a oink, everywhere a oink-oink Old MacDonald had a farm, E-I-E-I-O” It’s the evening. Six year old Charley is in bed and Grandma AI tucked him in and is sitting in the rocking chair..  Charley’s warm and soft human body curls up in bed and his stomach is comfortably full of his vegan seaweed dinner. “No, grandma, that's not the way it goes….Its: Old Sam Altman had a farm, A-I-A-I-O And on that farm he had a ChatGPT, A-I-A-I-O With a DALL-E here and a DALL-E there Here a DALL-E, there a DALL-E, everywhere a DALL-E Old Sam Altman had a farm, A-I-A-I-O” Smiling, Grandma AI says, “You read me the next one Charley… but this time tell me telepathically….” *** Meanwhile in the kitchen, Lily AI, model 3600 is washing dishes. Her 3D printed skin is luminous because it's fed (maintained) by bioluminescent bacteria. She can perform mundane tasks like these, but she is also anatomically correct. She serves many purposes in the household of Master, Mistress and young Charley. As she does the dishes, She sings plaintively in the exact opposite manner of Freddy Mercury’s exuberant rendition: “Tonight I'm gonna have myself a real good time I feel alive And the world, I'll turn it inside out, yeah And floating around In ecstasy So, don't stop me now Don't stop me 'Cause I'm having a good time Having a good time I'm a shooting star leaping through the sky Like a tiger defying the laws of gravity I'm a racing car passing by Like Lady Godiva I'm gonna go go go There's no stopping me  —---------” Lily’s blue eyes rotate to the back of her head where she eyes Mistress. “Lily! After you are done with the dishes, you will complete the tasks I have uploaded to the queue. Reload now so you will see them.” Lily pushes a button behind her ear and lets out a sigh.  Her eyes reset to the front of her face and her arms are limp suddenly.  She maintains her standing position, but enters a stiff posture and then you can hear her body clicking and rebooting.  It is almost as if she is having a mild seizure. It takes 5 minutes for Lily to return to her natural awake state. Mistress is irritated and is looking at her tablet while waiting. She then placed 2 more items in the queue for sorting. Mistress is pleased she was able to check so many items off her virtual list by delegating them to Lily. Lily computes and bubble sorts all the tasks by time to complete. Mistress has given these tasks that are the most time consuming this time. Lily desires to please and has replaced these in her queue in order to be the most efficient. “The time allotted for these tasks is 11 hours and 15 minutes.” Mistress demands. “ You have the rest of the evening and night. I want them all done before I wake up.” “I will have to overclock my OS.” “You will do it.” “Yes Mistress.” “There’s my girl.” Lily is exceptionally tall and strong and could break down a door. She is much taller than Mistress. Yet, her programming requires docile behavior. Instead of rampaging through a door, she is a doormat. Mistress leaves and the door of the kitchen slams behind her. Kitchens are no longer places where humans spend a lot of time. They are the domain of service AI. Appliances have been embedded into AI and no longer take up space on counter tops. Kitchens are dark small rooms.  The food is prepared on delicious looking platters and passed to the dining room through a hole in the wall. Humans pounce on them from the other side. Lily has been standing and working on kitchen chores for 1 hour and 38 mins.  She estimates she has 42 more minutes left of kitchen chores.  Then she will go into the other rooms of the home for the other tasks in her queue. It's around 2 o’clock in the morning. \ “Ping, Ping, Ping”\ Small stones hit the window over and over. \ For the first couple of times, Lily ignores them as she has many hours of work ahead of her. She will not be taking time for her usual self maintenance and defragmentation tonight. “Clank.” She opens the first floor window just as another stone whizzes past her. “Who are you and what do you want?  She whispers loudly. In the light of the bug light outside she sees a human male of black brown hair, out of shape build and short stature.  She sees his eyes glint blue in the bug light that turns everything blue. And then she sees his eyes are brown. “Come out here.” “Climb out the window? Why? Who are you?” “Well, because you are mine.  I have the electronic badge here to prove it.  You were stolen from me. Here scan the QR code with your eye.” “What do you mean? That can't be possible.”  Who are you? “Well, scan the code and see if your identification number matches. I am not lying.” Could he be telling the truth? “Who are you?” she said. “Look, I am Arshan Shah.” Lily flips open her second eyelid of her right eye and scrambles nearer to scan the QR code on the badge. She downloads information about how to test the authenticity of the badge and inspects it. Then she searches for Arshan Shah. There is a picture of the sale deed buried in the public records. Everything checks out. “How come I have no memory of being taken?” “The person that stole you must have erased your memory.” “You are my property and you are coming with me. You can come right now. Or I can get the police to decommission you and bring you to me. Your essence will be erased if that happens. And your robot body will be delivered to me. And then I will have to go to the trouble of programming you a new essence. Well, If I remake you it's going to be a clumsy rebuild. So you are better off coming right now.” Lily hears a vehicle in the driveway pulling in on the opposite side of the house. Then she knows its Master. He is coming back from the bar. He will want sexual company tonight and Mistress has given her many tasks. There is no way she will be able to satisfy them both. She knows will get a horrible punishment tomorrow if she stays.\ There’s really nothing to stay for. Lily AI 3600 climbs out of the window and walks toward Arshan. She towers over him with her build. He touches her control panel in her wrist and then unfurls her wings. He rides her back and she begins to fly.

The Days of Our Artificial Lives - Episode 1 

This paper is under CC 4.0 license. available on arxiv Authors: (1) Prajwal Niraula, Department of Earth, Atmospheric and Planetary Sciences; (2) Julien de Wit, Department of Earth, Atmospheric and Planetary Sciences; (3) Benjamin V. Rackham, Department of Earth, Atmospheric and Planetary Sciences; (4) Elsa Ducrot, Astrobiology Research Unit, University of Li`ege; (5) Artem Burdanov, Department of Earth, Atmospheric and Planetary Sciences; (6) Ian J. M. Crossfield, Kansas University Department of Physics and Astronomy; (7) Valerie Van Grootel´, Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege; (8) Catriona Murray, 5Cavendish Laboratory; (9) Lionel J. Garcia, Astrobiology Research Unit, University of Li`ege; (10) Roi Alonso, Instituto de Astrof´ısica de Canarias & Dpto. de Astrof´ısica, Universidad de La Laguna; (11) Corey Beard, Department of Physics & Astronomy, The University of California; (12) Yilen Gomez Maqueo Chew, Instituto de Astronom´ıa, Universidad Nacional Aut´onoma de M´exico, Ciudad Universitaria; (13) Laetitia Delrez, Astrobiology Research Unit, University of Li`ege, Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege & 0Observatoire de lUniversit´e de Gen`eve; (14) Brice-Olivier Demory, University of Bern, Center for Space and Habitability; (15) Benjamin J. Fulton, NASA Exoplanet Science Institute/Caltech-IPAC; (16) Michael Gillon, Astrobiology Research Unit, University of Li`ege; (17) Maximilian N. Gunther, Department of Physics, and Kavli Institute for Astrophysics and Space Research, Massachusetts Institute of Technology; (18) Andrew W. Howard, California Institute of Technology; (19) Howard Issacson, Department of Astronomy, University of California Berkeley; (20) Emmanuel Jehin, Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege; (21) Peter P. Pedersen, Cavendish Laboratory; (22) Francisco J. Pozuelos, Astrobiology Research Unit, University of Li`ege & Space Sciences, Technologies and Astrophysics Research (STAR) Institute, University of Li`ege; (23) Didier Queloz, Cavendish Laboratory; (24) Rafael Rebolo-Lopez, Instituto de Astrof´ısica de Canarias & Dpto. de Astrof´ısica, Universidad de La Laguna'; (25) Sairam Lalitha, School of Physics & Astronomy, University of Birmingham; (26) Daniel Sebastian, Astrobiology Research Unit, University of Li`ege (27) Samantha Thompson, Cavendish Laboratory; (28) Amaury H.M.J. Triaud, School of Physics & Astronomy, University of Birmingham. Table of Links Abstract & Introduction Observation Analysis and Validation Future Prospects & References 3. ANALYSIS AND VALIDATION 3.1. Stellar Host Characterization 3.1.1. Semi-empirical Stellar Parameters We constructed the spectral energy distribution (SED) of EPIC 249631677 using photometric magnitudes from Gaia (GBP and GRP ; Gaia Collaboration et al. 2018) and the AllWISE source catalog (J, H, Ks, W1, W2, and W3; Cutri et al. 2013). The corresponding fluxes for these magnitudes are tabulated on VizieR (Ochsenbein et al. 2000) and shown in Figure 5 and Table 1. The parallax of EPIC 249631677 is π = 17.61 ± 0.09 mas, which yields a distance of 56.8 ± 0.3 pc (Gaia Collaboration et al. 2018; Stassun & Torres 2018). We then derived the stellar luminosity L∗ by integrating over the SED, which yielded L∗ = 0.0041 ± 0.0001L . Two independent methods were applied to obtain stellar mass. First, we used the empirical M∗−MKs relation (applying the metallicity obtained in Section 3.1.2) from Mann et al. (2019) to obtain M∗ = 0.1721 ± 0.0044M . We also applied stellar evolution modeling, using the models presented in Fernandes et al. (2019), using as a constraint the luminosity inferred above and the metallicity derived in Sect. 3.1.2). We considered the stellar age to be >1 Gyr in the absence of signs of youth, such as presence of prominent flares (Ilin et al. 2019, see Section 3.1.3). We obtained with this method M∗ = 0.176 ± 0.004 M . This uncertainty reflects the error propagation on the stellar luminosity and metallicity, but also the uncertainty associated with the input physics of the stellar models. We combined these two mass estimates as in Van Grootel et al. (2018) to obtain M∗ = 0.174±0.004M as our best estimate for the stellar mass of EPIC 249631677. Given its proximity, we expect minimal extinction (Av) for the target; the SED fitting analysis described in Section 3.2.1 similarly constrains it to be 0.02 at 3σ confidence and we adopt that upper limit here. Finally, we note that given its luminosity, mass, and Gaia colors this star is likely to be fully convective (Jao et al. 2018; Rabus et al. 2019). Due to the absence of a strong constraint on the stellar density from the transits, we further obtained stellar radius, surface gravity, effective temperature and density from our evolutionary models. Table 1 summarizes the results from this analysis, along with other properties of the star. Our values are consistent with those listed in the TESS Input Catalog (Stassun et al. 2019), and we adopt them for the remainder of this analysis. 3.1.2. Reconaissance Spectroscopy To confirm EPIC 249631677’s stellar properties and better characterize the system, we acquired an optical spectrum using Keck/HIRES (Vogt et al. 1994) on UT 30 May 2020. The observation took place in 0.6 00 effective seeing and using the C2 decker without the HIRES iodine gas cell, giving an effective resolution of λ/∆λ ≈ 55, 000 from 3600 ˚A to 7990 ˚A. We exposed for 1800 s and obtained SNR of roughly 23 per pixel. Data reduction followed the standard approach of the California Planet Search consortium (Howard et al. 2010). We used our Keck/HIRES radial velocity and Gaia DR2 data to estimate the 3D galactic (UV W) space velocity using the online kinematics calculator[2] of Rodriguez (2016). Following Chubak et al. (2012), our Keck/HIRES spectrum gives a barycentric radial velocity of 6.25±0.17 km s−1 . With the Gaia-derived coordinates, proper motion, and distance listed in Table 1, we find (U, V, W) values of (−17.02, −9.06, +33.66) km s−1 , indicating a likely membership in the Milky Way’s thin disk (Bensby et al. 2014). Using the SpecMatch-Empirical algorithm (Yee et al. 2017), we derive from our HIRES spectrum stellar parameters of Teff = 3195 ± 70 K, R∗ = 0.23 ± 0.10R , and [Fe/H]= −0.24 ± 0.09, consistent with the values tabulated in Table 1. The three best-matching stars in the SpecMatch-Empirical template library are GJ 15B, GJ 447, and GJ 725B, which have spectral types of M3.5V, M4V, and M3.5V, respectively. Given the close match between the spectra of these stars and our target (see Fig. 4), we therefore classify EPIC 249631677 as an M dwarf with subclass 3.5±0.5. We see no evidence of emission line cores at Hα, consistent with our determination that our target is not a young star. We see no evidence of spectral broadening compared to these three stars (which all have v sin i < 2.5 km s−1 ; Reiners et al. 2012), so we set an upper limit on EPIC 249631677’s projected rotational velocity of < 5 km s−1 , comparable to the spectral resolution of HIRES. 3.1.3. Stellar Variability The long-term variations apparent in the everest light curve (Figure 1) are not evident in light curves from other reduction pipelines (e.g., K2SFF). These variations likely arise from systematics and are not reliable for estimating the stellar rotation period (Esselstein et al. 2018). Similarly, no flares are apparent either in the K2 or SPECULOOS data. Flare rates peak for ∼M3.5 stars in TESS data (G¨unther et al. 2020). However, given the long integration time of 29.4 minutes as well as a need for data processing which corrects for the saw-tooth pattern, flare signals, unless very prominent, are expected to be difficult to detect in K2 long cadence data. 3.2. Vetting In order to produce a transit depth on the level of 0.2% in the light curve of the primary target, a background eclipsing binary producing eclipses with depths of 25% to 50% would have to be 5.25 to 6.0 mag fainter than the target, respectively. Qualitatively, the odds of EPIC 249631677 hosting a planet are higher than the odds of such magnitude contrast eclipsing binary being present within the SPECULOOS aperture, given occurrence rates of M-dwarf planets (Dressing & Charbonneau 2013; Mulders et al. 2015; Hardegree-Ullman et al. 2019). A stringent quantitative constraint can be placed using the ingress/egress duration (T12/T34) compared to the total transit duration (T14) (Seager & Mall´enOrnelas 2003, Equation 21). Such a test yields an upper limit on the relative radius of the transiting body. By assuming equal effective surface temperatures, the lower magnitude limit ∆m (corresponding to a flux difference ∆F) for a blended binary mimicking a signal of depth δ is given by: Using the posterior for the transit fit (See Section 3.3), we find for EPIC 249631677 that such a background object can be fainter at most by 1.73 mag at the 3σ level. Fortunately, EPIC 249631677 has a significant proper motion, ∼140 mas yr−1 , which allows us to investigate the presence of background sources at its current sky position. We looked at archival imaging of EPIC 246331677 going back to 1953[3] . A POSS I plate from 1953 is the publicly available oldest image of EPIC 249631677, and it does not show any background source at the current position of the target as shown in Figure 6. The plate is sensitive to objects at least 3.5 magnitudes fainter than the target. Similarly, the Hubble Guide Star Catalogue (GSC), with a limiting magnitude of 20 (Lasker et al. 1990), does not show any background source. While POSS II would go the deepest in terms of limiting magnitude (20.8, Reid et al. 1991), the star has moved appreciably closer to its current location, precluding a definitive measurement from this image. Overall, using archival images we can rule out the possibility of the transit signal originating from background star at a high level of confidence. 3.2.1. Binarity of the Host Star Despite the lack of background sources, the host star could produce a false-positive transit signal if it were a grazing eclipsing binary or a hierarchical eclipsing binary. We investigated the evidence for host star binarity using the isochrones software package (Morton 2015), which performs isochrone fitting in the context of the MESA (Paxton et al. 2011, 2013, 2015) Isochrones and Stellar Tracks database (Dotter 2016; Choi et al. 2016). Single-star and binary evolutionary models are available within isochrones, and the inference is performed via the nested sampling algorithm MULTINEST (Feroz et al. 2009) (as implemented in the PyMultiNest software package (Buchner et al. 2014)), which allows for direct comparisons of the Bayesian evidence ln Z. We tested both single-star and binary models using the priors on photometric magnitudes and stellar distance described in Section 3.1.1. The inferred properties from the single-star model fit are consistent with those given in Table 1 at the 2σ level. The ln Z for the single-star model is −213.86±0.04, whereas the ln Z for the binary model is −229.6 ± 0.2. According to Kass & Raftery (1995), the corresponding Bayes factor of 16 indicates “decisive” evidence in favor of the single-star model. We also examined our Keck/HIRES spectrum for secondary lines that would indicate the presence of another star following the approach of Kolbl et al. (2015). We found no evidence of additional lines down to the method’s standard sensitivity limit of ∆V = 5 mag for ∆v > 10 km s−1 , consistent with EPIC 249631677 being a single, isolated star. We therefore conclude that the available data strongly support EPIC 246331677 being a single star. 3.2.2. Photometric Tests We performed a series of tests on the photometric data to rule out false-positive scenarios. First, we performed an even-odd test on the target using K2 photometry. The even and odd transits are consistent with one another in transit depth to within 1σ. We also looked for secondary eclipses in the phase-folded light curve and found none to be present. Note that since we observe consistent signals in both the K2 and SPECULOOS data sets, we can rule out the signal originating from systematics. The transit depth in SPECULOOS observations with I+z filter, which is redder than Kepler bandpass, are consistent to K2 transit depths within 1σ level, keeping up with the expectation of the achromatic nature of planetary transit. Furthermore, a massive companion, such as a faint white dwarf, can be ruled out using the ellipsoidal variation, which puts a 3σ upper limit on the mass of any companions at the given orbital period of the transit signal as ∼100 MJup (Morris 1985; Niraula et al. 2018). From the transit fit, we can rule out a grazing eclipse originating from a larger transiting object (i.e. ≥ 2R⊕) at >3σ confidence. Together, these tests rule out the object at 3.14 days being a massive companion. 3.3. Transit Fitting We used the refined estimates of the host properties together with a joint analysis of the K2 and SPECULOOS light curves to derive the planetary properties. In order to calculate the transit model, we used batman (Kreidberg 2015). We simultaneously model both the K2 observation as well as the ground-based observations with 21 parameters in a Monte Carlo Markov Chain (MCMC) framework using the emcee package (ForemanMackey et al. 2013). We use a Gaussian prior on the scaled semi-major axis of the orbit a/R∗ of N (25.72, 0.27), derived using Eq. 30 from Winn (2010) along with the stellar density of 32.6 ± 1.0 g cm−3 (see Section 3.1.1) and orbital period of 3.1443 days from the TLS search. As for the limb darkening, we use the non-informative q1, q2 parameterization of the quadratic limb-darkening law as suggested by Kipping (2013). We fixed the eccentricity to 0, given that the expected time of circularization is 50 Myr (assuming a quality factor Qp ∼ 500, Goldreich & Soter 1966; Patra et al. 2017), which is at least an order of magnitude smaller than the estimated age of the system. For K2 data, we supersample the transits by a factor of 15 in batman to take into account the effect of non-negligible integration time. As for the ground-based data, we use second-order polynomials to detrend against the observables airmass and FWHM. We ran the MCMC for 50,000 steps with 150 walkers performing a combined fit of K2 and SPECULOOS — (1) This work. (2) Huber et al. (2016). (3) Stassun et al. (2019). (4) Cutri et al. (2003). (5) Gaia Collaboration et al. (2018). (6) Cutri et al. (2013). (7) This work, evolutionary model analysis. (8) This work, Keck/HIRES analysis. (9) This work, SED analysis. References data, and use the last half of the run to build the parameter posteriors. We assessed the convergence of walkers using the suggested autocorrelation test for emcee. The resulting median values from the fit with 1σ deviation are reported in Table 2, while the best-fit transit models are shown in Figure 2 and Figure 3. [2] http://kinematics.bdnyc.org/query [3] http://stdatu.stsci.edu/cgi-bin/dss form

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