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Which of the following topics are you most excited by? OLED TV Technology and its evolution into QD-OLED and MLA WOLED from Samsung, LG, and Sony Why does it excite you? It's fascinating to me because display has been one of the hottest topics for the last 10yrs with Samsung Display and LG Display (The two-panel technology divisions of their respective parent companies) trying to out-innovate each other since what seems like the dawn of time. Things have certainly heated up in the last 2yrs with QD-OLED ( ) & MLA or META (but for the sake of clarity, we'll stick with MLA for now) WOLED ( ), Each offering their take on what they believe to be the best performing OLED display technology on the market. OLED Samsung Display LG Display What are the trends in this area or products in this area that you are the fondest of? Why? QD-OLED AND The newest OLED display technologies collided for the first time this year, so what makes them unique? MLA WOLED Quantifying QD-OLED QD OLED, which marked Samsung's long-awaited debut into the OLED market in 2022, takes the W or white color filter out of WOLED and instead uses Samsung's Quantum Dot or QD technology to increase the panel's brightness while removing the white filter that can wash out colors on display. The results are a screen that gives you the perfect blacks and contrasts from WOLED while vastly increasing the brightness and increasing color vibrancy from the white filter. QD-OLED becomes excellent for gaming and cinema on the big screen in your living room and is reliable enough to use as a monitor for your workstations due to the increased brightness and improved color accuracy for content creators. This year, Samsung launched its 2023 QD-OLED model, , and its performance left many pundits amazed. I should note that Sony's flagship TV, the A95L, which uses Samsung's QD-OLED panels, has yet to be released at the time of writing. But from early previews of Sony's highly anticipated flagship display, it has a great chance to outperform the S95C. the S95C So what does this mean for LG, who for close to 10 years were the kings of OLED? Well, they stated that they wouldn't be investing in the QD-OLED market and decided to continue development into WOLED. Enter MLA MLA WOLED, known as Micro Lens Array, is LG's answer to QD-OLED, which essentially doubles down on the (W)hite in WOLED. The increase in brightness is achieved by taking a panel with billions of microscopic lenses and placing them over a standard WOLED panel. The lenses help redirect any lost light back towards the screen, allowing the display to increase the white light and brightness overall. The result gives you an increasingly brighter picture of traditional WOLED, but what about the difference in color compared to QD-OLED? This year was LG's first use of MLA display on their flagship model, , and well, MLA is the real deal. A comparison of the G3 to Samsung's S95C showed the G3 can achieve a higher brightness level. Even though we talked about how the increased white can wash out colors, the G3 stays very competitive with regard to color against the S95C. LG says they're going all in on MLA technology, so it'll be a QD-OLED vs. MLA WOLED battle for the foreseeable future. the G3 Ultimately, when it comes to which one is better, I think it's too early to tell. One year MLA may be the best option, while the next, it could be QD-OLED. The displays are so close in performance that it will come down to individual use cases for prospective buyers and looking at which strengths would benefit them more. What matters is we as consumers are getting high-end competition that pushes technology to bounds not thought conceivable. What are the negative impacts they can have on consumers? The most concerning downside of OLED technology, including QD-OLED and MLA, is the risk of burn-in. is simply put when a static image is left on display for an extended period, which causes the screen to display an almost watermark-looking image. Situations where this would come up are if you left your TV on for hundreds of hours on CNN or used your OLED TV as a monitor. Now, I want to mention that burn-in risk has been significantly reduced and is getting better with each concurrent generation of display, but technically the risk is still there. Burn-in What are your predictions on how these technologies will evolve? LG, Samsung, Sony, have done so much with advancing where OLED brightness and color can go and my predictions on how the technology will evolve are hopefully to continue the reduction of burn-in along with pushing the boundaries of what brightness on OLED while preventing loss in color accuracy can look like. That said, it seems like the next improvement for OLED is not far off, and it comes in the form of , but I'll leave that for later. phosphorescent blue Do you have any more thoughts on this topic? I really just want to emphasize that these displays are so competitive and impressive that I genuinely believe there is NO clear-cut winner or loser between QD-OLED and MLA WOLED at this time. It's an exciting time to be in the A/V space, and if you're currently or will be in the market to buy a new OLED TV or monitor, it's hard to say there's a wrong choice.

QD-OLED vs. MLA OLED: Samsung, Sony, and LG Battle for the Future of Screens

has raised $441k+ from 366 investors in a week. We’re at 41% of our goal with 53 days remaining. . The Hacker Noon equity crowdfunding campaign Support the future of independent tech media by owning shares in Hacker Noon Big thanks to these kind words from some of our recent investors: , , , , , , , , , , ‏ , , , , , , and more. Alexis Ohanian Nele Maria Palipea , Felipe Rueda Kiba Gateaux Ryan Who Codes Brother Doyle Tom Terado Mark Roudebush Nick Soman Kevin Natanzon Robin Banks Mark Nadal Aaron Silverman Ross Campbell Olga Krieger Andras Caron Ugolino Here’s my Monday tech thought: I think it starts with simply listening, learning and (when the time is right) asking. We do it consistently in our contributor groups, but we also for the first time, did it systematically with a reader survey. The by . This survey impacted our internal decision making. For example, 71% of people surveyed said they wanted a podcast, so and made the . Additionally, we learned that 57% of readers wanted to attend Hacker Noon events. While that may not be much more than half, we think going from reading a story on a site to wanting to go to an event by that site, is quite a leap. Since the majority want it, look out for Hacker Noon events in 2019 :-) how can a startup better serve its community? results are published today Linh Dao Smooke we bought Crypto Disrupted Hacker Noon podcast with Trent Lapinski But serving your community is about more than surveys and analyzing data. In buidling a large community (Hacker Noon has 200k+ daily readers ), I wanted to pass on some simple things anyone can do to better their own startup community: Minimize response time. This is tough to do with a small staff and we fail at it too often, but just like responding to a text from a friend in need, a quick response time can scale relationships. Trust your community’s feedback. The majority of ideas for were first thought up by Hacker Noon contributors and not by me. I just pushed them forward. Hacker Noon 2.0 Be transparent when you and how you need to adapt. Every young business will face a time where they must evolve or die. Our primary source of revenue was threatened, so we evolved. We made a plan, and are of making that plan financially possible. almost to the half way point Onto the top 24 tech stories to kickoff your week: Software Emotions by [10 min read]. A Love Letter to the Commodore 64 Christer Enfors “Dad, if you don’t stop talking about things from the 1900’s, people are going to think YOU are from the 1900's!” It’s been nine years since my daugter said the above to me at six years old, and I’ve nearly forgiven her by now. I still love her, but this story isn’t about her. No, this story is about my first love, the Commodore 64 — a home computer from the 80’s, which is still the best selling computer of all time. More PC’s have been sold since, of course, but no single model of any computer has sold as many units as the Commodore 64 did back in the day. by [10 min read]. Why Angular Made Me Quit Web Dev Tobias Merkle One of the most reliable ways to discern whether a corporation has begun to rot is to gauge the derivative of the utility its products provide over time. A company like Apple witnessed a huge spike in average product utility when they released the iPhone, which increased for some time, but eventually plateaued when they started removing vital phone functions like the 3.5mm jack. Generally speaking, most companies experience either an S-curve or a parabolic curve of this kind of utility: the former types generally find their niche, fill it, and operate in comfortable profit without innovating much more; the latter types manage to muck things up and crash and burn having failed to understand their product. Deep Tech Thoughts by [11 min read]. Elon Musk wants to give you super human cognitive powers Harbind Kharod Elon says we‘re already cyborgs. The modern day human is able to answer almost any question you ask it within a matter of seconds. That futuristic device we all carry around connects us to an infinite pool of human knowledge. If someone makes a discovery, it can be shared with the human race within seconds on the internet. Combined with our devices holding access to this unlimited knowledge pool we‘re basically a giant inter-connected cybernetic organism composed of humans and machines. by . Windows as a Service? Terry Crowley The recent issues with the quality of Windows releases has reopened discussions of what it means to deliver “Windows as a Service”. When Windows 10 was released, Microsoft made a big deal that this was “the last version of Windows”. From now on, Windows would be delivered as a series of continuous ongoing incremental feature releases rather than as a big bang release every 3 years or so. by [16 min read]. To Become a Space Faring Civilization, We need to Move Beyond Rockets, including SpaceX and Blue Origin Riz Virk While SpaceX and BlueOrigin and others are making progress on re-usable rockets, this doesn’t change the fact that they are still basically relying on the same tech developed in the 1950s and 1960s by NASA and the Soviet Union. 50 years later, you would think we had built some alternatives, but we are basically relying on the same old technology — rocket engines. Rockets in general (whether using liquid or solid fuel), based on the work of pioneers like Robert Goddard and Werner von Braun (who brought over his expertise from Nazi Germany) have on average a few percentage payload to total weight (i.e. the payload being the weight of the capsule and/or what they are carrying in proportion to the total weight or volume of the rocket). The Saturn V had a 4% ratio, and the space shuttles were 1%. These are because of the vast amount of fuel needed by that outdated technology, combustible rocket engines. By far, the most difficult part of becoming an interplanetary species is getting off the Earth and into orbit en masse, what we might call the “first mile” problem. Blockchain Think Pieces by [7 min read]. Why Blockchain Immutability Matters Kevin Doubleday We spend Trillions of dollars on cybersecurity solutions meant to keep outside prying eyes from accessing our sensitive data. But rarely do we fight the internal cybersecurity battle: ensuring that our data has not been manipulated, replaced, or falsified by a company or its employees. In many cases, we have come to simply trust that the data is correct by methods like private keys and user permissions. But in reality, we cannot prove — methodically or mathematically — that information in a standard application database is unequivocally tamper-free. Auditing becomes our next (and expensive) line of defense. by [10 min read]. Proof-of-Work and Proof-of-Stake are Regressive Amber Cazzell The recent low in cryptocurrency morale has given our community a rich opportunity for reflection. The vast majority of us crypto enthusiasts have a genuine heart for marrying technology and social action, and I believe it’s time we reflect on where we wanted to go with digital currencies, honestly take stock of the state of blockchain technology today, and rigorously plan how to improve digital currencies moving forward. I’ve been fortunate enough to sit in on many lectures discussing blockchain technologies and incentive structures in computer science at Stanford University, and it’s led me to the conclusion that crypto incentives have driven a lust for global consensus which obscures the important goals we originally had in mind. by [4 min read]. Stablecoins: What you need to know Jimmy Song Stablecoins are a dollar-denominated cryptocurrency. The supposed benefits are that you get the convenience of cryptocurrency (fast settlement, less regulatory hurdles, etc) with the stability of the dollar (or another fiat currency). This makes arbitraging between exchanges more convenient, for example, allowing for a more stable BTC price between exchanges. Generally, 1 token of the stablecoin (SteemIt Dollars, Basis, Tether, etc) is supposed to be worth $1. The rate fluctuates in the market as Tether’s traded as low as $0.85, but that’s supposed to be the exception, not the norm. Some are supposed to be able to be converted to USD directly like Tether. Others have mechanisms to change the value towards $1 should the token price go up or down like Basis. Entrepreneurial Stories by [9 min read]. How I Made $15,000 / Day as a Fresh College Grad Daniel Sangyoon Kim Due to hazy regulations regarding cross-border cryptocurrency trades, my Korean colleagues convinced me to pause. Looking back, I think that was a huge mistake. This massive arbitrage opportunity existed for several months, and we could have made enough to sip coconut juice on a Hawaiian beach for the rest of our lives. While we played it safe, somebody out there figured out how to do it in scale, and the gap has since closed. by [5 min read]. How to Buy 20 Dollar Prescription Glasses from China Mark Peter Having lived in Asia for a while and seeing glasses in various prescriptions being sold on night markets for just a few dollars, paying hundreds and hundreds of dollars in western countries just seems ridiculous now — especially considering that glasses are just a piece of plastic, metal, and glass. I can buy a decent hi-tech smartphone these days for as little as 100 dollars or less. In comparison, it’s just crazy to spend, say, 200–400 dollars on a low-tech piece of plastic with lenses created by a machine. Warby Parker and others have paved the way for buying glasses online. So why not go a step further and pass on the savings to the consumer as well?! 💸 Crypto BUIDLing News by [5 min read]. Introducing a New Standard for Digital Stock Certificates: ERC-1450 Howard Marks StartEngine is the developer of ERC-1450 and is using it to issue tens of thousands of tokenized securities sold initially on StartEngine. If and when StartEngine’s broker-dealer becomes registered with the SEC and its ATS, called Secondary, is available, it will use ERC-1450 for transacting securities as well. StartEngine is in discussions with other registered transfer agents and ATS operators to also support this standard. Editor’s Note: If you buy Hacker Noon shares, it comes with a digital stock certificate. by . How to Build a Crowdsourced Bitcoin Price Prediction Algorithm Marc Howard What best predicts whether the price of Bitcoin will go up or down? What if there was an algorithm that could predict this at least a day in advance? This is what we’re building at the AlgoHive project and will be sharing how step-by-step. Just a quick refresher this project began with my initial post on how I created a Bitcoin prediction algorithm that produces a 29% positive return . This kicked off quite a few conversations on how best to improve and create a more robust algorithm. We now have a thriving community with investors, machine learning experts, data scientists and even beginners just wanting to follow along and learn more. The first project we’re working on is how build a Bitcoin prediction algorithm that gives a Buy/Sell signal for a given date with the intention to maximize profits. Productivity by [8 min read]. 30 Chrome Extensions, Apps, and Hacks to 2x Your Productivity Brian Tan Over the past three years, I’ve tried and tested hundreds of apps, Chrome extensions, and productivity hacks to make myself become more effective and efficient. I found most of these through podcasts or reading other productivity-tools lists, but I wanted to write a single list that listed all the ones I love and use. This article is the product of that, and this should be the best list of productivity tools and hacks currently on the web. Coin Histories by Marcell Nimfuehr [12 min read] The Amazing Story of Cryptocurrencies Before Bitcoin . David Chaum is a 28-year-old Ph.D. student in computer science from the University of Berkeley, California when he publishes a scientific paper in 1983. He is the first to describe digital money. Chaum comes from a wealthy US-American family, is a brilliant mathematician and is appointed head of the cryptographic department of the Mathematical Institute in Amsterdam. In his paper, he describes the key point that his digital money differs from credit card payments through anonymity . Users receive the digital currency from their bank, but then it is made anonymous. This allows the bank to see who has exchanged how much money, but not what it is used for. [7 min read] Charlie Shrem: a Bitcoin Story From Riches-to-Rags . The Winklevoss Twins are subject to ridicule more than once. 15 years ago, they were outsmarted by Mark Zuckerberg who allegedly stole their idea of a social network. Just last week they announced that Charlie Shrem embezzled US$32 Million by taking their Dollars and not giving them Bitcoin back in 2012 (Took a long time to go public with that). Time to recall who Charlie Shrem is and which pivotal role he played in the history of Bitcoin. “ In prison”, said Shrem, “the more of a celebrity you are, the less respect you get. You’re judged on who you are as a person, and I like being judged like that because I feel like I’m a I’m a pretty okay person. People liked me and I was judged on that, not on the Bitcoin stuff.” Software Trends by [4 min read]. Common Misconceptions of C++ Buckaroo - C/C++ Package Manager C++ has evolved massively in recent years and yet it is still perceived by many as the language that it was back in the early 2000s. Let’s dispel some myths…”C++ is a Dying Language…” C++ is actually growing! Even as computers becomes faster, our demands of what we want to do with them are always increasing. C++ is one of the few languages that allows us to maximize the potential of our hardware. by [15 min read]. CNN based Object Detection — Current Challenges Alex Punnen I am not a researcher but have been basically using open source algorithms and frameworks for Object detection for about two years now. Started from the ML-based HOG and HAAR in OpenCV, then the faster version of that via CUDA and GPU and finally since tuning the parameters of these systems to works across different videos was proving to be futile, went ahead with the neural network based method; I wanted to write this as there is a tendency by many who have used the open source implementations like Yolo, to think that it is a done done; also heavy marketing by a lot of small and specialised companies, who follow similar thinking, and promising visual automation, either customisable or customised for some vertical. Software How-Tos by [6 min read]. A crash course on writing a better README Adnan Rahić I started looking into projects with large amounts of contributions. It got me thinking. A common pattern started appearing. They all have amazing _readme.md_ files. I doubt it would have been easy to contribute otherwise. There may be a connection. I’d sure say there is! Let’s mention a few famous projects like React , Vue , freeCodeCamp , Sourcerer or Serverless. You can see their _readme.md_ ’s are a perfect blend of documentation, project overview, FAQ, and contribution steps. They mention the ecosystem, the community, and have visuals explaining the open source project itself. Because the open-source community runs the project, it needs a central file to make communication easy. by [5 min read]. Azure Functions: Choosing between queues and event hubs Jeff Hollan I have this conversation about twice a week. Someone has decided they want to take advantage of the benefits of serverless Azure Functions for an upcoming project, but when starting to lay out the architecture a question pops up: “Should we be using Azure Event Hubs, Queues, or Event Grid?” It’s honestly a great question — and it’s a question with consequences. Each of these messaging technologies comes with its own set of behaviors that can impact your solution. by [5 min read]. Complete Guide: Receive Push Notifications in React-Native iOS app Oleg Kalyta Adding push notifications to your app is not only a great way to improve the user experience. If used smart, it also helps to: (1) Stimulate user engagement, (2) Retain users, (3) Increase conversion rates. Recently our team implemented push-notifications for React-Native iOS app. We spent a couple days to get this fully working for most common scenarios. The goal of this article is to save this time for you. by [4 min read]. How to Compile Node.js Code Using Bytenode? Osama Abbas In this post, I will show you how to “truly” compile Node.js (JavaScript) code to V8 Bytecode. This allows you to hide or protect your source code in a better way than obfuscation or other not-very-efficient tricks (like encrypting your code using a secret key, which will be embedded in your app binaries, that’s why I said “truly” above). So, using _bytenode_ tool, you can distribute a binary version _.jsc_ of your JavaScript files. You can also bundle all your _.js_ files using Browserify, then compile that single file into _.jsc_ . by [9 min read]. How to fix your Java learning: a story of one tutor John Selawsky Common mistakes and how to struggle them: 1. Too much theory from the first steps. So, you started to learn a programming language. What should you do first? Read a lot then write a program? Not at all, buddies. Read a bit and then code, code and again code! Recall your kindergarten or primary school. Drawing class… Did you listen or read a lecture then how to draw? I am pretty sure the answer is “no”. You and other kids just took your crayons and… drew. At most your teacher could show you how to hold a pencil or tell something about “red and blue is violet”. Or you took part in stage playing Cucumber or Broccoli… I don’t think your drama teacher explained you Stanislavsky system that time…The same story with programming. JUST.START. CODING. Theory is important. But later. Tech Careers by [7 min read]. Want a mentor? Stop asking for one. Bethany Crystal There’s something culturally “off” about the way we talk about mentorship. In some fantasy-land world in your head, you may be imagining an ideal role model — someone loved and respected who has already saved the world twice over, has all of the experience you want one day, and by the way, happens to be free on Thursdays at 10 a.m. for the next six months to meet for coffee and tell you all the secrets of their ways of life. This person will take a liking to you immediately without knowing why (sort of like Albus Dumbledore and Harry Potter), and your instant charm will somehow compel them to give up some percent of their time just to make you better. by [7 min read]. Maximizing Your Next Salary Yotam Kadishay You passed all interviews and tests for a cool company — Congrats! The recruiter just gave you a call saying they were very impressed with you and want to offer you a contract, then she will ask you the biggest question of all — a big question with no single true answer — “What are your salary expectations?”. Hopefully, this story will help you answer this question in the best way possible, and maximize the salary in the next contract you sign. Until next time, don’t take the realities of the world for granted. Kind Regards, David Smooke Thanks again to the kind words from some of our recent investors: , , , , , , , , , , , ‏ , , , , , , and more. P.S. Alexis Ohanian Nele Maria Palipea Felipe Rueda Kiba Gateaux Ryan Who Codes Brother Doyle Tom Terado Mark Roudebush Nick Soman Kevin Natanzon Robin Banks Mark Nadal Aaron Silverman Ross Campbell Olga Krieger Andras Caron Ugolino Own Hacker Noon shares today.

24 TOP TECH STORIES TO START YOUR WEEK

You can jump to any section of y The National Cislunar Science & Technology Strateg here. The U.S. S&T approach to Cislunar space The decade ahead is critically important for exploration of Cislunar space, including the Lunar surface. The U.S. government, other countries, and private entities are all planning to send spacecraft into and through Cislunar space in the coming years. NASA estimates that over the next ten years human activity in Cislunar space will be equal to or exceed all that has occurred in this region since the Space Age began in 1957. The growth of current and planned activities in Cislunar space is driven by decreasing launch costs, advanced and increasingly commodified space technologies, growing commercial interest in space activities, new missions by national space programs that are motivated by national and geopolitical ambitions, and the utility of Cislunar activities as a programmatic step toward some future missions into the solar system. These trends have opened Cislunar space as a new domain of diverse human activities, and spacefaring actors will begin to set important new precedents across the next decade. Leadership by the United States and its international partners will support the responsible, peaceful, and sustainable exploration and use of Cislunar space, including the Moon. Fostering scientific discovery, economic development, and international cooperation are essential to sustaining this leadership. With this framework, the Cislunar S&T Strategy provides four objectives for the early years of Cislunar growth: (1) Support research and development (R&D) to enable long-term growth in Cislunar space. (2) Expand international S&T cooperation in Cislunar space. (3) Extend U.S. space situational awareness capabilities into Cislunar space. (4) Implement Cislunar communications and PNT capabilities with scalable and interoperable approaches. All four S&T objectives support the U.S. vision of responsible, peaceful, and sustainable exploration and use of Cislunar space, including the Moon. Visionary R&D can foster world-leading scientific discovery; new approaches created in R&D enable responsible and sustainable space activities, enable economic development, and promote peaceful uses of space to the benefit of all. International S&T cooperation can foster peace, develop responsible practices, and create collaborations to enable enduring human presence in Cislunar space, including at the Moon. Extending space situational awareness (SSA) into Cislunar space creates a necessary foundation to promote and sustain responsible spaceflight practices, and enables transparency to promote peaceful and cooperative uses of Cislunar space. Finally, implementing needed Cislunar communications and PNT capabilities with scalable and interoperable approaches, analogous to development of early internet technologies, can foster commercial development necessary for sustainable activities, build early technology ecosystems based on cooperation around shared values, and advance responsible and safe spaceflight practices. These objectives build on enduring strengths of the United States, including a global network of allies and international partners, the ability to draw the world’s best talent and recombine it with the benefits of diversity, world-leading universities and higher education, private sector innovation ecosystems built on competition and self-correction, the rule of law and open science, and a culture of new beginnings. This content was initially published on in November 2022. whitehouse.gov This content has been broken-up into bite sized sections, each with unique headlines and AI-generated lead images, in line with the provisions of Creative Commons 3.0.

The U.S. Outlines Scientific and Technological Vision for Cislunar Frontier

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 4. FUTURE PROSPECTS The search for transiting planets around small stars has been motivated in large part by their potential for atmospheric characterization. Owing to the size and proximity of its host, K2-315b is thus one of the few known terrestrial exoplanets possibly amenable for atmospheric characterization in the next two decades. In order to quantify and contextualize its prospects for atmospheric study, we followed the same approach as for TRAPPIST-1 in Gillon et al. (2016) (see de Wit & Seager 2013), focusing here on all known terrestrial planets. We selected terrestrial planets as planets with a reported radius below 1.6 R⊕ in the NASA Exoplanet Archive[4] (Rogers 2015; Fulton et al. 2017). We thus derive the amplitude of the planets’ signals in transmission as: where Rp is the planetary radius, R∗ is the stellar radius, and heff is the effective atmospheric height, µ is the atmospheric mean molecular mass, T is the atmospheric temperature and g is the local gravity. We assume heff to cover seven atmospheric scale heights, µ the atmospheric mean molecular mass to be 20 amu, and the atmospheric temperature to be the equilibrium temperature for a Bond albedo of 0. For the planets with missing masses, we estimated g using the model of Chen & Kipping (2017). The signal amplitudes are reported in Figure 7 together with the SNR relative to TRAPPIST-1 b’s, calculated by scaling the signal amplitude with the hosts’ brightness in J band. We find that K2-315b fares closely to the outer planets of TRAPPIST-1 in terms of potential for atmospheric exploration with JWST— its warmer and thus larger atmosphere compensating for its larger star. In fact, its relative SNR for transmission spectroscopy is half those of TRAPPIST-1 f–h, meaning that assessing the presence of a µ ∼ 20 atmosphere around the planet would require of the order of 40 transits—four times the ∼10 transits required for a similar assessment for TRAPPIST-1 f–h (Lustig-Yaeger et al. 2019). K2-315b is thus at the very edge of JWST’s capability for atmospheric characterization, mostly due to its “large” host star. The derivation above allows us to rank planets in terms of relative potential for atmospheric characterization, assuming a similar atmospheric scenario. In practice, a significant difference in atmospheric mean molecular mass, surface pressure, and/or cloud/haze altitude will strongly affect the actual potential of a planet for characterization (Lustig-Yaeger et al. 2019). For example, in some cases clouds could render the characterization of the favorable TRAPPIST-1 e difficult even with the generation of instruments following the JWST (i.e., LUVOIR, Pidhorodetska et al. 2020). With an estimated radial velocity semi-amplitude of 1.3 m s−1 (assuming a mass comparable to that of Earth), the planet could be accessible for mass measurements using modern ultra-precise radial velocity instruments. Such possibilities and a ranking amongst the 10 best-suited Earth-sized planets for atmospheric study, EPIC 249631677 b will therefore play an important role in the upcoming era of comparative exoplanetology for terrestrial worlds. It will surely be a prime target for the generation of observatories to follow JWST and bring the field fully into this new era. This project makes use of publicly available K2 data. P.N. would like to acknowledge funding for Kerr Fellowship and Elliot Fellowship at MIT. J.d.W. and MIT gratefully acknowledge financial support from the Heising-Simons Foundation, Dr. and Mrs. Colin Masson and Dr. Peter A. Gilman for Artemis, the first telescope of the SPECULOOS network situated in Tenerife, Spain. B.V.R. thanks the Heising-Simons Foundation for support. V.V.G. is a F.R.S.-FNRS Research Associate. M.G. and E.J. are F.R.S.-FNRS Senior Research Associates. This work was also partially supported by a grant from the Simons Foundation (PI Queloz, grant number 327127), and funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013) ERC Grant Agreement Number 336480, from the ARC grant for Concerted Research Actions financed by the Wallonia-Brussels Federation, from the Balzan Prize Foundation, from F.R.S-FNRS (Research Project ID T010920F), from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (grant agreement n◦ 803193/BEBOP), and from a Leverhulme Trust Research Project Grant n◦ RPG-2018-418. 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π Earth: a 3.14-day Earth-sized Planet from K2's Kitchen Served Warm: Future Prospects & References

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

π Earth: a 3.14-day Earth-sized Planet from K2's Kitchen Served Warm: Analysis and Validation

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 2. OBSERVATIONS 2.1. A Candidate in Archival K2 Data EPIC 249631677 was observed by K2 in Campaign 15 from 2017-08-23 22:18:11 UTC to 2017-11-19 22:58:27 UTC continuously for about 90 days as part of program GO 15005 (PI: I. Crossfield). The pointing was maintained by using two functioning reaction wheels, while the telescope drifted slowly in the third axis due to radiation pressure from the Sun, which was corrected periodically by thruster firing (Howell et al. 2014). As a consequence of such a modus operandi, uncorrected K2 light curves can show saw-tooth structures. Many pipelines have been built to correct for such systematics. Two popular detrending algorithms for K2 light curves are K2SFF (Vanderburg & Johnson 2014) and everest (Luger et al. 2016). These pipelines have helped to achieve precision comparable to that of Kepler by correcting for systematics caused by intrapixel and inter-pixel variations. In the case of EPIC 249631677b, the standard deviation of the flattened light curve for K2SFF was observed to be 1230 ppm, compared to 685 ppm for everest. Considering this, we use the light curve from the everest pipeline, available from the Mikulski Archive for Space Telescopes, throughout this analysis. We use a biweight filter with a window of 0.75 days, as implemented in w¯otan (Hippke et al. 2019), to generate the flattened light curve for further analysis, and use only data with quality factor of 0. This light curve can be seen in Figure 1. The simple aperture photometric light curve has a scatter of 2527 ppm, which improves to 685 ppm after everest processing. We searched the flattened data for periodic transit signals using the transit least squares algorithm (TLS) (Hippke & Heller 2019), and found a prominent peak around 3.14 days as can be seen in Figure 2. We assessed the presence of additional candidate signals after modeling out the 3.14-d signal by re-running TLS, but did not find any with a significant signal detection efficiency (i.e., SDE>10). 2.2. Candidate Vetting with SPECULOOS Telescopes We followed up on the planetary candidate by observing with SPECULOOS Southern Observatory (SSO) two transit windows on UT 25 February 2020 by Ganymede and on UT 18 March 2020 by Io, and one transit window with SPECULOOS Northern Observa-. tory on UT 18 May 2020 by Artemis. SSO is composed of four telescopes: Io, Europa, Ganymede and Callisto, which are installed at ESO Paranal Observatory (Chile) and have been operational since January 2018. SNO is currently composed of one telescope (Artemis), which is located at the Teide Observatory (Canary Islands, Spain) and operational since June 2019. All SPECULOOS telescopes are identical robotic Ritchey-Chretien (F/8) telescopes with an aperture of 1-m. They are equipped with Andor iKon-L cameras with e2v 2K × 2K deep-depletion CCDs, which provide a Field of View (FoV) of 12 0 × 12 0 and the corresponding pixel scale is 0.35 00 pixel−1 (Delrez et al. 2018; Jehin et al. 2018). To schedule those windows we used the SPeculoos Observatory sChedule maKer (SPOCK), described in Sebastian et al. (in prep.). Observations were made with an exposure time of 40 s in an I+z filter, a custom filter (transmittance >90% from 750 nm to beyond 1000 nm) designed for the observation of faint red targets usually observed by the SPECULOOS survey (Delrez et al. 2018; Murray et al. 2020). SSO data were then processed using the SSO Pipeline, which accounts for the water vapor effects known to be significant for differential photometry of redder hosts with bluer comparison stars (Murray et al. 2020). SNO data were processed using prose, a Python-based data reduction package, which generates light curves from raw images (Garcia et al. in prep.). It creates a stacked image to extract the positions of the stars in the field, and uses the positions to perform aperture annulus photometry. A differential light curve is produced using a weighted light curve derived from the field stars, while the instrumental systematics, such as pointing shift and full width half maximum, are recorded to assist later in detrending. We show detrended light curves from SPECULOOS in Figure 3, where we recovered the transit events within 1σ of the calculated ephemeris from K2 data. Since these observations were obtained two years after K2 Campaign 15, they improve the precision of the transit ephemeris by an order of magnitude.

π Earth: a 3.14-day Earth-sized Planet from K2's Kitchen Served Warm: Observation

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 ABSTRACT We report on the discovery of a transiting Earth-sized (0.95R⊕) planet around an M3.5 dwarf star at 57 pc, K2-315b. The planet has a period of ∼3.14 days, i.e. ∼π, with an instellation of 7.45 S⊕. The detection was made using publicly available data from K2’s Campaign 15. We observed three additional transits with SPECULOOS Southern and Northern Observatories, and a stellar spectrum from Keck/HIRES, which allowed us to validate the planetary nature of the signal. The confirmed planet is well suited for comparative terrestrial exoplanetology. While exoplanets transiting ultracool dwarfs present the best opportunity for atmospheric studies of terrestrial exoplanets with the James Webb Space Telescope, those orbiting mid-M dwarfs within 100 pc such as K2-315b will become increasingly accessible with the next generation of observatories. stars: individual (2MASS J15120519-2006307, EPIC 249631677, TIC 70298662, K2-315b) – planets and satellites: detection Keywords: 1. INTRODUCTION The redesigned Kepler mission, K2 (Howell et al. 2014), has been a success by adding almost 400 confirmed planets to the 2,348 discovered by the original mission[1]. Building upon Kepler (Borucki et al. 2010), K2 expanded the search of planets around brighter stars, covered a wider region of sky along the ecliptic, and studied a variety of astronomical objects . Together, these endeavors have revolutionized the field of exoplanetary science by quadrupling the number of exoplanets known at the time, while K2 in particular has led to exciting discoveries, such as disintegrating planetesimals around the white dwarf WD-1145 (Vanderburg et al. 2015), multi-planet systems around bright stars like GJ 9827 (K2-135) (Niraula et al. 2017; Rodriguez et al. 2018), and resonant chains of planets like the K2-138 system with five planets (Christiansen et al. 2018). Space-based platforms such as Kepler can provide high-quality continuous monitoring of targets above the Earth’s atmosphere. The simultaneous photometric monitoring of tens of thousands of stars enables finding rare configurations (e.g., WD-1145) and answering science questions regarding planetary populations that are more statistical in nature such as how unique our own Solar System is, or what are the most common type of planets (e.g. Fressin et al. 2013; Fulton et al. 2017). Ground-based facilities, on the other hand, often detect fewer planets while operating at a lower cost. These planets frequently exhibit larger signal-to-noise ratios (SNRs) in various metrics (e.g., transmission), thereby allowing for these planets to be characterized further. One such example is the TRAPPIST-1 planetary system (Gillon et al. 2016, 2017), discovered by the TRAPPISTUltra Cool Dwarf Transiting Survey, a prototype survey for the SPECULOOS Survey (Gillon et al. 2013). The goal of the SPECULOOS Survey is to explore the nearest ultracool dwarfs (Teff <3000 K) for transits of rocky planets (Burdanov et al. 2018; Delrez et al. 2018; Jehin et al. 2018; Sebastian et al. in prep.). Although few systems are expected (Delrez et al. 2018; Sebastian et al. in prep.), their impact on the field will be significant as they should provide most of the temperate Earthsized exoplanets amenable for atmospheric studies with the next generation of observatories such as JWST (e.g. Gillon et al. 2020). Beyond the SPECULOOS Survey, which monitors nearby late-M dwarfs for terrestrial planets, the SPECULOOS telescopes have been used to study the planetary population around mid- and late-M dwarfs. In that context, SPECULOOS facilities have been involved in following up and validating planetary candidates, notably from TESS (G¨unther et al. 2019; Kostov et al. 2019; Quinn et al. 2019). Next to confirming planetary candidates that cross detection thresholds, we have started to investigate weaker signals. For this work, we revisited K2 data, a mission which ended only in 2019. We reanalyzed the light curves of stars with Teff < 3500 K, a Kepler magnitude < 15, and a log g > 4.5. While these criteria were motivated particularly to look for planets around ultra-cool dwarfs, they were relaxed in order to allow room for errors in the stellar properties and improve completeness of the analysis. Among the 1,213 stars fitting these criteria, EPIC 249631677 presented the strongest periodic transit-like signal. In this paper, we report the discovery of an Earthsized K2 planet in a close-in orbit around EPIC 249631677. The paper is structured as follow; observations (Section 2), analysis and validation (Section 3), and the discussion in regards to future prospects for characterization (Section 4). In this paper, we report the discovery of an Earthsized K2 planet in a close-in orbit around EPIC 249631677. The paper is structured as follow; observations (Section 2), analysis and validation (Section 3), and the discussion in regards to future prospects for characterization (Section 4). [1] https://exoplanetarchive.ipac.caltech.edu

π Earth: a 3.14-day Earth-sized Planet from K2's Kitchen Served Warm: Abstract & Intro

Imagine Superman absorbed the energy not of the sun, but of people’s gratitude and belief in his powers. And kryptonite was people’s disbelief, discouragement, and hate. I just described Bitcoin. You have heard it said that technology is a double-edged sword. Recently, ChatGPT. It can harm as well as uplift a student. Or humanity in general. But after some thought, I posit that some technologies, like Bitcoin, are a net-good technology. Much less harmful than useful and instead, very vulnerable to being attacked, stained, ridiculed, and greatly misunderstood. My idea could be taken with a pinch of salt. Because of its vulnerabilities, Bitcoin is one technology that quite early on, many famous people have said is a scam, a Ponzi scheme, money used by criminals, ‘stupid’ and ‘evil’. To be fair, though, others have praised it. , said Bill Gates, while the billionaire investor Michael Saylor quit his CEO job last year to focus on singing Bitcoin’s praises. And buying more Bitcoin. “It is a technological tour de force” The trouble is, Bitcoin is sometimes complicated, like an action novel - Fast paced action featuring Japanese, Chinese, and American corporations, financial mind games with people spending billions of dollars of money that ‘does not exist’, innocent victims who get ‘rekt’. Other times, it is mundane and in a little corner of the world for my neighbors right now hardly know it exists. Or that it is a real thing with real power. In other places, it is high philosophy dealing with human action (praxeology), divine conceptions, and so on. But it is good. Only good. The fastest good on Earth. And this might be appreciated if we ponder, as we shall do today, how people would react to its gradual disappearance, its relation to Facebook or Nuclear power, and the core architecture built mostly on cooperation and not competition. The Last Bitcoin Currently, there are 19.6 million bitcoins in existence, and they will soon reach the hard cap limit of 21 million. To get a feel for where Bitcoin stands in the eyes of the world, imagine this. Imagine Bitcoins’ greatest weakness  - the ability of keys to get lost - has affected all the coins except one. Of the 21,000,000 Bitcoin that can exist, 20,999,999 get lost, and only 1 Bitcoin is left in the entire world. Would this be a good thing or a bad thing? Some people would say it would be a bad thing but for different reasons. A Bitcoiner today would definitely say this would be a bad thing to happen, as Bitcoin would be one thread away from being lost forever. Though, chances are high that Bitcoiners in that world with only one coin left would be very humble people. True believers in a lost technology especially if lost coins had never been salvaged before. A no-coiner (non-Bitcoiner) today who has brushed against some very toxic maximalists, would likely say it is bad because it would lead to wars. ”, they would argue. With rage-fuelled toxic humans in their mind’s eye. “People would wring each other’s throats for this worthless single thing A no-coiner in that world with 1 coin would likely be somebody who doesn’t lose any sleep over “Bitcoin”. Hard to think they would even know what it is, as lost technology is usually sought out by archaeological types. But one thing I believe is nobody who learns of this one bitcoin would be outraged that only 1 exists. That would be absurd. They would be saddened at learning of the history of this great technology, now reduced to a single event in space and time. : Definitely, all altcoins would be goners. Not even one would be left Aside However, instead, this tragic event might then become the most uplifting event in the world. After moping around over lost bitcoins, this one coin could quickly become a beacon of hope. A unifier to put ahead of us, as we remember all the likenesses that went before it into the deep dark void of cyberspace. Preserved with the collective will of everybody on Earth like Da Vinci’s Mona Lisa. And maybe, if quantum computing is mature by then, there might be a way to actually map and treasure hunt for these lost coins in the depths of cyberspace. today’s no-coiner insists. Zapping me back to reality. “How about having a World War 3 because of this coin” “Frankly, it would be much easier for a few people to destroy the last few nodes holding up this last Bitcoin than to bother waging a world war over it at all”. : People will treasure Bitcoin’s Scarcity. Like they would Superman. They just haven’t realized it yet. Lesson Types of Technologies Physical Technology As already posited, most technology is a double-edged sword. That means, it could benefit you, but it could hurt you. Fire was the first example of highly-destructive, highly-beneficial tech. Thousands of years later, circa 1938, Nuclear power became the best example. In a few hours, the nuclear weapons we humans have created could totally destroy the planet, ushering all surviving creatures back to the Stone Age. Or rather, back to a post-CT-extinction world. But wielded with care and the will to create a great civilization, together, the energy abundance that our nuclear fission and fusion resources can unleash would solve world hunger, climate change, desertification, and global electrification, with enough to spare for space exploration. Physical technologies like nuclear power thus depend on humanity having enough heart to care about the common good for us all, more than the clouding squabbles over race, gender, religious affiliation, cultural predispositions, or economic interests. To use nuclear power for good means sacrificing the chance to exploit or step over others, for the opportunity to sit on the round table and work together. Social Technology Another type of technology is social technology. It is . Social technologies like telephones, the internet, and social media, have exponentially multiplied our capability to harness physical technologies like nuclear power, and we would be severely limited as a species without them. a way of using human, intellectual, and digital resources in order to influence social processes - Wikipedia Knowledge would travel at a snail’s pace, and some places would be dramatically better worse, in many ways, than others because of the highly difficult flow of technological progress and the unique cultural situations and environments of each place. and Now unlike physical technologies like fire, nuclear power or knives, social technologies are mostly a force for good, but there is a caveat. Being information-collecting entities, they can easily decouple from their place of serving people to making people serve them. The power shifts to reside not with the users anymore but with the central authorities i.e. the corporations owning the IP of these websites. Plus the websites themselves when the AIs get sentient! And because human habits are mathematically predictable (lunch is between 11 am and 2 pm everywhere), these sites e.g. Google or Facebook, have amassed so much data on their users that they can send targeted ads with precision, making money from us before we know we want to buy a product. This is no problem until data breaches happen, or until artificial intelligence sitting on top of this technology acquires the capability to undermine the efforts of us, the people, who trained it in the first place (by competing with us for pennies). As is happening today which is fuelling online rage and clickbait. Fiat currencies are another form of social technology with a central authority called the Central Bank, and altcoin cryptocurrencies are a form of social technology with a central authority called the ICO company. Synergistic social technology The third technology I know is Bitcoin. A synergistic social technology. A synergistic social technology works unlike any other social technology. First, it does not harvest people’s data so it then becomes even more powerful than the individual person. It grows only if people believe in it, protect it, and use it consistently. Any slight disinterest, distrust or dissatisfaction, and its value collapses (these are all those spiky swings of the Bitcoin price. It is frantically trying to satisfy everybody). Not like Google stock which is rock solid and stable. And goes up relatively predictably. in real-time When BTC grows in value, the people get stronger because the users are the owners. When data breaches happen, it suffers because people jump ship like * that. They are very picky when it comes to their monetary self-sovereignty. snap* So it can only be a force for good because bad people creeping in will scare away the good people who actually do the hard work of loving, sharing, building, maintaining, and innovating around the technology. This is easy to see with the Silk Road incident of 2013. Negative connotations of Bitcoin with criminal activity crashed the price faster than a meteorite. From $266 to $50. Did any illegal trade in drugs and whatnot proliferate with this crash? No. It quickly dried up. If anything, the US government greatly profited after the seizure of Bitcoin worth billions of dollars while US citizens were lost in FUD, faithless and not sure whether the dream of monetary sovereignty was over this quickly. Interestingly, some people tried creating Silk Road 2.0, but the FBI got them so fast that they hardly made headlines. : Criminal activity in a currency like Bitcoin = You will get caught and Bitcoin suffers. Lesson Fraudsters look for Thriving Environments Every Bitcoiner got on board this global social ecosystem by listening to a few sound rules of money and making the bold choice to live unapologetically truthfully. Bitcoin is good because fixed rules of money, including the ultimate rule on quantity, mean a simple order everyone can follow and make wealth. Work hard and buy or mine some Bitcoin satoshis. Hold for at least 5 years. You’ll make a profit more than anything else. How hard is that? How non-evil. Good money is not controlled by anybody but is protected and used by everybody. Alas, whenever good people connect to the wisdom that is Bitcoin and join the party, the number goes up and fraudsters get on board as well. Fraudsters are predators, and predators eat the meatiest prey in the Jungle. Despite being only a modest $600 billion net worth right now, because it is such a sound and positive force of good for people, the scammers are plentiful, and they want to take your cash and disappear. And each time good people’s money is taken, they get rekt (financially ruined) and the price crashes. The scammers go into hiding, to wait for you and me to pick ourselves up again, so they can strike again. Many of these scammers and fraudsters hide behind the thin veil of ‘cryptocurrencies’ so the next time you read a toxic maximalist calling an altcoin a “sh**coin”, understand they are frustrated and just want to protect you and themselves from the sweet words of scam artists. Pumping and dumping of crypto, even bitcoin “investments”, is fraud and hurts both the naive people who opt into these scams, and the bitcoin community at large when the exit is made and people’s morale crashes into millions of tiny pieces. : Bitcoin is not evil. It is the easiest technology for corrupt and evil people to ruin. That is why it sounds so evil when anything bad happens by its hand, yet the majority of the ills in the financial world happen via fiat currencies. Lesson Cooperation outshines Competition What’s in it for poor people? - Anonymous There are people who feel that Bitcoin has been an entirely useless innovation as far as getting poor people out of poverty is concerned, while billionaires like Michael Saylor keep buying all the bitcoins. They can make millions in profit in months when the price goes up, while a modest earning pleb can only Dollar Cost Average a few sats every month and hence needs to wait all 5 years to make a modest enough profit to cash out. But here are some facts; Logically, nobody can own all bitcoins cause not everybody wants to sell at any moment in time. If the price of Bitcoin goes up you can’t buy more with the stock you already have. People have to spend bitcoins on food and other things no matter how ‘hodledor’ they would like to be. Most importantly, Bitcoin is about the people. The common man, woman, and child. on how spending and replacing, vs hodling, is how we spread Bitcoin adoption and ultimately, its utility in more sectors around the world. Carl Menger penned a great piece a few days ago Cooperation outshines competition. Consensus and collective agreement is built into the nature of the protocol, not one-upmanship. If Bitcoin gets too valuable and transaction fees balloon, I believe there will be another fork to break down satoshis into even smaller amounts. Or we shall find ways to make bigger and cheaper coinjoins. Because the most valuable Bitcoiner to the network is every Bitcoiner. Not only Mr. Saylor. More important than competition, Bitcoin thrives on cooperation. Think of everybody; some work as miners, others run nodes, some code LN apps, others orange-pill. It is impossible for us to all stack as much as the other because different work earns differently in the Bitcoin ecosystem. In the world. And aside from the Bitcoin activities, some people are CEOs of big companies creating all the other wonderful stuff we want to buy with Bitcoin while some are students, still grappling with what they should learn to make it in this fast-changing world, et cetera. Bottom line - Together is how it works. Thinking of how each Bitcoin node runs can show us the importance of sticking together. The one lesson we should steadfastly hold onto, as taught to us by Bitcoin itself, is using and running Bitcoin just like Bitcoin nodes. Together. As a family. Some nodes (people) are big miners with 10,000 ASICs minting entire bitcoins on a daily basis while others are laptop nodes. It does not matter. All need to DYOR (Do Their Own Research) and verify transactions themselves. If a transaction (a deal in the real world) is no good, they should do everyone else a favor and block it. Fast. If Bitcoin goes to $1 million and Michael Saylor becomes the richest man in the history of our planet, I believe I will benefit because Mr. Saylor will spend his coins investing in pro-people companies all over the world. Poor or financially desperate people in Africa, Asia, or anywhere right now should stack as a good habit for financial discipline, the way exercise is good for your body even when you are not preparing for a world-championship fighting match (like yours truly). When the price gears up, opportunities will open up. And Bitcoiners are hardly underpaid despite great work ‘cause honest payments flow best through Bitcoin as well. One more thing, the halving is near. Get ready.

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