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Astronomers Find Seven "Earth-Like" Planets Orbiting a Cool Star

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An artist's conception of what it might be like to stand on the surface of the exoplanet TRAPPIST-1f. Image credit: NASA/JPL-Caltech.

 
Astronomers say they’ve discovered seven Earth-sized planets in tight orbit around a cool, dim star about 39 light-years from us—and all seven are located in the habitable zone that could potentially host life. This is the first time a planetary system oriented to this kind of star has been detected—and its discovery holds the potential to lead us to a lot more exoplanets. An international team of researchers reported their findings in a letter published today in the journal Nature.

“It’s the first time we have seven planets in this temperate zone … that can be called terrestrial,” lead author Michaël Gillon, of Belgium’s Université de Liège, said in a press briefing. “So many is really, really surprising.”

TRAPPIST-1 is an ultracool dwarf star that’s 1/80th the brightness of the Sun and similar in size to Jupiter. All seven planets in its system are within 20 percent of the size and mass of Earth, and their density measurements indicate they’re likely of rocky composition. They’re clutched by TRAPPIST-1 in tight orbits—all would fit well within the orbit of Mercury. But unlike in our solar system, where such closeness to a hot star renders life impossible, the TRAPPIST-1 planetary system, with its cool celestial heart, could potentially host liquid water and organic molecules.

The first three planets were spotted in early 2016 by some of the same researchers involved in the current findings, including Gillon. As the planets cross in front of the star during their orbits, they cause the star, which emits light in the infrared, to briefly dim. Such transits, or eclipses, provide a common way for astronomers to detect exoplanets.

Using telescopes in Chile, South Africa, Spain, the UK, and Morocco, the researchers followed up on these transit signals multiple times in 2016, most notably in late September with a 20-day, nearly continuous monitoring of the star using the Spitzer Space Telescope, currently located about 145 million miles from us in an Earth-trailing orbit around the Sun. By moving our view off the Earth, researchers were able to detect 34 separate transits. This turned out to be the result of seven planets—six in near-resonant orbit—crossing in front of their home star. (The transit of the seventh was detected only once, so the orbit of this planet, known as TRAPPIST-h, hasn’t been determined yet.)

The planets have relatively narrow surface temperature fluctuations—about 100 degrees—despite their proximity to their home star. (Compare that to Mercury, which has temperature variations of nearly 1200°F.) The researchers write that three of the planets—E, F, and G—“could harbor water oceans on their surfaces, assuming Earth-like atmospheres.”

They’re probably tidally locked, meaning the same hemisphere of each planet always faces the star. Because they’re so close to each other, they can influence each other’s movements, causing eccentric orbits. The result is a planetary system that looks more like Jupiter and its Galilean moons than our own solar system. The planets likely formed outside the system and were pulled into it, and it’s entirely possible the seven so far identified are not alone.

Top row: Artist conceptions of the seven planets of TRAPPIST-1 with their orbital periods, distances from their star, radii, and masses as compared to those of Earth. Bottom row: Data about Mercury, Venus, Earth, and Mars. Image Credit: NASA/JPL-Caltech.

“It’s an exciting discovery," University of Montreal astrophysicist Lauren Weiss tells mental_floss. "The TRAPPIST-1 system demonstrates that even the smallest stars in our galaxy can form a multitude of planets.”

Weiss, who was not involved in the current study, researches exoplanetary systems—their masses, density, composition, and orbital dynamics. “These planets are all of sizes that are consistent with rocky compositions," she says of the TRAPPIST-1 system. "In addition, the mass measurements the authors have conducted are consistent with rocky compositions for the planets.”

Most planet-hunting efforts have been focused on brighter stars and bigger planets—and these efforts have been fruitful. Consider NASA’s Kepler mission: As of today, astronomers using the space telescope have detected 2330 exoplanets.

But the TRAPPIST-1 discovery suggests that we shouldn’t overlook the potential that even cool, dim stars have to lead us to new planets. About 15 percent of stars in our neighborhood are ultracool dwarfs like TRAPPIST-1. Moreover, M dwarf stars like this one are by far the most abundant in the galaxy, says astronomer Jackie Faherty, senior scientist at the American Museum of Natural History, who studies them.

“When I heard that the number of planets around TRAPPIST-1 had increased from three to seven, I was taken aback,” Faherty tells mental_floss. “The thought that the galaxy must be bursting at the seams with planets immediately sprung into my head.”

What makes them especially appealing is that, because they are dim and small, a relatively substantial amount of light is blocked when a near object—like a planet in a close orbit—crosses in front of one. That makes planetary transits easier to spot.

What does this discovery suggest about the number of Earth-like planets in the galaxy? “There are 200 billion stars in our galaxy, so do the count. You multiply by 10, and you have the number of Earth-size planets in the galaxy—which is a lot,” study co-author Emmanuël Jehin, of the Université de Liège, said in the press briefing.

And as for finding life on one of the TRAPPIST-1 planets? Gillon said that, short of traveling to one and collecting a sample, we can’t say for certain whether life exists on any of them, but the presence of certain molecules in combination with one another will be a likely indicator. “If you have methane, oxygen or ozone, and CO2, you have a strong indication of life and biological activity,” he said in the press briefing. The combination is key—the presence of any one of these on its own isn’t enough to indicate biological life, Gillon noted.

According to Gillon, the James Webb Space Telescope—an infrared telescope slated for launch in October 2018—will greatly help in this effort. “Methane and, for instance, water could be detected with the James Webb telescope, and give us a very good insight on the atmospheric properties of the planet,” he said.

Of course, other scientists are continuing their own search for exoplanets. One high-profile initiative coming soon is NASA's Transiting Exoplanet Survey Satellite (TESS), which will study more than 200,000 of the brightest stars for two years in hopes of discovering thousands of exoplanets. It is slated to launch in early to mid 2018.

TESS project scientist Stephen Rinehart tells mental_floss that the TRAPPIST-1 planetary system "actually dovetails very nicely with what TESS is expected to discover. At present, there are only a handful of known exoplanets that are suitable for more detailed study. By focusing on finding planets around bright, nearby stars, we hope that TESS will find some 'siblings' for Trappist-1—other systems nearby with multiple planets in the habitable zone of their host star."

But it's not just identifying more exoplanets that's important—it's closer study of individual planets that we need. Rinehart points out that while planets located in the "habitable zone" sound promising, we don't yet know if even one of them can host life. "We know that there are a lot of small, rocky planets in the habitable zones of their host stars, but look at our own solar system," he says. "Venus, Earth, and Mars are all in (or very nearly in) the habitable zone, all three are small, rocky planets, but the three are completely different! So, if we find an exoplanet that is about the same size and mass as Earth, and that planet is in the habitable zone of its host star, we know that it has the potential to be habitable, but we can’t know that it is habitable without more careful study."

The TRAPPIST-1 researchers are going to continue their own search with the project SPECULOOS (Search for Planets EClipsing ULtra-cOOl Stars).

“We’ve taken a crucial step of finding life out there,” said co-author Amaury Triaud, of the University of Cambridge. “Here if life managed to thrive and release gases similar to those we have on Earth, we will know. We have the right target.”

Editor's note: This post has been updated with additional commentary from TESS project scientist Stephen Rinehart.

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Nick Briggs/Comic Relief
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What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
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Nick Briggs/Comic Relief

Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]

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