Original image
David A. Aguilar/Harvard-Smithsonian Center for Astrophysics

The Terrible Weather on 6 Exoplanets

Original image
David A. Aguilar/Harvard-Smithsonian Center for Astrophysics

Of the more than 900 exoplanets—planets outside our solar system—discovered to date, none, not a single one, appears to be a nice place to visit or live. If anything, descriptions of most of these far-flung bodies sound like a walking tour of hell. There’s the planet where glass falls from the sky, or the one where temperatures spike so quickly that they generate supersonic megastorm.

These weather reports are educated guesses, of course, culled from measurements of the apparent mass, infrared output, chemical makeup, and position of each exoplanet. Though the majority of these alien worlds tend to be astonishingly large and hot, that’s more a function of how our space-based and terrestrial telescopes search—big and blazing stands out better than Earth-sized and temperate, and planets with a tighter, closer orbit are more likely to catch our attention by crossing in front of a star. Here are the exoplanets whose estimated weather conditions are as detailed and evocative as they are terrifying, all further reminders of how uniquely livable our own planet is. (Note: There are exoplanets with less harsh or extreme characteristics, but whose weather is even more speculative.)

1. Baking and Breezy: Kepler-76b

Our first selection (above) is, in many ways, the archetypical exoplanet—its name is exceedingly dull, an indication of the telescope that spotted it (NASA’s space-based Kepler telescope, in this case) and the star system it resides in (it’s the “b” planet in the Kepler 76 system). It’s also what astronomers call a “hot Jupiter,” a gas giant with at least as much mass as our own resident behemoth, but with a much higher temperature. Kepler-76b’s hotness comes from its cozy proximity to its own star, circling it every 1.5 days (compared to 4332 days for Jupiter). The result is a world whose surface doesn’t rotate—it’s tidally-locked, like our Moon—but whose blisteringly hot winds do, carrying the 3600-degree Fahrenheit temperatures on its star-facing side around to the “dark” side in a constant, planet-wide gale.

2. Blue Skies, with a Chance of Glass: HD 189733b


HD 189733b's blue sky is caused by silicate particles in the atmosphere that form into droplets of glass, which cast a bluish tinge. Researchers studying the planet with the Hubble space telescope determined not only its unique, cobalt-blue hue, but the fact that its glass rainfall is whipping across the planet at some 4500 mph. And like Kepler-76b, this silicate-scoured deathtrap is a tidally-locked hot Jupiter—though with its permanently dark side averaging around 1500 degrees Fahrenheit, it’s comparatively temperate.

3. Bad World Rising: Kepler-36b

David A. Anguilar/Harvard-Smithsonian Center for Astrophysics

One of a slim minority of exoplanets discovered that happen to be rocky, Kepler-36b has a turbulent orbital relationship with its neighboring world, 36c. Every 97 days that planet, a “hot Neptune” (like a hot Jupiter, but smaller) gas giant comes perilously close to 36b, roughly five times the distance between the Earth and the Moon. Astronomers paint the spectacle as undoubtedly glorious, with the purple gas giant looming some 2.5 times larger (in diameter) than our own moon. Unfortunately, these picturesque swing-bys would likely trigger cataclysmic—by our standards—seismic activity, as gravitational forces stretch the two planets, triggering even more volcanic activity on 36b, a planet already defined by its lava flows and 1300-degree Fahrenheit temperatures. (The image above shows what 36c might look like from 36b.)

4. A Song of Ice-Cold Rocks and Fire: CoRoT-7b


Like many confirmed exoplanets, CoRoT-7b is close enough to its parent star to be both hotter than anyone’s interpretation of hell (up to 4700 F, to be specific) and tidally-locked, with one hemisphere cooking under a stellar heat lamp. CoRoT-7b is a strange case, though. It’s rocky, so its heat isn’t distributed throughout the planet, as is the case with some gas giants, keeping its dark hemisphere at somewhere around minus 350 F. Weirder still, astronomers believe that 7b’s combination of scorching heat and mineral-rich atmosphere could result in a rainfall of rocks, on both the frigid and lava-soaked sides.

5. High Winds, Green Sunset: HD 209458b

European Space Agency and Alfred Vidal-Madjar (Institut d'Astrophysique de Paris, CNRS, France)

The most interesting thing about HD 209458b isn’t that it’s so ludicrously windy—nearly 4500 mph, similar to the speeds estimated in the glass-blasted upper reaches of HD 189733b—but that it's leaking. Although its atmosphere includes significant amounts of carbon monoxide, sodium, and other elements, the gas giant’s close proximity to its star seems to be tearing the planet’s hydrogen free. HD 209458b could be losing as much as 500 million kg of hydrogen per second, which might be visible in a long, comet-like tail. Anyone somehow lurking within the atmosphere, however, wouldn’t necessarily be able to see that trail, though researchers have described what it might be like to watch the sunset from HD 209458b—a eerie progression from blue to green, no doubt complimented wonderfully by that scouring carbon monoxide super-breeze. 

6. Explosions in the Sky: HD 80606b

D. Kasen, J. Langton, and G. Laughlin (UCSC)

Most days on HD 80606b are simply nightmarish—980 degrees Fahrenheit, with unimaginable pressures due to its mass (four times that of Jupiter). But every 114 or so days, the gas giant’s hugely elliptical orbit brings it point-blank with its star. Over six hours, the temperature rises by some 1000 degrees, and the atmosphere essentially explodes. As the star gets 1000 times brighter, the sudden heat births titanic superstorms, with winds topping 11,000 mph. These atmospheric shockwaves wrap around the planet as it rockets back along its pinched orbital circuit, away from the heat source that creates perhaps the most violent weather system ever discovered.

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

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