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The Mystery of the "Space Roar"

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ThinkStock

In 2009, scientists at NASA's Goddard Space Flight Center sent a machine called ARCADE into space on a giant balloon, in search of radiation from the universe's earliest stars. ARCADE (Absolute Radiometer for Cosmology, Astrophysics, and Diffuse Emission) carried seven sensors that picked up electromagnetic radiation like radio waves. The plan was to lift it far enough up to prevent the Earth's atmosphere from interfering. Then, the finely-tuned instrument could detect faint radio signals from ancient stars.

Instead, ARCADE detected a huge amount of radio noise—six times louder than scientists had predicted—which has since come to be known as the "space roar." And while there are some theories, we still don't know what's causing it.

Space Sounds

Of course, space isn't roaring in any way that our ears could hear. But there are objects in the universe—including some galaxies—which emit radio waves via synchrotron radiation.

According to Dale Fixsen, a University of Maryland research scientist and a member of the ARCADE team, NASA had built devices that detected radio noise before. These worked by looking at one point in the sky, and then at another nearby one for contrast. These instruments were useful for detecting radio-emitting galaxies and supernovas, because they measured the difference between two points. But they couldn't detect the roar.

"If there's a uniform source [of synchrotron radiation], those instruments are blind to it," Fixsen tells mental_floss.

On the other hand, ARCADE used a "large beam" that searched 7 percent of the sky. Because of the large area it searched, and its high-precision sensors, it was the first instrument we've built that could discover the roar.

But it couldn't find out everything. Fixsen says that synchrotron radiation has a characteristic spectrum. And since every source of the radiation displays this same spectrum, ARCADE couldn't discover what was roaring.

Roar Theories

Fixsen says that synchrotron radiation usually comes hand in hand with infrared radiation. We've already measured the amount of infrared radiation that the Milky Way emits with the COBE satellite, and according to Fixsen, with our galaxy's level of infrared, it doesn't look like the Milky Way is the source of the synchrotron radiation for the "space roar."

"The relationship is tight for all galaxies we've measured," Fixsen says. "It should hold true for our galaxy as well."

On the other hand, theorists think that we've detected almost all the sources of this radiation outside our galaxy. And we know that none of these sources is causing the "roar."

According to Fixsen, there are a few possible explanations. First, the "roar" could be coming from the earliest stars. The first stars didn't have any dust—because the first dust in the universe was formed within those stars. This could have let those stars create a lot of synchrotron radiation, without a correspondingly high amount of infrared.

Second, the radiation might be coming from gases in large clusters of galaxies—Fixsen says that it would be difficult for the instruments we've used up until now to detect radiation from these.

Third, it could be coming from dim, but extremely plentiful, radio galaxies. Individually, they would be too quiet for us to detect, but en masse they might be loud enough to create the "roar."

Future plans

But while there are some plausible theories, we still don't have any data to tell us which one is right. Fixsen says that there's been talk about flying ARCADE again (it's currently living in the Goddard Space Flight Center). Or they might use an instrument on the ground next time; Fixsen says they could use the data from the ARCADE mission to calibrate it, and avoid interference from the atmosphere.

But for now, what NASA wrote in its 2009 press release is still true: "The source of this cosmic radio background remains a mystery."

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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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