Astronomers Trace Fast Radio Burst to Extreme Cosmic Neighborhood

On Christmas Eve 2016, Andrew Seymour, an astronomer at the Arecibo Observatory in Puerto Rico, kissed his 4-year-old daughter, Cora Lee, goodnight, telling her he was off to track Santa. He walked to the well-worn telescope, occasionally passing revelers riding horses through the empty streets—a common sight in Arecibo during the holidays. Sometimes a lonely firework would light up in the distance. Close to midnight, he nodded to a guard and entered the nearly empty complex.

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The radio dish was on a break from its regular schedule, so Seymour decided to test out new hardware that he and his colleagues had been working on. Soon after he began recording his observations, an extremely powerful radio source, 3 billion light-years away, decided to say hello. Seymour didn’t find Santa that Christmas, but rather an unexpected twist in the tale of one of the most mysterious objects in the cosmos.

The object that Seymour caught that night was the only known repeating fast radio burst (FRB), an ultra-brief flash of energy that flickers on and off at uneven intervals. Astronomers had been debating what might be causing mysterious repeater, officially called FRB 121102 and unofficially the “Spitler burst,” after the astronomer who discovered it.

In the weeks following that Christmas detection, Arecibo registered 15 more bursts from this one source. These flashes were the highest frequency FRBs ever captured at the time, a measurement made possible by the hardware Seymour and his team had just installed. Based on the new information, the scientists have concluded in a study released this week in the journal Nature that whatever object is creating the bursts, it must be in a very odd and extreme cosmic neighborhood, something akin to the environment surrounding a black hole with a mass of more than 10,000 suns.

The new work helps to strengthen the theory that at least some FRBs might be produced by magnetars—highly magnetized, rotating neutron stars, which are the extremely dense remains of massive stars that have gone supernova, said Shami Chatterjee, an astrophysicist at Cornell University. In the case of the repeater, it could be a neutron star “that lives in the environment of a massive black hole,” he said. Or it might also be like nothing we’ve seen before—a different kind of magnetar ensconced in a very intense, magnetically dense birth nebula, unlike any known to exist in our galaxy—“quite extraordinary circumstances,” he said.

Too Extreme to Find

It wasn’t obvious at first that the repeating burst had to live in such an extreme environment. In October, 10 months after Seymour detected that initial burst at Arecibo, Jason Hessels, an astronomer at the University of Amsterdam, and his student Daniele Michilli were staring at the data on Michilli’s laptop screen. They had been trying to determine whether a magnetic field near the source might have twisted its radio waves, an effect known as Faraday rotation. There appeared to be nothing to see.

But then Hessels had an idea: “I wondered whether maybe we had missed this effect simply because it was very extreme.” They had been looking for just a little bit of a twist. What if they were to search for something exceptional? He asked Michilli to crank up the search parameters, “to try crazy numbers,” as Michilli put it. The student expanded the search by a factor of five—a rather “naive thing to do,” Chatterjee said, because such a high value would be completely unprecedented.

When Michilli’s laptop displayed the new data plot, Hessels immediately realized that the radio waves had gone through a hugely powerful magnetic field. “I was shocked to see how extreme the Faraday rotation effect is in this case,” he said. It was like nothing else ever seen in pulsars and magnetars. “I’m also embarrassed because we were sitting on the critical data for months” before attempting such an analysis, he added.

Jason Hessels led the team that identified the Faraday rotation coming from the burst.

Courtesy of Jason Hessels

The discovery sent ripples across the community. “I was shocked by the email announcing the result,” said Vicky Kaspi, an astrophysicist at McGill University. “I had to read it multiple times.”

Final confirmation came from a team searching for aliens. The Breakthrough Listen initiative ordinarily uses radio telescopes such as the Green Bank Telescope in West Virginia to scan the skies for signs of extraterrestrial life. Yet “since it’s not obvious in which direction they should point the telescope to search for E.T., they decided to spend some time looking at the repeating FRB, which clearly paid off,” said the astronomer Laura Spitler, namesake of the Spitler burst.

The Green Bank Telescope not only confirmed the Arecibo findings, it also observed several additional bursts from the repeater at even higher frequencies. These bursts also showed the same mad, highly twisted Faraday rotation.

What Powers Them

The extreme Faraday rotation is a signal that “the repeating FRB is in a very special, extreme environment,” Kaspi said. It takes a lot of energy to produce and maintain such highly magnetized conditions. In one hypothesis outlined by the researchers, the energy comes from a nebula around the neutron star itself. In another, it comes from a massive black hole.

In the nebula hypothesis, flares from a newly born neutron star create a nebula of hot electrons and strong magnetic fields. These magnetic fields twist the radio waves coming out of the neutron star. In the black hole model, a neutron star has its radio waves twisted by the enormous magnetic field generated by a nearby massive black hole.

Researchers haven’t come to an agreement about what’s going on here. Kaspi leans toward the black hole model, but Brian Metzger, an astrophysicist at Columbia University, feels that it’s somewhat contrived. “In our galaxy, only one out of dozens of magnetars resides so close to the central black hole. What makes such black hole-hugging magnetars so special that they would preferentially produce fast radio bursts? Did we just get really lucky with the first well-localized FRB?”

And the debate may get muddier before it gets cleared up. Chatterjee said theorists are certain to soon jump on the paper and start producing a multitude of new models and possibilities.

Burst Machines

The Spitler repeater is still the only FRB source that has been nailed down to a particular galaxy. No one knows quite where the other bursts are coming from. To say with any certainty that some—or all—of these energetic radio flashes come from highly magnetized environments, researchers need more data. And data are coming in. The Australian Square Kilometer Array Pathfinder (ASKAP), which is not yet officially complete, has already netted more FRBs than any other telescope in the world. With a tally of about 10 FRBs last year alone, it has proven to be “a remarkable FRB-finding machine,” said Matthew Bailes, an astrophysicist at Swinburne University of Technology—although none of them repeat.

Soon another telescope with a highly unusual design, called CHIME, will come online in Canada, and should spot many more FRBs—maybe 10 times more than ASKAP. Other next-generation telescopes, like the Square Kilometer Array (SKA), with dishes in South Africa and Australia, will surely contribute as well. As we register more of these flashes, chances are that some of them will repeat. Once scientists can sift through such data, the Faraday rotation effect may help them understand whether all FRBs are powered by a similar mechanism—or not.

Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

The Math Behind Gerrymandering and Wasted Votes

Imagine fighting a war on 10 battlefields. You and your opponent each have 200 soldiers, and your aim is to win as many battles as possible. How would you deploy your troops? If you spread them out evenly, sending 20 to each battlefield, your opponent could concentrate their own troops and easily win a majority of the fights. You could try to overwhelm several locations yourself, but there’s no guarantee you’ll win, and you’ll leave the remaining battlefields poorly defended. Devising a winning strategy isn’t easy, but as long as neither side knows the other’s plan in advance, it’s a fair fight.

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Now imagine your opponent has the power to deploy your troops as well as their own. Even if you get more troops, you can’t win.

In the war of politics, this power to deploy forces comes from gerrymandering, the age-old practice of manipulating voting districts for partisan gain. By determining who votes where, politicians can tilt the odds in their favor and defeat their opponents before the battle even begins.

In 1986, the Supreme Court ruled extreme partisan gerrymanders unconstitutional. But without a reliable test for identifying unfair district maps, the court has yet to throw any out. Now, as the nation’s highest court hears arguments for and against a legal challenge to Wisconsin’s state assembly district map, mathematicians are on the front lines in the fight for electoral fairness.

Simple math can help scheming politicians draw up districts that give their party outsize influence, but mathematics can also help identify and remedy these situations. This past summer the Metric Geometry and Gerrymandering Group, led by the mathematician Moon Duchin, convened at Tufts University, in part to discuss new mathematical tools for analyzing and addressing gerrymandering. The “efficiency gap” is a simple idea at the heart of some of the tools being considered by the Supreme Court. Let’s explore this concept and some of its ramifications.

Start by imagining a state with 200 voters, of whom 100 are loyal to party A and 100 to party B. Let’s suppose the state needs to elect four representatives and so must create four districts of equal electoral size.

Imagine that you have the power to assign voters to any district you wish. If you favor party A, you might distribute the 100 A voters and 100 B voters into the four districts like this:

With districts constructed in this way, party A wins three of the four elections. Of course, if you prefer party B, you might distribute the voters this way:

Here, the results are reversed, and party B wins three of the four elections.

Notice that in both scenarios the same number of voters with the same preferences are voting in the same number of elections. Changing only the distribution of voters among the districts dramatically alters the results. The ability to determine voting districts confers a lot of power, and attending to some simple math is all that’s needed to create an electoral edge.

What if, instead of creating an advantage for one party over the other, you wished to use your power to create fair districts? First, you’d need to determine what “fair” means, and that can be tricky, as winners and losers often have different perspectives on fairness. But if we start with some assumptions about what “fair” means, we can try to quantify the fairness of different voter distributions. We may argue about those assumptions and their implications, but by adopting a mathematical model we can attempt to compare different scenarios. The efficiency gap is one approach to quantifying the fairness of a voter distribution.

To understand the efficiency gap, we can begin with the observation that, in a series of related elections, not all votes have the same impact. Some votes might make a big difference, and some votes might be considered “wasted.” The disparity in wasted votes is the efficiency gap: It measures how equally, or unequally, wasted votes are distributed among the competing parties.

So what counts as a wasted vote? Consider California’s role in presidential elections. Since 1992, California has always backed the Democratic nominee for president. Therefore, California Republicans know they are almost certainly backing a losing candidate. In some sense their vote is wasted: If they were allowed to vote in a toss-up state like Florida, their vote might make more of a difference. From a Republican perspective, that would be a more efficient use of their vote.

As it turns out, Democratic voters in California can make a similar argument about their vote being wasted. Since the Democratic candidate will likely win California in a landslide, many of their votes, in a sense, are wasted, too: Whether the candidate wins California with 51 percent of the vote or 67 percent of the vote, the outcome is the same. Those extra winning votes are meaningless.

Thus, in the context of the efficiency gap, there are two kinds of wasted votes: those for a losing candidate and those for a winning candidate that go beyond what is necessary for victory (for simplicity, we take the threshold for victory to be 50 percent, even though this could technically result in a tie; an actual tie is beyond unlikely with hundreds of thousands of voters in each congressional district). In a multi-district election, each party will likely have wasted votes of each kind. The efficiency gap is the difference in the totals of the wasted votes for each party, expressed as a percentage of total votes cast. (We subtract the smaller number from the larger when possible, to ensure a nonnegative efficiency gap. We could also take the absolute value of the difference.)

Let’s return to our four-district scenarios and examine their efficiency gaps. Our first distribution looked like this.

In this scenario, 75 of B’s votes are wasted: 60 in losing causes and 15 more than the 25 needed to win district 4. Only 25 of party A’s votes are wasted: 5 extra votes in each victory and 10 losing votes. The raw difference in wasted votes is 75 − 25 = 50, so the efficiency gap here is 50/200 = 25 percent. We say the 25 percent efficiency gap here favors party A, as party B had the larger number of wasted votes. In the second scenario, where the numbers are reversed, the 25 percent efficiency gap now favors party B.

Can the efficiency gap give us a sense of the fairness of a distribution? Well, if you had the power to create voting districts and you wanted to engineer victories for your party, your strategy would be to minimize the wasted votes for your party and maximize the wasted votes for your opponent. To this end, a technique colorfully known as packing and cracking is employed: Opposition votes are packed into a small number of conceded districts, and the remaining block of votes is cracked and spread out thinly over the rest of the districts to minimize their impact. This practice naturally creates large efficiency gaps, so we might expect fairer distributions to have smaller ones.

Let’s take a deeper look at efficiency gaps by imagining our 200-voter state now divided into 10 equal districts. Consider the following voter distribution, in which party A wins 9 of the 10 districts.

On the surface, this doesn’t seem like a fair distribution of voters. What does the efficiency gap say?

In this scenario, almost all of party B’s votes are wasted: nine losing votes in each of nine districts, plus nine excess votes in one victory, for a total of 90 wasted votes. Party A’s voters are much more efficient: only 10 total votes are wasted. There is a difference of 90 − 10 = 80 wasted votes and an efficiency gap of 80/200 = 40 percent, favoring party A.

Compare that with the following distribution, where party A wins 7 of the 10 districts.

Here, the wasted vote tally is 70 for party B and 30 for party A, producing an efficiency gap of 40/200 = 20 percent. A seemingly fairer distribution results in a smaller efficiency gap.

As a final exercise, consider this even split of district elections.

The symmetry alone suggests the answer, and the calculations confirm it: 50 wasted votes for each party means a 0 percent efficiency gap. Notice here that a 0 percent efficiency gap corresponds to an independent notion of fairness: Namely, with voters across the state evenly split between both parties, it seems reasonable that each party would win half of the elections.

These elementary examples demonstrate the utility of the efficiency gap as a measure of electoral fairness. It’s easy to understand and compute, it’s transparent, and its interpretations are consistent with other notions of fairness. It’s a simple idea, but one that is being used in a variety of complex ways to study gerrymandering. For example, mathematicians are now using simulations to consider millions of theoretical electoral maps for a given state and then examining the distribution of all possible efficiency gaps. Not only does this create a context for evaluating the fairness of a current map against other possibilities, it can also potentially be used to suggest fairer alternatives.

Though voters are not actually assigned to districts in the way we have imagined in our examples, the practice of gerrymandering achieves similar results. By strategically redrawing district boundaries, gerrymanderers can engineer voting distributions to create an uneven electoral playing field. These unfair fights affect how we are governed and help majority-party incumbents coast to re-election term after term. The case before the Supreme Court involves just one of many potentially unfair maps. Objective mathematical tools like the efficiency gap may be the only way to root out gerrymandering and keep our political battlefields in balance.

Download the “Doing the Political Math” PDF worksheet to practice these concepts or to share with students.

Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

What Protects Elephants from Cancer?

Elephants and other large animals have a lower incidence of cancer than would be expected statistically, suggesting that they have evolved ways to protect themselves against the disease. A new study reveals how elephants do it: An old gene that was no longer functional was recycled from the vast “genome junkyard” to increase the sensitivity of elephant cells to DNA damage, enabling them to cull potentially cancerous cells early.

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In multicellular animals, cells go through many cycles of growth and division. At each division, cells copy their entire genome, and inevitably a few mistakes creep in. Some of those mutations can lead to cancer. One might think that animals with larger bodies and longer lives would therefore have a greater risk of developing cancer. But that’s not what researchers see when they compare species across a wide range of body sizes: The incidence of cancer does not appear to correlate with the number of cells in an organism or its lifespan. In fact, researchers find that larger, longer-lived mammals have fewer cases of cancer. In the 1970s, the cancer epidemiologist Richard Peto, now a professor of medical statistics and epidemiology at the University of Oxford, articulated this surprising phenomenon, which has come to be known as Peto’s paradox.

The fact that larger animals like elephants do not have high rates of cancer suggests that they have evolved special cancer suppression mechanisms. In 2015, Joshua Schiffman at the University of Utah School of Medicine and Carlo Maley at Arizona State University headed a team of researchers who showed that the elephant genome has about 20 extra duplicates of p53, a canonical tumor suppressor gene. They went on to suggest that these extra copies of p53 could account, at least in part, for the elephants’ enhanced cancer suppression capabilities. Currently, Lisa M. Abegglen, a cell biologist at the Utah School of Medicine who contributed to the study, is leading a project to find out whether the copies of p53 have different functions.

Vincent Lynch, a geneticist at the University of Chicago, has shown that part of what enabled elephants to grow so big was that one of their pseudogenes—a broken duplicate of an ancestral gene—suddenly acquired a new function.

Courtesy of Vincent J. Lynch

Yet extra copies of p53 are not the elephants’ only source of protection. New work led by Vincent Lynch, a geneticist at the University of Chicago, shows that elephants and their smaller-bodied relatives (such as hyraxes, armadillos and aardvarks) also have duplicate copies of the LIF gene, which encodes for leukemia inhibitory factor. This signaling protein is normally involved in fertility and reproduction and also stimulates the growth of embryonic stem cells. Lynch presented his work at the Pan-American Society for Evolutionary Developmental Biology meeting in Calgary in August 2017, and it is currently posted on biorxiv.org.

Lynch found that the 11 duplicates of LIF differ from one another but are all incomplete: At a minimum they all lack the initial block of protein-encoding information as well as a promoter sequence to regulate the activity of the gene. These deficiencies suggested to Lynch that none of the duplicates should be able to perform the normal functions of a LIF gene, or even be expressed by cells.

The eminent biologist Richard Peto, now at the University of Oxford, pointed out in the 1970s that elephants and other large-bodied animals ought to be at great statistical risk for cancer.

Cathy Harwood

But when Lynch looked in cells, he found RNA transcripts from at least one of the duplicates, LIF6, which indicated that it must have a promoter sequence somewhere to turn it on. Indeed, a few thousand bases upstream of LIF6 in the genome, Lynch and his collaborators discovered a sequence of DNA that looked like a binding site for p53 protein. It suggested to them that p53 (but not any of the p53 duplicates) might be regulating the expression of LIF6. Subsequent experiments on elephant cells confirmed this hunch.

To discover what LIF6 was doing, the researchers blocked the gene’s activity and subjected the cells to DNA-damaging conditions. The result was that the cells became less likely to destroy themselves through a process called apoptosis (programmed cell death), which organisms often use as a kind of quality control system for eliminating defective tissue. LIF6 therefore seems to help eradicate potentially malignant cells. Further experiments indicated that LIF6 triggers cell death by creating leaks in the membranes around mitochondria, the vital energy-producing organelles of cells.

To find out more about the evolutionary history of LIF and its duplicates, Lynch found their counterparts in the genomes of closely related species: manatees, hyraxes and extinct mammoths and mastodons. His analysis suggested that the LIF gene was duplicated 17 times and lost 14 times during the evolution of the elephant’s lineage. Hyraxes and manatees have LIF duplicates, but the p53 duplicates appear only in living and extinct elephants, which suggests that the LIF duplications happened earlier in evolution.

Elephants are closely related to large animals such as manatees (left), but also to smaller ones like hyraxes (right), aardvarks and armadillos. Elephants only began to develop their immense size about 30 million years ago.

Jim P. Reid, USFWS / Bjørn Christian Tørrissen

Lynch found that most duplicates of the LIF gene are pseudogenes—old, mutated, useless copies of genes that survive in the genome by chance. The exception, however, is the LIF6 gene sequence, which unlike the others has not accumulated random mutations, implying that natural selection is preserving it.

“We think that LIF6 is a refunctionalized pseudogene,” Lynch said. That is, the elephant LIF6 re-evolved into a functional gene from a pseudogene ancestor. Because it came back from the dead and plays a role in cell death, Lynch called it a “zombie gene.”

Although manatees and hyraxes also have extra copies of LIF, only modern and extinct elephants have LIF6, which suggests that it evolved only after the elephants branched away from those related species. And when Lynch’s group dated the origin of LIF6 by molecular clock methods, they found that the pseudogene regained a function about 30 million years ago, when the fossil record indicates that elephants were evolving large body sizes.

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“Refunctionalizing a pseudogene is not something that happens every day,” explained Stephen Stearns, an evolutionary biologist at Yale University, in an email to Quanta. Being able to show that it happened at roughly the same time that elephants evolved a large body, he wrote, “supports, but does not prove, that the refunctionalizing of the gene was a precondition for the evolution of large body size.”

Evolving protections against cancer would seem to be in the interest of all animals, so why don’t they all have a refunctionalized LIF6 gene? According to the researchers, it’s because this protection comes with risks. LIF6 suppresses cancer, but extra copies of LIF6 would kill the cell if they accidentally turned on. “There’s a bunch of toxic pseudogenes sitting there” in the genome, Lynch explained in an email. “If they get inappropriately expressed, it’s basically game over.”

There also appears to be a trade-off between cancer suppression mechanisms and fertility. A study published in 2009 suggested that LIF is critical for implantation of the embryo in the uterus. Because LIF activity is controlled by p53, LIF and p53 jointly regulate the efficiency of reproduction. When the same set of genes has two functions (such as reproduction and cancer suppression), it is possible that those functions will be in direct conflict—a phenomenon that geneticists call antagonistic pleiotropy.

The elephants may have solved the problem of antagonistic pleiotropy by duplicating p53 and LIF and splitting up those functions, according to Maley. “Some copies of p53 and LIF are doing what’s necessary for fertility, while other pairs of LIF and p53 are doing what’s necessary for cancer suppression,” he said. Maley speculated that the gene duplicates “allowed the elephants to get better at cancer suppression and still maintain their fertility, which would allow them to grow a larger body.” That hypothesis, however, still needs to be tested, he said.

Bats are not large animals, but some species live for decades. Scientists are investigating whether they have their own protective adaptations against cancer.

Ann Froschauer, USFWS

Evolving extra copies of p53 and LIF may have helped elephants overcome Peto’s paradox, but that can’t be the only solution: Other large animals like whales have only one copy of p53 and one version of LIF. Lynch and his team are currently exploring how whales and bats solve Peto’s paradox. Although not large-bodied, some bat species live up to 30 years, and the longer-lived ones might have evolved cancer suppression mechanisms that the shorter-lived ones lack.

Maley is also working on how whales solve Peto’s paradox. Even though whales don’t have extra copies of p53, he said, “we do think there has been a lot of selection and evolution on genes in the p53 pathway.” Maley believes that understanding how diverse large-bodied animals solve Peto’s paradox may have applications in human health. “That is the end goal,” he said. “The hope is that by seeing how evolution has found a way to prevent cancer, we could translate that into better cancer prevention in humans.”

“Every organism that evolved large body size probably has a different solution to Peto’s paradox,” Maley said. “There’s a bunch of discoveries that are just waiting for us out there in nature, where nature is showing us the way to prevent cancer.”

Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.

Just how colors Vision stumbled on the Animals

Animals live color. Wasps buzz with painted warnings. Birds shimmer their iridescent desires. Fish hide from predators with body colors that dapple like light across a rippling pond. And all this color on every one of these animals happened because other creatures could view it.

The normal world can be so showy, it’s no wonder boffins have been attracted to animal color for hundreds of years. Even now, the questions how pets see, create, and use color are among the most compelling in biology.

Before the last couple of years, they were additionally at the least partially unanswerable—because color scientists are only peoples, which means that they can’t begin to see the rich, vivid colors that other animals do. But now brand new technologies, like portable hyperspectral scanners and cameras tiny sufficient to match on a bird’s head, are assisting biologists see the unseen. And also as described in a new Science paper, it’s really a totally new world.

Visions of life

The basic principles: Photons strike a surface—a rock, a plant, another animal—and that area absorbs some photons, reflects others, refracts still others, all based on the molecular arrangement of pigments and structures. Some of these photons find their way into an animal’s eye, where specific cells transmit the signals of these photons toward animal’s brain, which decodes them as colors and forms.

Oahu is the mind that determines or perhaps a colorful thing is a distinct and interesting form, not the same as the photons through the trees, sand, sky, lake, an such like it received as well. If it is effective, it has to decide whether this colorful thing is food, a potential mate, or maybe a predator. “The biology of color is all about these complex cascades of activities,” says Richard Prum, an ornithologist at Yale University and co-author for the paper.

In the beginning, there was light and there is dark. Which, fundamental greyscale vision probably developed first, because pets that could anticipate the dawn or skitter far from a shadow are pets that live to breed. And very first eye-like structures—flat spots of photosensitive cells—probably did not resolve much more than that. It wasn’t sufficient. “The problem with making use of simply light and dark is that the information is quite noisy, and something problem which comes up is determining where one object stops and a different one begins. ” states Innes Cuthill, a behavioral ecologist within University of Bristol and coauthor regarding the new review.

Colors adds context. And context on a scene is an evolutionary benefit. So, just like with smart phones, better resolution and brighter colors became competitive enterprises. The quality bit, the area light-sensing cells developed over countless years right into a appropriate eye—first by recessing right into a cup, then a cavity, and eventually a fluid-filled spheroid capped having a lens. For color, look much deeper at those light-sensing cells. Wedged within their surfaces are proteins called opsins. Each time they get hit with a photon—a quantum little bit of light itself—they transduce that sign into an electrical zap toward rudimentary animal’s rudimentary brain. The first light/dark opsin mutated into spin-offs that may detect certain ranges of wavelengths. Colors vision was so essential it developed individually multiple times within the animal kingdom—in mollusks, arthropods, and vertebrates.

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In fact, primitive fish had four different opsins, to sense four spectra—red, green, blue, and ultraviolet light. That four-fold ability is known as tetrachromacy, and also the dinosaurs most likely had it. As they are the ancestors of today’s wild birds, many of them are tetrachromats, too.

But contemporary mammals don’t see things that way. That is most likely because early mammals had been little, nocturnal things that spent their first 100 million years running around at night, trying to save yourself from being eaten by tetrachromatic dinosaurs. “During that duration the complicated artistic system they inherited from their ancestors degraded,” states Prum. “We have clumsy, retrofitted form of color eyesight. Fishes, and wild birds, and many lizards visit a much richer globe than we do.”

In fact, many monkeys and apes are dichromats, and discover the world as greyish and somewhat red-hued. Boffins believe very early primates regained three-color vision because spotting fruit and immature leaves led to a far more healthy diet. But regardless of how much you love springtime of fall colors, the wildly varicolored world we humans are now living in now isn’t putting on a show for all of us. It’s mostly for pests and birds. “Flowering flowers of course have evolved to signal pollinators,” states Prum. “The proven fact that we find them gorgeous is incidental, and the undeniable fact that we can see them at all is because of an overlap in spectrums insects and wild birds can easily see and those we can see.”

Covered in color

And also as animals gained the ability to sense color, evolution kickstarted an hands competition in displays—hues and patterns that aided in survival became signifiers of ace baby-making skills. Almost every expression of color in the natural world came into being to signal, or obscure, a creature to something different.

For example, “aposematism” is color used as warning—the butterfly’s bright colors say “don’t consume me, you’ll receive ill.” “Crypsis” is color utilized as camouflage. Colors acts social purposes, too. Like, in mating. Did you know that feminine lions choose brunets? Or that paper wasps can recognize each other people’ faces? “Some wasps have small black colored spots that become karate belts, telling other wasps to not try to fight them,” claims Elizabeth Tibbetts, an entomologist at University of Michigan.

But pets display colors utilizing two completely different techniques. The very first is with pigments, colored substances produced by cells called chromatophores (in reptiles, seafood, and cephalopods), and melanocytes (in animals and wild birds). They absorb most wavelengths of light and mirror just a few, restricting both their range and brilliance. As an example, many animals cannot naturally produce red; they synthesize it from plant chemical substances called carotenoids.

Others means pets make color is by using nanoscale structures. Bugs, and, up to a smaller degree, birds, would be the masters of color-based structure. And compared to pigment, framework is fabulous. Structural coloration scatters light into vibrant, shimmering colors, like shimmering iridescent bib for a Broad-tailed hummingbird, and/or metallic carapace of a Golden scarab beetle. And experts aren’t quite yes why iridescence evolved. Most likely to signal mates, but still: Why?

Decoding the rainbow of life

Issue of iridescence is comparable to most questions boffins have actually about animal coloration. They understand what the colors do in broad strokes, but there’s till lots of nuance to tease away. This is certainly mostly because, until recently, these were restricted to seeing the normal world through peoples eyes. “If you ask issue, what’s this color for, you need to treat it the way in which animals see those colors,” claims Tim Caro, a wildlife biologist at UC Davis together with organizing force behind the new paper. (Speaking of mysteries, Caro recently figured out why zebras have stripes.)

Just take the peacock. “The male’s tail is breathtaking, plus it evolved to wow the feminine. But the feminine might be impressed in a different way than you or I,” Caro says. Humans have a tendency to gaze during the shimmering eyes during the tip of every tail feather; peahens typically consider the root of the feathers, where they put on the peacock’s rump. How does the peahen find the root of the feathers sexy? No one understands. But until scientists strapped towards the wild birds’ minds small cameras spun faraway from the cellular phone industry, they couldn’t also monitor the peahens’ gaze.

Another new technology: Advanced nanomaterials give researchers the ability to replicate the structures animals used to bend light into iridescent displays. By recreating those structures, researchers can figure out how genetically high priced they’re to make.

Likewise, new magnification practices have allowed researchers to check into an animal’s eye structure. You may have find out about how mantis shrimp never have three or four but a whopping 12 different color receptors, and how they see the globe in psychedelic hyperspectral saturation. This really isn’t quite real. Those color channels aren’t linked together—not like they truly are in other pets. The shrimp most likely aren’t seeing 12 various, overlapping color spectra. “We are usually planning perhaps those color receptors are increasingly being switched on or down by some other, non-color, signal,” claims Caro.

But perhaps the most important modern innovation in biological color scientific studies are getting all the various people from different procedures together. “There certainly are a lot of differing types of people working on color,” claims Caro. “Some behavioral biologists, some neurophysiologists, some anthropologists, some structural biologists, and so on.”

And these researchers are scattered around the world. He says the reason why he brought everybody else to Berlin is really so they might finally synthesize each one of these sub-disciplines together, and transfer to a wider understanding of color worldwide. The main technology in understanding animal color eyesight isn’t a camera or perhaps a nanotech surface. It’s an airplane. And/or internet.

Watch SpaceX Launch Its Second Rocket in 48 Hours

If Friday’s rocket livestream wasn’t enough for you, you’re in luck—this Sunday, SpaceX is set to launch its second Falcon 9 of the week. This time, the company is firing a shiny new rocket from California’s Vandenberg Air Force Base. It’s the fastest turnaround yet for two SpaceX launches, but if it’s going to launch as many satellites as it says, there are more rapid-fire liftoffs to come.

These two payloads weren’t originally planned as a double-whammy. A pneumatic valve pushed the BulgariaSat launch back from Monday, June 19. And after initially being delayed from October—then December, then April—today’s liftoff is actually a bit ahead of schedule. This launch delivers 10 more satellites to the fleet that telecommunications company Iridium is building in low Earth orbit. To get the new satellites situated just-so, the launch window is exact, scheduled for 1:25:14 pm Pacific time.

Roughly an hour after it lifts off from Space Launch Complex 4E, the Falcon 9 will dispense one satellite every 90 seconds. These newcomers will be tested for a few weeks before joining the rest of their brethren to beam voice and data information. After dispensing the satellites into orbit, the first stage of the Falcon 9, like a few before it), will land vertically on a drone barge in the Pacific Ocean, to be reused in later launches.

So far, Iridium has only contracted new, unused rockets from SpaceX to place its constellation of satellites. But they may soon get on board with Musk’s rocket reusability plan, if older rockets mean faster launches. Their 2010 agreement with SpaceX originally aimed to send around 70 satellites up by the end of 2017, and that the endpoint has now been delayed to 2018.

Despite the delays, the car-size satellites being launched today have come a long way since they were first trucked in pairs from Phoenix to Vandenberg. Today’s satellite delivery brings Iridium’s total up to 20, with six more SpaceX launches scheduled to deliver the remaining 55 satellites in the next year or so. If all goes well, the end of the day will mark two down, six to go, with precedent set for rapid launches to come.