Computer simulations have become so accurate that cosmologists can now use them to study dark matter, supermassive black holes and other mysteries of the real evolving cosmos.
The evolution of magnetic fields in a 10-Megaparsec section of the IllustrisTNG universe simulation. Regions of low magnetic energy appear in blue and purple, while orange and white correspond to more magnetically energetic regions inside dark matter halos and galaxies.
In the early 2000s, a small community of coder-cosmologists set out to simulate the 14-billion-year history of the universe on a supercomputer. They aimed to create a proxy of the cosmos, a Cliffs Notes version in computer code that could run in months instead of giga-years, to serve as a laboratory for studying the real universe.
The simulations failed spectacularly. Like mutant cells in a petri dish, mock galaxies grew all wrong, becoming excessively starry blobs instead of gently rotating spirals. When the researchers programmed in supermassive black holes at the centers of galaxies, the black holes either turned those galaxies into donuts or drifted out from galactic centers like monsters on the prowl.
But recently, the scientists seem to have begun to master the science and art of cosmos creation. They are applying the laws of physics to a smooth, hot fluid of (simulated) matter, as existed in the infant universe, and seeing the fluid evolve into spiral galaxies and galaxy clusters like those in the cosmos today.
,
,
Tiziana Di Matteo, a professor of physics at Carnegie Mellon University, co-developed the MassiveBlack-II and BlueTides cosmological simulations.
Carnegie Mellon University
“I was like, wow, I can’t believe it!” said Tiziana Di Matteo, a numerical cosmologist at Carnegie Mellon University, about seeing realistic spiral galaxies form for the first time in 2015 in the initial run of BlueTides, one of several major ongoing simulation series. “You kind of surprise yourself, because it’s just a bunch of lines of code, right?”
With the leap in mock-universe verisimilitude, researchers are now using their simulations as laboratories. After each run, they can peer into their codes and figure out how and why certain features of their simulated cosmos arise, potentially also explaining what’s going on in reality. The newly functional proxies have inspired explanations and hypotheses about the 84 percent of matter that’s invisible — the long-sought “dark matter” that seemingly engulfs galaxies. Formerly puzzling telescope observations about real galaxies that raised questions about the standard dark matter hypothesis are being explained in the state-of-the-art facsimiles.
The simulations have also granted researchers such as Di Matteo virtual access to the supermassive black holes that anchor the centers of galaxies, whose formation in the early universe remains mysterious. “Now we are in an exciting place where we can actually use these models to make completely new predictions,” she said.
Black Hole Engines and Superbubble Shockwaves
Until about 15 years ago, most cosmological simulations didn’t even attempt to form realistic galaxies. They modeled only dark matter, which in the standard hypothesis interacts only gravitationally, making it much easier to code than the complicated atomic stuff we see.
The dark-matter-only simulations found that roundish “halos” of invisible matter spontaneously formed with the right sizes and shapes to potentially cradle visible galaxies within them. Volker Springel, a leading coder-cosmologist at Heidelberg University in Germany, said, “These calculations were really instrumental to establish that the now-standard cosmological model, despite its two strange components — the dark matter and the dark energy — is actually a pretty promising prediction of what’s going on.”
Researchers then started adding visible matter into their codes, stepping up the difficulty astronomically. Unlike dark matter halos, interacting atoms evolve complexly as the universe unfolds, giving rise to fantastic objects like stars and supernovas. Unable to code the physics in full, coders had to simplify and omit. Every team took a different approach to this abridgement, picking and programming what they saw as the key astrophysics.
Then, in 2012, a study by Cecilia Scannapieco of the Leibniz Institute for Astrophysics in Potsdam gave the field a wake-up call. “She convinced a bunch of people to run the same galaxy with all their codes,” said James Wadsley of McMaster University in Canada, who participated. “And everyone got it wrong.” All their galaxies looked different, and “everyone made too many stars.”
,
,
Henize 70 is a superbubble of hot expanding gas about 300 light-years across that is located within the Large Magellanic Cloud, a satellite of the Milky Way galaxy.
FORS Team, 8.2-meter VLT, ESO
Scannapieco’s study was both “embarrassing,” Wadsley said, and hugely motivational: “That’s when people doubled down and realized they needed black holes, and they needed the supernovae to work better” in order to create credible galaxies. In real galaxies, he and others explained, star production is diminishing. As the galaxies run low on fuel, their lights are burning out and not being replaced. But in the simulations, Wadsley said, late-stage galaxies were “still making stars like crazy,” because gas wasn’t getting kicked out.
The first of the two critical updates that have fixed the problem in the latest generation of simulations is the addition of supermassive black holes at spiral galaxies’ centers. These immeasurably dense, bottomless pits in the space-time fabric, some weighing more than a billion suns, act as fuel-burning engines, messily eating surrounding stars, gas and dust and spewing the debris outward in lightsaber-like beams called jets. They’re the main reason present-day spiral galaxies form fewer stars than they used to.
The other new key ingredient is supernovas — and the “superbubbles” formed from the combined shockwaves of hundreds of supernovas exploding in quick succession. In a superbubble, “a small galaxy over a few million years could blow itself apart,” said Wadsley, who integrated superbubbles into a code called GASOLINE2 in 2015.
“They’re very kind of crazy extreme objects.” They occur because stars tend to live and die in clusters, forming by the hundreds of thousands as giant gas clouds collapse and later going supernova within about a million years of one another. Superbubbles sweep whole areas or even entire small galaxies clean of gas and dust, curbing star formation and helping to stir the pushed-out matter before it later recollapses. Their inclusion made small simulated galaxies much more realistic.
,
,
Jillian Bellovary, a numerical cosmologist at Queensborough Community College and the American Museum of Natural History in New York, put black holes into the GASOLINE simulation code.
H.N. James
Jillian Bellovary, a wry young numerical cosmologist at Queensborough Community College and the American Museum of Natural History in New York, coded some of the first black holes, putting them into GASOLINE in 2008. Skipping or simplifying tons of physics, she programmed an equation dictating how much gas the black hole should consume as a function of the gas’s density and temperature, and a second equation telling the black hole how much energy to release. Others later built on Bellovary’s work, most importantly by figuring out how to keep black holes anchored at the centers of mock galaxies, while stopping them from blowing out so much gas that they’d form galactic donuts.
Simulating all this physics for hundreds of thousands of galaxies at once takes immense computing power and cleverness. Modern supercomputers, having essentially maxed out the number of transistors they can pack upon a single chip, have expanded outward across as many as 100,000 parallel cores that crunch numbers in concert.
Coders have had to figure out how to divvy up the cores — not an easy task when some parts of a simulated universe evolve quickly and complexly, while little happens elsewhere, and then conditions can switch on a dime. Researchers have found ways of dealing with this huge dynamic range with algorithms that adaptively allocate computer resources according to need.
They’ve also fought and won a variety of logistical battles. For instance, “If you have two black holes eating the same gas,” Bellovary said, and they’re “on two different processors of the supercomputer, how do you have the black holes not eat the same particle?” Parallel processors “have to talk to each other,” she said.
Saving Dark Matter
The simulations finally work well enough to be used for science. With BlueTides, Di Matteo and collaborators are focusing on galaxy formation during the universe’s first 600 million years. Somehow, supermassive black holes wound up at the centers of dark matter halos during that period and helped pull rotating skirts of visible gas and dust around themselves. What isn’t known is how they got so big so fast. One possibility, as witnessed in BlueTides, is that supermassive black holes spontaneously formed from the gravitational collapse of gargantuan gas clouds in over-dense patches of the infant universe.
“We’ve used the BlueTides simulations to actually predict what this first population of galaxies and black holes is like,” Di Matteo said. In the simulations, they see pickle-shaped proto-galaxies and miniature spirals taking shape around the newborn supermassive black holes. What future telescopes (including the James Webb Space Telescope, set to launch in 2020) observe as they peer deep into space and back in time to the birth of galaxies will in turn test the equations that went into the code.
Another leader in this back-and-forth game is Phil Hopkins, a professor at the California Institute of Technology. His code, FIRE, simulates relatively small volumes of the cosmos at high resolution. Hopkins “has pushed the resolution in a way that not many other people have,” Wadsley said. “His galaxies look very good.” Hopkins and his team have created some of the most realistic small galaxies, like the “dwarf galaxy” satellites that orbit the Milky Way.
,
Source: Quantamagazine