As humans struggle to understand dark energy, the mysterious force driving the universe’s rapid expansion, scientists have begun to think about the future instead. Can computers do any better? Well, preliminary results from a team that has used artificial intelligence (AI) techniques to estimate the influence of dark energy with unprecedented precision may suggest the answer: yes.
The team, led by University College London scientist Neil Jeffery, worked in collaboration with the Dark Energy Survey to use measurements of visible matter and dark matter to create a supercomputer simulation of the universe. While dark energy helps push the universe outward in all directions, dark matter is a mysterious form of matter that remains invisible because it does not interact with light.
After creating a cosmological simulation, the team then used AI to produce an accurate map of the universe spanning the past seven billion years and showing the functions of dark energy. The team’s resulting data represent 100 million galaxies across about 25 percent of Earth’s southern hemisphere sky. Without AI, creating such a map using this data, which represents observations from the first three years of the Dark Energy Survey, would require many more observations. The results help confirm which models of cosmic evolution are viable when combined with dark energy dynamics, while ruling out others that may not be.
“Compared to using old-fashioned methods to learn about dark energy from these data maps, using this AI approach doubles our accuracy in measuring dark energy,” Jeffrey told Space.com. ” “You would need four times as much data using the standard method.
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“If you want to achieve this level of accuracy and understanding of dark energy without AI,” Jeffrey added, “you’d have to collect the same data three times in different patches of the sky. That would equate to mapping another 300. million galaxies.”
The dark energy problem
Dark energy is a placeholder name for the mysterious force that accelerates the expansion of the universe, pushes distant galaxies away from the Milky Way, and grows faster and faster together over time.
The current period of “cosmic inflation” is distinct from that which occurred after the birth of the universe after the Big Bang. It seems to have started after the initial expansion had stopped.
Imagine giving a baby a single push on a swing. After adding this initial force, the swing slows down, but instead of stopping, without you pushing again, the swing suddenly starts moving again. That would be weird enough in itself, but there’s actually more. After suddenly resuming the motion, the swing will also begin to accelerate as it reaches ever-increasing heights and speeds. This is similar to what is happening in space, the bubble of the universe is swinging back and forth outwards instead of swinging.
You may be quite anxious to understand what added that extra “push” and caused the acceleration. Scientists feel the same way about whatever dark energy is, and it seems to add an extra cosmic push to the very fabric of space.
This desire is fueled by the fact that dark energy accounts for about 70 percent of the universe’s energy and matter budget, even though we don’t know what it is. When factoring in dark matter, which makes up 25 percent of that budget and can’t be made from the atoms we’re familiar with—the ones that make up stars, planets, the moon, neutron stars, our bodies, and the cat next door— We only really have visible access to about 5% of the entire universe.
“We don’t really understand what dark energy is; it’s one of those weird things. It’s just a word we use to describe a kind of extra force in the universe that binds everything together. away because the expansion of the universe is accelerating,” Jeffrey said. “The Dark Energy Survey is trying to understand what dark energy is. The main thing we’re trying to do is ask the question: Is it a cosmic constant?”
The cosmological constant, represented by the Greek letter lambda, has a storied history for cosmologists. Albert Einstein first introduced it in his 1915 revolutionary theory of gravity to ensure the equality of gravity, general relativity, supported what he called a “static universe”.
This notion was challenged, however, when observations of distant galaxies by Edwin Hubble showed that the universe was expanding and thus no Static Einstein threw the cosmological constant into the scientific dustbin, reportedly calling it his “biggest mistake”.
However, in 1998, two separate teams of astronomers observed distant supernovae to discover that the universe was not only expanding, but that it appeared to be doing so at an accelerated rate. Dark energy was invented as the explanation for the force behind this acceleration, and the cosmological constant was kicked out of the hypothetical dustbin.
Now, the cosmological constant lambda represents the background space energy of the universe, acting almost like an “antigravity” force driving its expansion. So far, the cosmic constant is the best evidence for dark energy.
“Our results, compared to using standard methods with the same dark matter map, are robust, and we find that it is still consistent with the dark energy being explained,” Jeffrey said. Cosmic constancy is done.” “So we’ve ruled out some physical models of dark energy with this result.”
However, this does not mean that the mystery of dark energy—or the headache that the cosmic constant represents—is solved.
‘The worst prediction in the history of physics’
The cosmological constant still remains a huge problem for scientists.
This is because observations of distant, receding celestial objects show lambda values 120 orders of magnitude lower (10 followed by 119 zeros) than predicted by quantum physics. It is for good reason that some scientists have described the cosmological constant as “the worst theoretical prediction in the history of physics.”
Jeffrey is clear: As pleased as the team is with these results, the research still cannot explain the large gap between theory and observation.
“This discrepancy is huge, and it tells us that our quantum mechanical theory is wrong,” he continued. “What these results can tell us is what kind of equations or what kind of physical models describe how our universe expands and how gravity works, pulling together everything that contains matter in the universe. “
Also, while the team’s results suggest that general relativity is the correct prescription for gravity, it cannot rule out other possible models of gravity that could explain the observed effects of dark energy.
“On the face of it, just looking at these results is consistent with general relativity — but still, there’s a lot of room for it to allow for other theories about how dark energy or gravity might work,” Jeffrey said. “Yes,” said Jeffrey.
The research demonstrates the utility of using AI to estimate synthetic models of the universe, picking out key patterns that humans can miss, and thus looking for important clues to dark energy.
“Using these techniques, we can get results that look like we got that data three times over — that’s pretty amazing,” Jeffery said.
It will take a very specific form of AI that is well-trained in spotting patterns in the universe to carry out these studies, the UCL researcher said. Cosmologists won’t just be able to feed universe-based simulations into their AI systems like one can plug queries into ChatGPT and expect results.
“The problem with ChatGPT is that if it doesn’t know something, it will just make it up,” he said. “What do we want to know when we know something and when we don’t know something. So I think there’s still a lot of development that needs to be done so that people interested in working with science and AI can get reliable results. can.”
Another six years of data from the Dark Energy Survey, which, combined with observations from the Euclid telescope, launched in July 2023, will provide much more information about the large-scale structure of the universe. This should help scientists improve their cosmological models and create even more accurate simulations of the universe, which could eventually lead them to answers to the dark energy puzzle.
“This means that the simulated universes we create are very realistic; in some ways, they can be more realistic than we’ve been able to do with our old-fashioned methods,” Jeffery concludes. “It’s not just about accuracy, it’s about believing in those results and thinking they’re reliable.”
The team’s research paper is available as a preprint on the arXiv repository.