by As people struggle to understand dark energy, the mysterious force driving the accelerated expansion of the universe, scientists have begun to think of something futuristic. Can computers be better? Well, initial results from a team that used artificial intelligence (AI) techniques to infer dark energy’s influence with unmatched precision may suggest an answer: Yes.
The team, led by University College London scientist Niall Jeffrey, worked in collaboration with the Dark Energy Survey to use measurements of visible and dark matter to create a supercomputer simulation of the universe. Although dark energy helps push the universe out in all directions, dark matter is a mysterious type of matter that remains invisible because it does not interact with light.
After creating the cosmic simulation, the team employed AI to draw a precise map of the universe covering the last seven billion years and showing the actions of dark energy. The team’s resulting data represents 100 million galaxies across about 25% of Earth’s Southern Hemisphere sky. Without AI, many more observations would be needed to create such a map using this data, which represents the first three years of observations from the Dark Energy Survey. The results help to validate the models of cosmic evolution that are viable when combined with dark energy dynamics, while eliminating others that are not.
“Compared to using old-fashioned methods to learn about dark energy from these data maps, using this AI approach ended up doubling our precision in measuring dark energy,” said Space.com’s Jeffrey. “You’d need four times as much data using the standard method.
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“If you wanted to get this level of accuracy and understanding of dark energy without AI,” said Jeffrey, “you would have to collect the same data three times more in different patches of the sky. This is equivalent to mapping another 300. million galaxies.”
The problem with dark energy
Dark energy is a kind of holder name for the mysterious force that accelerates the expansion of the universe, pushing distant galaxies away from the Milky Way, and away from each other, faster and faster over time.
The current period of “cosmic inflation” is separate from the period that followed the birth of the universe after the Big Bang; it seems to have started after that initial expansion had slowed to a halt.
Imagine giving a child one push on a swing. The pendulum slows down after adding that initial force, but instead of coming to a stop, without you pushing again, the pendulum suddenly starts moving again. That would be strange enough in itself, but there is actually more to it. The swing also began to accelerate after the sudden resumption of movement, reaching ever-increasing heights and speeds. This is similar to what is happening in space, with the globe bubbling away instead of a pendulum moving back and forth.
You would probably like to understand what added that extra pressure and caused the acceleration. Scientists feel the same way about whatever dark energy is involved, and how it appears to have exerted extra cosmic pressure on the fabric of space.
This desire is exacerbated by the fact that dark energy is responsible for about 70% of the energy and matter budget of the universe, although we do not know what it is. When we take into account dark matter, which is 25% of this budget and cannot be made from atoms that we are familiar with — those that make up stars, planets, moons, neutron stars, our bodies and a cat next door — only us. in fact about 5% of the entire universe is visible.
“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’s pushing everything apart as it that the expansion of the universe continues to accelerate,” Jeffery 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 cosmological constant?”
The cosmological constant, represented by the Greek letter lambda, has a storied history for cosmologists. Albert Einstein first introduced it to ensure that the equations of his revolutionary 1915 theory of gravity, general relativity, were supported by what was called a “static universe.”
However, this concept was challenged when Edwin Hubble’s observations of distant galaxies showed that the universe is expanding and so on. no static. Einstein threw the cosmological constant into the scientific dustbin, allegedly describing it as “the biggest mistake”.
However, in 1998, two separate teams of astronomers observed a distant supernova to discover that not only was the universe expanding, but that it appeared to be doing so at an accelerating rate. Dark energy was proposed to explain the force behind this acceleration, and the cosmological constant was fished out of the hypothetical dustbin.
Now, the cosmological constant lambda is the background vacuum energy of the universe, acting almost like an “anti-gravity” force driving its expansion. So far, the main evidence for dark energy is the cosmological constant.
“Our results, compared using standard methods with this same dark matter map, have been rigorously concluded, and we found that this is still consistent with dark energy being explained by a cosmological constant,” said Jeffrey. “So we have ruled out some physical models of dark energy with this result.”
This does not mean that the mystery of dark energy – or the headache that represents the cosmological constant – is relieved, however.
‘The worst prediction in the history of physics’
The cosmological constant still poses a huge problem for scientists.
That is because observations of distant celestial objects indicate that the value of lambda is 120 orders of magnitude (followed by 10 and 119 zeros) less than predicted by quantum physics. It is with good reason that some scientists have described the cosmological constant as “the worst theoretical prediction in the history of physics”.
Jeffrey makes it clear: As happy as the team is with these results, this research still can’t explain the huge gap between theory and observation.
“That difference is too big, and it tells us that our quantum mechanical theory is wrong,” he continued. “These results can tell us what kind of equations or what kind of physical models describe the way our Universe expands and how gravity works, pulling everything made up of matter in the universe together.”
Also, while the team’s results suggest that general relativity is the correct prescription for gravity, it cannot rule out other possible gravity models that could explain the observed effects of dark energy.
“Therefore, just looking at these results in isolation is consistent with general relativity – but still, there is a lot of room because it also allows for other theories of how dark energy or gravity works as well,” Jeffrey said.
This research demonstrates the utility of using AI to evaluate simulation models of the universe, pick out important patterns that humans may have missed, and thus look for important dark energy clues.
“Using these techniques, we can get results as if we had that data three times more – that’s amazing,” Jeffrey said.
The UCL researcher points out that it will take a very specific form of AI that is well-trained in seeing patterns in the universe to carry out these studies. Cosmologists will be able to simply feed globe-based simulations to their AI systems as questions can be entered into ChatGPT and results can be expected.
“The problem with ChatGPT is that if it doesn’t know something, it will make it up,” he said. “What we want to know is when we know something and when we don’t know something. So I think a lot of growth is still needed so that people can they are interested in the work that combines science and AI to get reliable results.”
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Another six years of data are still to come from the Dark Energy Survey, which, together with observations from the Euclid telescope launched in July 2023, should provide much more information about the large-scale structures of the universe. This should help scientists refine their cosmological models and create more accurate simulations of the universe, which may ultimately provide answers to the dark energy puzzle.
“It means that the simulated universes we generate are so realistic; in some sense, they can be more realistic than what we managed to do with our old-fashioned methods,” Jeffrey concluded. “It’s not only about accuracy, but I believe in these results and think they are reliable.”
The team’s research is available as a preprint on the arXiv paper repository.
