A pretty futuristic question has begun to cross scientists’ minds as they attempt to comprehend dark energy, the mysterious element responsible for the universe’s rapid expansion. Are computers capable of doing better? An solution may be suggested by preliminary findings from a team that employed artificial intelligence (AI) tools to deduce the influence of dark energy with unparalleled precision: Sure.
Using measurements of visible and dark matter, the team, under the direction of scientist Niall Jeffrey of University College, London, collaborated with the Dark Energy Survey collaboration to build a supercomputer simulation of the universe. Dark matter is a mystery form of substance that is unseen because it does not interact with light, while dark energy helps push the universe outward in all directions.
Following the creation of the cosmic simulation, the team used artificial intelligence (AI) to extract an accurate map of the cosmos that shows the activities of dark energy over the last seven billion years. The data that the researchers came up with shows an astounding 100 million galaxies spread over about 25% of the sky in the Southern Hemisphere of Earth. This data, which includes the first three years of observations from the Dark Energy Survey, would have required far more observations to create such a map in the absence of AI. The results serve to validate which theories of cosmic development are possible when combined with dark energy dynamics, while ruling out some that are not.
According to Jeffrey, employing this AI technology doubled our accuracy in measuring dark energy as compared to traditional techniques for deriving knowledge about dark energy from these data maps, as reported by Space.com. “Using the conventional method would require four times as much data.
Jeffrey mentioned that gathering the same information three more times in other sky regions would be necessary to obtain this degree of accuracy and comprehension of dark energy without the use of artificial intelligence. That’s the same as mapping an additional 300 million galaxies.
The issue with dark energy
The unexplained force that accelerates the expansion of the universe and gradually pushes distant galaxies away from the Milky Way and from one another is known by the loose term “dark energy.”
The current epoch of “cosmic inflation” appears to have begun after that initial phase of halting after the Big Bang, and is distinct from that which occurred after the universe was born.
Consider pushing a child on a swing just once. After that initial power is applied, the swing slows down, but rather of stopping without your further effort, it abruptly starts to move again. Even while that would be unusual in and of itself, there’s more. Upon abruptly resuming motion, the swing would also pick up pace, scaling ever-higher heights and distances. This is analogous to the phenomena observed in space, where the cosmos is expanding instead of oscillating in a bidirectional manner.
I bet you would be itching to know what produced the acceleration and that extra “push”. Whatever dark energy is and how it seems to have added an extra cosmic push on the very fabric of space, scientists feel the same way.
This need is further exacerbated by the fact that, although its nature is unknown, dark energy comprises around 70% of the universe’s budget of matter and energy. We truly only have visible access to around 5 percent of the universe when we include dark matter, which makes up 25% of this budget and cannot be composed of atoms we are familiar with, such as those that make up stars, planets, moons, neutron stars, human bodies, and the cat next door.
“Dark energy is one of those strange phenomena about which we really don’t know anything.” It’s just a term we use to explain an additional force at work in the world that’s pushing everything apart as it expands faster and faster, according to Jeffrey. The goal of the Dark Energy Survey is to define dark energy. Our main goal is to determine whether or not it is a cosmological constant.
For cosmologists, the cosmological constant—represented by the Greek letter lambda—has a long and illustrious past. First established in 1915, Albert Einstein used it to ensure that the equations underlying his breakthrough theory of gravity, general relativity, supported the idea of a “static universe.”
However, this theory was called into question when Edwin Hubble’s observations of far-off galaxies revealed that the cosmos is expanding and not static. Throwing the cosmological constant in the trash, Einstein is said to have called it his “greatest blunder.”
But in 1998, two different groups of astronomers detected distant supernovas, leading them to conclude that not only was the universe expanding, but that it was also growing faster than before. The acceleration’s cause was attributed to dark energy, and the cosmological constant was extracted from the realm of hypothesis.
The underlying vacuum energy of the cosmos is now represented by the cosmological constant lambda, which functions practically as a “anti-gravity” force propelling the universe’s expansion. The most compelling evidence for dark energy at this time is the cosmological constant.
According to Jeffrey, their findings are in close agreement with the explanation of dark energy by a cosmological constant, since they were compared to the application of conventional methods with the identical dark matter map. With this conclusion, they have eliminated a few physical dark energy hypotheses.
However, this does not imply that the puzzles surrounding dark energy or the headache that the cosmological constant symbolizes are resolved.
The most disastrous forecast in the history of physics
For scientists, the cosmological constant continues to be a major challenge.
This is because far-off, receding celestial object measurements point to a lambda value 120 orders of magnitude (10 followed by 119 zeroes) less than what quantum theory predicts. The cosmological constant has been called “the worst theoretical prediction in the history of physics” by some scientists, and with good reason.
As delighted as the team is with these findings, Jeffrey is apparent that current research is unable to account for the enormous discrepancy between theory and fact.
He went on, That difference is simply too great, and it indicates that their theory of quantum mechanics is incorrect. These findings can help them determine what kinds of mathematical formulas or scientific theories best explain how the cosmos grows and how gravity pulls everything made of matter together.
Furthermore, even while the team’s findings point to general relativity as the best explanation for gravity, they do not rule out the possibility of alternative gravity models that could account for the effects of dark energy that have been observed.
On the surface, these findings support general relativity, but according to Jeffrey, there is still a lot of space for interpretation as it still leaves up the possibility of alternative theories explaining the operation of dark energy or gravity.
This work shows the value of applying AI to evaluate universe-simulated models, identify significant patterns that humans would overlook, and subsequently seek for significant dark energy hints.
It’s very surprising that we can obtain results with these techniques that would have required three more data acquisitions, according to Jeffrey.
The researcher from UCL notes that these kinds of investigations will require a very specific kind of AI that is skilled at identifying patterns in the cosmos. Cosmologists won’t be able to ask their AI systems to run simulations based on universes in the same way that users may ask queries of ChatGPT and get responses.
He claimed that the issue with ChatGPT is that it will simply make stuff up if it doesn’t know something. They are interested in knowing when they are knowledgeable and when they are not. For those interested in working with a combination of science and AI, he believes there is still much room for improvement in order to provide consistent outcomes.
The Dark Energy Survey will provide six more years of data in the future, which when paired with observations from the July 2023-launched Euclid telescope should yield a wealth of additional information regarding the large-scale architecture of the cosmos. This should assist researchers in honing their cosmological models and producing increasingly more accurate universe simulations, which may ultimately enable them to solve the mystery of dark energy.
As a result, Jeffrey concluded, “the simulated universes we generate can be more realistic than what we’ve been able to do with our old-fashioned methods.” It goes beyond accuracy to include confidence in these findings and their dependability.
The preprint of the team’s work can be found on the publication repository arXiv.
