As humanity grapples with comprehending dark energy, the enigmatic force steering the universe’s rapid expansion, scientists are contemplating a futuristic notion: Can computers outperform us in this quest? Preliminary findings from a team leveraging artificial intelligence (AI) methodologies to deduce the impact of dark energy with unparalleled accuracy may hint at an affirmative response.
Led by Niall Jeffrey, a researcher at University College London, the team collaborated with the Dark Energy Survey group to construct a supercomputer simulation of the cosmos using measurements of visible and dark matter. While dark energy propels the universe outwards uniformly, dark matter, an elusive substance, eludes detection as it does not interact with light.
Subsequent to crafting this cosmic simulation, the team harnessed AI to extract a detailed universe map spanning the past seven billion years, illustrating the effects of dark energy. This dataset encompasses a remarkable 100 million galaxies sprawled across approximately 25% of the Southern Hemisphere sky. Without AI, achieving such a map from the initial three years’ observations of the Dark Energy Survey would have necessitated significantly more data. These outcomes corroborate the viability of certain cosmic evolution models when intertwined with dark energy dynamics, while eliminating others that may not hold true.
“By employing this AI approach to decipher insights from these data maps, we effectively doubled our precision in gauging dark energy,” remarked Jeffrey to Space.com. “Using conventional methods, you would require four times the data volume.”
To attain a comparable level of accuracy and comprehension regarding dark energy sans AI, Jeffrey elaborated, one would need to procure identical data thrice more from disparate sky patches, equivalent to mapping an additional 300 million galaxies.
Unraveling the Dark Energy Conundrum
Dark energy serves as a provisional term denoting the enigmatic force expediting the universe’s expansion, propelling remote galaxies away from the Milky Way and each other at an escalating pace over time.
The ongoing phase of “cosmic inflation” differs from the post-Big Bang universe’s genesis; it appears to have commenced subsequent to the initial expansion grinding to a halt.
Imagine nudging a child’s swing once. Following that initial impetus, the swing decelerates, but instead of halting, it unexpectedly resumes motion without further intervention. Strikingly, the swing not only recommences movement but also accelerates, ascending to greater heights and velocities. Analogously, the universe expands outward akin to a swing’s unidirectional motion.
One would naturally seek to fathom the source of this additional “push” instigating acceleration. Scientists harbor a similar curiosity regarding dark energy’s nature and its apparent augmentation of cosmic expansion.
This intrigue intensifies considering that dark energy constitutes roughly 70% of the universe’s energy and matter budget, despite its enigmatic essence. When factoring in dark matter—comprising 25% of this budget and composed of non-atomic entities unlike familiar stellar, planetary, lunar, and biological constituents—merely 5% of the entire universe is visibly accessible.
“We lack a comprehensive understanding of dark energy; it remains a perplexing enigma. It’s a term we employ to describe an additional universal force propelling spatial entities apart as the universe’s expansion accelerates,” elucidated Jeffery. “The Dark Energy Survey endeavors to elucidate the essence of dark energy. Our primary objective is to ascertain whether it embodies a cosmological constant.”
The cosmological constant, symbolized by the Greek letter lambda, boasts a rich cosmological legacy. Initially introduced by Albert Einstein to reconcile his groundbreaking 1915 gravitational theory, general relativity, with a “static universe,” this concept encountered a challenge when Edwin Hubble’s observations revealed the universe’s expanding—not static—nature. Einstein discarded the cosmological constant, purportedly deeming it his “greatest blunder.”
Nonetheless, in 1998, two distinct astronomical teams observed distant supernovas, unveiling not just the universe’s expansion but its acceleration. Dark energy emerged as a plausible explanation for this accelerating force, reviving the cosmological constant from theoretical oblivion.
Presently, the cosmological constant lambda epitomizes the universe’s background vacuum energy, akin to an “anti-gravity” influence propelling its expansion. Currently, the cosmological constant stands as the primary substantiation for dark energy.
“Our findings, juxtaposed with conventional methods employing the same dark matter map, are finely tuned, affirming consistency with dark energy being explicable by a cosmological constant,” Jeffrey affirmed. “Thus, we have refuted certain physical models positing dark energy.”
Nonetheless, the enigma persists:
The Cosmic Conundrum of the Cosmological Constant
The cosmological constant remains a formidable quandary for scientists.
Observations of distant celestial entities receding from Earth suggest a lambda value 120 orders of magnitude smaller than quantum physics’ projections. Consequently, the cosmological constant has earned the dubious distinction of being labeled “the worst theoretical prediction in the history of physics” by some scholars.
Jeffrey underscores the research team’s satisfaction with these outcomes while acknowledging the unresolved discrepancy between theory and observation.
“The disparity is staggering, signifying a flaw in our quantum mechanical framework,” he elaborated. “While these outcomes illuminate the universe’s expansion dynamics and gravitational interactions, they do not bridge the chasm between theory and empirical data.”
While affirming general relativity as the apt gravitational framework, the team’s findings do not preclude alternative gravity models that could elucidate dark energy’s observed effects.
“Superficially, our results align with general relativity. However, they offer leeway for alternative theories explicating dark energy or gravitational mechanisms,” Jeffrey noted.
This study underscores the efficacy of utilizing AI to scrutinize simulated universe models, discern crucial patterns imperceptible to humans, and pursue vital clues regarding dark energy.
“Through these methodologies, we glean insights equivalent to tripling our data volume—a remarkable feat,” Jeffrey remarked.
The UCL researcher underscores the imperative of employing a specialized AI variant adept at discerning cosmic patterns for such investigations. Unlike querying ChatGPT for responses, where gaps may be filled with speculative content, scientific-AI integration necessitates precision and reliability.
“ChatGPT’s limitation lies in fabricating responses when confronted with unknowns. What we seek is clarity on known and unknown realms. Hence, substantial advancements are indispensable for reliable outcomes in scientific-AI amalgamation,” he emphasized.
Anticipated data influx from the Dark Energy Survey spanning six additional years, coupled with inputs from the Euclid telescope launched in July 2023, promises enhanced insights into the universe’s macroscopic structures. These advancements are poised to refine cosmological models, fostering more intricate universe simulations that could potentially unravel the dark energy enigma.
“Our simulated universes exhibit a striking realism, surpassing conventional methodologies. Precision aside, it’s about instilling faith in these outcomes and deeming them dependable,” Jeffrey concluded.
The team’s research is accessible as a preprint on the arXiv paper repository.
