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You are at:Home » Calculating the Likelihood of Intelligent Life in the Universe and Beyond: A New Theoretical Model
Calculating The Likelihood Of Intelligent Life In The Universe And
Science November 14, 2024

Calculating the Likelihood of Intelligent Life in the Universe and Beyond: A New Theoretical Model

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In 1961, American astrophysicist and astrobiologist Dr. Frank Drake multiplied several factors to estimate the number of intelligent civilizations in the Milky Way that could make their presence known to humans. I devised an equation. More than 60 years later, astrophysicists have created a different model that focuses instead on conditions created by the accelerating expansion of the universe and the amount of stars forming. This expansion is thought to be caused by dark energy, which makes up more than two-thirds of the universe.

Artistic impression of the multiverse. Image credit: Jaime Salcido / EAGLE collaboration.

“Understanding dark energy and its impact on our universe is one of the biggest challenges in cosmology and fundamental physics,” said Dr. Daniele Solini, a researcher at Durham University’s Institute for Computational Cosmology. .

“The parameters that govern our universe, such as the density of dark energy, may explain our own existence.”

Because stars are a prerequisite for the emergence of life as we know it, the team’s new model predicts the probability of intelligent life arising in our universe, and in a hypothetical multiverse scenario of different universes. could be used to estimate the

The new study does not attempt to calculate the absolute number of observers (i.e. intelligent life) in the universe, but instead calculates the relative probability that a randomly chosen observer will inhabit a universe with certain properties. will be considered.

It concludes that a typical observer would expect to experience significantly greater densities of dark energy than seen in our Universe. This suggests that its ingredients make it a rare and unusual case in the multiverse.

The approach presented in this paper involves calculating the rate at which ordinary matter is converted into stars for different dark energy densities throughout the history of the universe.

Models predict that this proportion would be about 27% in a universe where star formation is most efficient, compared to 23% in our universe.

This means that we do not live in a hypothetical universe where intelligent life has the highest probability of forming.

In other words, according to the model, the values ​​of dark energy density that we observe in the Universe do not maximize the potential for life.

“Surprisingly, we found that even fairly high dark energy densities can still coexist with life. This suggests that we may not be living in the most likely universe. ,” Dr. Solini said.

The model could help scientists understand how different densities of dark energy affect the structure of the universe and the conditions for life to develop there.

Dark energy causes the universe to expand faster, balancing the pull of gravity and creating a universe that is capable of both expansion and structure formation.

But for life to develop, there needs to be areas where matter can aggregate to form stars and planets, and conditions need to remain stable for billions of years to allow life to evolve.

Importantly, this study shows that the astrophysics of star formation and the evolution of the large-scale structure of the universe combine in subtle ways to determine the optimal value of dark energy density required for the generation of intelligent life. It suggests that.

“We will use this model to investigate the emergence of life across different universes and reinterpret some fundamental questions we ask ourselves about our own universe,” said Lucas Lombreiser, professor at the University of Geneva. It will be interesting to see if there is a need.”

of study Published in Royal Astronomical Society Monthly Notices.

_____

Daniele Solini others. 2024. Influence of the cosmological constant on past and future star formation. MNRAS 535 (2): 1449-1474;doi: 10.1093/mnras/stae2236

Source: www.sci.news

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