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Using machine learning to probe dark energy in the Universe

In conjunction with researchers at Istanbul Technical University, researchers from the University of Malta have recently completed two works related to investigating the evolution of dark energy using recently published measurements from the James Webb Space Telescope and other observatories.

This is the result of the “BridgingCosmology - Bridging early and late cosmological survey samples using machine learning” project, which is a collaboration of researchers from both institutions.

The main goal of the project is to utilise the increasingly applicable range of machine learning toolkits in order to boost the level of data extraction from observational measurements in the direction of probing the evolution and fundamental nature of dark energy.

Dark energy is responsible for the present accelerated expansion of the Universe. This has recently come into focus due to a growing disharmony between observational constraints on the present rate of cosmic expansion. The source of the statistical tension arises from the comparison of direct constraints on this value and presentations using early Universe measurements. This is increasingly becoming a central question in modern cosmology.

The BridgingCosmology project contributes to this open question in modern cosmology by giving a proof of principle of ways in which machine learning can be used to probe the nature of dark energy. One of the key results of the project has been the strengthening of the statistical evidence for a possible transition in dark energy, occurring at a redshift of 2. This may be sourced by a fundamental transition of the Universe from a false vacuum to a true one, among other possible sources. This would explain the disharmony in estimates of the expansion rate of the Universe.

Another key result of the project is the use of reconstruction techniques to parametrize the expansion evolution of the Universe using a combination of scalar fields with actions at different epochs in the expansion of the Universe.

The BridgingCosmology project is financed through the Xjenza Malta-TÜBÄ°TAK 2024 Joint Programme. For further information, the principal investigator Prof. Jackson Levi Said, Institute for Space Sciences and Astronomy, University of Malta.

References:

Akarsu, Ö, Caruana, M., Dialektopoulos, K. F., Escamilla, L. A., Kahya, E. O. and Levi Said, J. Hints of sign-changing scalar field energy density and a transient acceleration phase at from model-agnostic reconstructions. arXiv:2602.08928

Akarsu, Ö, Caruana, M., Dialektopoulos, K. F., Escamilla, L. A., Kahya, E. O. and Levi Said, J. Do equation of state parametrizations of dark energy faithfully capture the dynamics of the late universe?. arXiv:2604.12987