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The Darkish Vitality Survey has enhanced our understanding of the Universe, doubling the precision of darkish power measurements by means of AI and simulation strategies, and providing insights into the Universe’s construction and the potential want for brand new cosmological fashions. Credit score: SciTechDaily.com
A UCL-led analysis group has used synthetic intelligence (AI) strategies to deduce the affect and properties of darkish power extra exactly from a map of darkish and visual matter within the Universe protecting the final seven billion years.
The research, carried out by the Darkish Vitality Survey collaboration, doubled the precision at which key traits of the Universe, together with the general density of dark energy, might be inferred from the map.
This elevated precision permits researchers to rule out fashions of the Universe that may beforehand have been conceivable.
Advances in Cosmic Understanding
Darkish power is the mysterious power that’s accelerating the Universe’s enlargement and is believed to make up about 70% of the content material of the Universe (with darkish matter, invisible stuff whose gravity pulls galaxies, making up 25%, and regular matter simply 5%).
Lead creator Dr. Niall Jeffrey (UCL Physics & Astronomy) mentioned: “Utilizing AI to study from computer-simulated universes, we elevated the precision of our estimates of key properties of the Universe by an element of two.
“To attain this enchancment with out these novel strategies, we would wish 4 instances the quantity of knowledge. This may be equal to mapping one other 300 million galaxies.”
Co-author Dr. Lorne Whiteway (UCL Physics & Astronomy) mentioned: “Our findings are according to the present greatest prediction of darkish power as a ‘cosmological fixed’ whose worth doesn’t fluctuate in area or time. Nonetheless, additionally they permit flexibility for a unique clarification to be appropriate. As an example, it nonetheless might be that our idea of gravity is mistaken.”
A matter map derived from one of many simulated universes. The lightest areas of the map present the areas the place darkish matter is most dense. These correspond to superclusters of galaxies. The darkish, nearly black patches are cosmic voids, the massive empty areas in between clusters of galaxies. Credit score: Niall Jeffrey et al
Refining Cosmological Fashions
According to earlier evaluation of the Darkish Vitality Survey map, first revealed in 2021, the findings counsel that matter within the Universe is extra easily unfold out – much less lumpy – than Einstein’s idea of normal relativity would predict. Nonetheless, the discrepancy was much less vital for this research in comparison with the sooner evaluation, because the error bars had been bigger.
The Darkish Vitality Survey map was obtained by means of a way referred to as weak gravitational lensing – that’s, seeing how gentle from distant galaxies has been bent by the gravity of intervening matter on its strategy to Earth.
The collaboration analyzed distortions within the shapes of 100 million galaxies to deduce the distribution of all matter, each darkish and visual, within the foreground of these galaxies. The ensuing map coated 1 / 4 of the sky within the Southern Hemisphere.
For the brand new research, researchers used UK government-funded supercomputers to run simulations of various universes based mostly on the information from the Darkish Vitality Survey matter map. Every simulation had a unique mathematical mannequin of the universe underpinning it.
The researchers created matter maps from every of those simulations. A machine studying mannequin was used to extract the knowledge in these maps that was related to cosmological fashions. A second machine studying software, studying from the various examples of simulated universes with totally different cosmological fashions, checked out the actual noticed information and gave the percentages on any cosmological mannequin being the true mannequin of our Universe.
This new approach allowed researchers to make use of way more info from the maps than could be doable with the earlier technique.
The simulations had been run on DiRAC Excessive Efficiency Computing (HPC) facility, funded by the UK’s Science and Know-how Amenities Council (STFC).
Future Explorations in Cosmology
The following section of darkish universe tasks – together with the European Space Agency (ESA) mission Euclid, launched last summer – will significantly improve the amount of knowledge we’ve on the large-scale buildings of the Universe, serving to researchers decide if the surprising smoothness of the Universe is an indication present cosmological fashions are mistaken or if there’s one other clarification for it.
At the moment, this smoothness is at odds with what could be predicted based mostly on evaluation of the cosmic microwave background (CMB) – the sunshine left over from the Large Bang.
The Darkish Vitality Survey collaboration, of which UCL is a founding member, is hosted by the US Division of Vitality’s Fermi Nationwide Accelerator Laboratory (Fermilab) and includes greater than 400 scientists from 25 establishments in seven nations.
The collaboration has cataloged a whole bunch of tens of millions of galaxies, utilizing images of the evening sky taken by the 570-megapixel Darkish Vitality Digital camera, one of many world’s strongest digital cameras, over six years (from 2013 to 2019). The digital camera, whose optical corrector was constructed at UCL, is mounted on a telescope on the Nationwide Science Basis’s Cerro Tololo Inter-American Observatory in Chile.
Reference: “Darkish Vitality Survey Yr 3 outcomes: likelihood-free, simulation-based wCDM inference with neural compression of weak-lensing map statistics” by N. Jeffrey, L. Whiteway, M. Gatti, J. Williamson, J. Alsing, A. Porredon, J. Prat, C. Doux, B. Jain, C. Chang, T.-Y. Cheng, T. Kacprzak, P. Lemos, A. Alarcon, A. Amon, Ok. Bechtol, M. R. Becker, G. M. Bernstein, A. Campos, A. Carnero Rosell, R. Chen, A. Choi, J. DeRose, A. Drlica-Wagner, Ok. Eckert, S. Everett, A. Ferté, D. Gruen, R. A. Gruendl, Ok. Herner, M. Jarvis, J. McCullough, J. Myles, A. Navarro-Alsina, S. Pandey, M. Raveri, R. P. Rollins, E. S. Rykoff, C. Sánchez, L. F. Secco, I. Sevilla-Noarbe, E. Sheldon, T. Shin, M. A. Troxel, I. Tutusaus, T. N. Varga, B. Yanny, B. Yin, J. Zuntz, M. Aguena, S. S. Allam, O. Alves, D. Bacon, S. Bocquet, D. Brooks, L. N. da Costa, T. M. Davis, J. De Vicente, S. Desai, H. T. Diehl, I. Ferrero, J. Frieman, J. García-Bellido, E. Gaztanaga, G. Giannini, G. Gutierrez, S. R. Hinton, D. L. Hollowood, Ok. Honscheid, D. Huterer, D. J. James, O. Lahav, S. Lee, J. L. Marshall, J. Mena-Fernández, R. Miquel, A. Pieres, A. A. Plazas Malagón, A. Roodman, M. Sako, E. Sanchez, D. Sanchez Cid, M. Smith, E. Suchyta, M. E. C. Swanson, G. Tarle, D. L. Tucker, N. Weaverdyck, J. Weller, P. Wiseman and M. Yamamoto, 4 March 2024, Cosmology and Nongalactic Astrophysics.
arXiv:2403.02314
