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Baryon acoustic oscillations reconstruction using convolutional neural networks
- Source :
- Mao, T-X, Wang, J, Li, B, Cai, Y-C, Falck, B, Neyrinck, M & Szalay, A 2021, ' Baryon acoustic oscillations reconstruction using convolutional neural networks ', Monthly Notices of the Royal Astronomical Society, vol. 501, no. 1, pp. 1499-1510 . https://doi.org/10.1093/mnras/staa3741, Monthly notices of the Royal Astronomical Society, 2021, Vol.501(1), pp.1499-1510 [Peer Reviewed Journal]
- Publication Year :
- 2020
-
Abstract
- We propose a new scheme to reconstruct the baryon acoustic oscillations (BAO) signal, which contains key cosmological information, based on deep convolutional neural networks (CNN). Trained with almost no fine-tuning, the network can recover large-scale modes accurately in the test set: the correlation coefficient between the true and reconstructed initial conditions reaches $90\%$ at $k\leq 0.2 h\mathrm{Mpc}^{-1}$, which can lead to significant improvements of the BAO signal-to-noise ratio down to $k\simeq0.4h\mathrm{Mpc}^{-1}$. Since this new scheme is based on the configuration-space density field in sub-boxes, it is local and less affected by survey boundaries than the standard reconstruction method, as our tests confirm. We find that the network trained in one cosmology is able to reconstruct BAO peaks in the others, i.e. recovering information lost to non-linearity independent of cosmology. The accuracy of recovered BAO peak positions is far less than that caused by the difference in the cosmology models for training and testing, suggesting that different models can be distinguished efficiently in our scheme. It is very promising that Our scheme provides a different new way to extract the cosmological information from the ongoing and future large galaxy surveys.<br />Accepted for publication in MNRAS
- Subjects :
- Physics
FOS: Computer and information sciences
Fine-tuning
Computer Science - Machine Learning
Cosmology and Nongalactic Astrophysics (astro-ph.CO)
Correlation coefficient
010308 nuclear & particles physics
cs.LG
FOS: Physical sciences
Astronomy and Astrophysics
Astrophysics::Cosmology and Extragalactic Astrophysics
01 natural sciences
Convolutional neural network
Galaxy
Cosmology
Machine Learning (cs.LG)
Space and Planetary Science
Test set
0103 physical sciences
Dark energy
astro-ph.CO
Baryon acoustic oscillations
010303 astronomy & astrophysics
Algorithm
Astrophysics - Cosmology and Nongalactic Astrophysics
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Mao, T-X, Wang, J, Li, B, Cai, Y-C, Falck, B, Neyrinck, M & Szalay, A 2021, ' Baryon acoustic oscillations reconstruction using convolutional neural networks ', Monthly Notices of the Royal Astronomical Society, vol. 501, no. 1, pp. 1499-1510 . https://doi.org/10.1093/mnras/staa3741, Monthly notices of the Royal Astronomical Society, 2021, Vol.501(1), pp.1499-1510 [Peer Reviewed Journal]
- Accession number :
- edsair.doi.dedup.....5d0cbbefe6adc22eb1a629b812f83079