From EMBER to FIRE: predicting high resolution baryon fields from dark matter simulations with Deep...
From EMBER to FIRE: predicting high resolution baryon fields from dark matter simulations with Deep Learning
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Ithaca: Cornell University Library, arXiv.org
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English
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Publisher
Ithaca: Cornell University Library, arXiv.org
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Contents
Hydrodynamic simulations provide a powerful, but computationally expensive, approach to study the interplay of dark matter and baryons in cosmological structure formation. Here we introduce the EMulating Baryonic EnRichment (EMBER) Deep Learning framework to predict baryon fields based on dark-matter-only simulations thereby reducing computational...
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Full title
From EMBER to FIRE: predicting high resolution baryon fields from dark matter simulations with Deep Learning
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TN_cdi_proquest_journals_2586208887
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2586208887
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E-ISSN
2331-8422
DOI
10.48550/arxiv.2110.11970
