Hiflow: Generating diverse hi maps and inferring cosmology while marginalizing over astrophysics using normalizing flows

dc.contributor.authorHassan, Sultan
dc.contributor.authorVillaescusa-Navarro, Francisco
dc.contributor.authorWandelt, Benjamin
dc.date.accessioned2022-10-18T07:55:31Z
dc.date.available2022-10-18T07:55:31Z
dc.date.issued2022
dc.description.abstractA wealth of cosmological and astrophysical information is expected from many ongoing and upcoming large-scale surveys. It is crucial to prepare for these surveys now and develop tools that can efficiently extract most information. We present HIFLOW: a fast generative model of the neutral hydrogen (HI) maps that is conditioned only on cosmology (Ωm and σ8) and designed using a class of normalizing flow models, the masked autoregressive flow. HIFLOW is trained on the state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project. HIFLOW has the ability to generate realistic diverse maps without explicitly incorporating the expected two-dimensional maps structure into the flow as an inductive bias. We find that HIFLOW is able to reproduce the CAMELS average and standard deviation HI power spectrum within a factor of 2, scoring a very high R2 > 90%. By inverting the flow, HIFLOW provides a tractable high-dimensional likelihood for efficient parameter inference. We show that the conditional HIFLOW on cosmology is successfully able to marginalize over astrophysics at the field level, regardless of the stellar and AGN feedback strengths. This new tool represents a first step toward a more powerful parameter inference, maximizing the scientific return of future HI surveys, and opening a new avenue to minimize the loss of complex information due to data compression down to summary statistics.en_US
dc.identifier.citationHassan, S. et al. (2022). Hiflow: Generating diverse hi maps and inferring cosmology while marginalizing over astrophysics using normalizing flows. Astrophysical Journal, 937(2), 83. https://doi.org/10.3847/1538-4357/ac8b09en_US
dc.identifier.issn1538-4357
dc.identifier.urihttps://doi.org/10.3847/1538-4357/ac8b09
dc.identifier.urihttp://hdl.handle.net/10566/8060
dc.language.isoenen_US
dc.publisherIOP Publishingen_US
dc.subjectAstrophysicsen_US
dc.subjectAstrophysicsen_US
dc.subjectCosmologyen_US
dc.subjectReionizationen_US
dc.subjectEarly universeen_US
dc.titleHiflow: Generating diverse hi maps and inferring cosmology while marginalizing over astrophysics using normalizing flowsen_US
dc.typeArticleen_US

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