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Conference object . 2022
License: CC BY
Data sources: Datacite
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Other literature type . 2022
License: CC BY
Data sources: ZENODO
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Conference object . 2022
License: CC BY
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Star Formation histories and Chemical enrichment using neural networks

descriptionPublicationkeyboard_double_arrow_right Conference object , Other literature type 02 Sep 2022 English Publisher:Zenodo
Authors: Galceran, Enrique; Sánchez-Blázquez, Patricia; Collaboration, The PHANGS;

doi: 10.5281/zenodo.7047433 , 10.5281/zenodo.7043880

Star Formation histories and Chemical enrichment using neural networks

Abstract

We present spatially resolved Star Formation Histories and metallicity evolution on nearby galaxies. We use Convolutional Neural Networks with a combination of MUSE optical spectroscopy and HST photometry in the UV range. Combined with the high-resolution CO emission information from the PHANGS catalogue, this analysis will allow to infer the timescales for star formation and cloud destruction in different galaxy environments, providing clues about the dominant mechanisms of stellar feedback.

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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