ASCL.net

Astrophysics Source Code Library

Making codes discoverable since 1999

Searching for codes credited to 'Somerville, Rachel S.'

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[ascl:2104.015] dense_basis: Dense Basis SED fitting

dense_basis implements the Dense Basis method tailored to SED fitting, in particular, the task of recovering accurate star formation history (SFH) information from galaxy spectral energy distributions (SEDs). The code's original use-case was simultaneously fitting specific large catalogs of galaxies; it is adapted to a general purpose SED fitting code, and acts as a module to compress and decompress SFHs and other time-series.

[ascl:2306.015] Mangrove: Infer galaxy properties using dark matter merger trees

Mangrove uses Graph Neural Networks to regress baryonic properties directly from full dark matter merger trees to infer galaxy properties. The package includes code for preprocessing the merger tree, and training the model can be done either as single experiments or as a sweep. Mangrove provides loss functions, learning rate schedulers, models, and a script for doing the training on a GPU.