CONF1DENCE

Zenodo (CERN European Organization for Nuclear Research) 2026 Open access

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Authors: Martin Ying, Brian Chaboyer, Phillip Cargile, George Dufresne
DOI: 10.5281/zenodo.18331872
Cited by: 1

Abstract

COnditional Normalizing Flow based 1D stellar EvolutioN aCCElerator A fast, flexible stellar population synthesis tool powered by machine learning. CONF1DENCE uses conditional normalizing flows to emulate 1D stellar evolution models, enabling rapid generation of synthetic stellar populations with realistic observational effects.

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
22 January 2026