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Astrophysics Source Code Library

Making codes discoverable since 1999

Searching for codes credited to 'Padilla, Nelson'

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[ascl:1804.011] DESCQA: Synthetic Sky Catalog Validation Framework

The DESCQA framework provides rigorous validation protocols for assessing the quality of high-quality simulated sky catalogs in a straightforward and comprehensive way. DESCQA enables the inspection, validation, and comparison of an inhomogeneous set of synthetic catalogs via the provision of a common interface within an automated framework. An interactive web interface is also available at https://portal.nersc.gov/projecta/lsst/descqa/v2/.

[ascl:2312.015] SUNBIRD: Neural-network-based models for galaxy clustering

SUNBIRD trains neural-network-based models for galaxy clustering. It also incorporates pre-trained emulators for different summary statistics, including galaxy two-point correlation function, density-split clustering statistics, and old-galaxy cross-correlation function. These models have been trained on mock galaxy catalogs, and were calibrated to work for specific samples of galaxies. SUNBIRD implements routines with PyTorch to train new neural-network emulators.