ASCL.net

Astrophysics Source Code Library

Making codes discoverable since 1999

Searching for codes credited to 'Gully-Santiago, Michael'

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[ascl:1812.013] Lightkurve: Kepler and TESS time series analysis in Python

Lightkurve analyzes astronomical flux time series data, in particular the pixels and light curves obtained by NASA’s Kepler, K2, and TESS exoplanet missions. This community-developed Python package is designed to be user friendly to lower the barrier for students, astronomers, and citizen scientists interested in analyzing data from these missions. Lightkurve provides easy tools to download, inspect, and analyze time series data and its documentation is supported by a large syllabus of tutorials.

[ascl:2502.017] blasé: Interpretable machine learning for high-resolution astronomical spectroscopy

blasé performs whole-spectrum fitting by cloning 10,000+ spectral lines from a pre-computed synthetic spectral model template and then learning the perturbations to those lines through comparison to real data. Each spectral line has four parameters, yielding possibly 40,000+ parameters. The technique uses autodiff to tune the parameters precisely and quickly. Built in PyTorch with native GPU support, blasé can be extended to, for example, Doppler imaging, Precision RVs, and abundances.

[ascl:2502.018] TESS-SIP: Long term rotation period finding tool

TESS-SIP creates a Systematics-insensitive Periodogram (SIP) using lightkurve (ascl:1812.013) to detect long period rotation in NASA's TESS mission data. The SIP method detrends telescope systematics (the TESS scattered light) simultaneously with calculating a Lomb-Scargle periodogram, thus allowing estimation of the rotation rate of variables with a period of >30 days when there are multiple sectors.

[ascl:2503.015] gollum: Programmatic access to precomputed synthetic spectral model grids

Gollum performs spectral visualization and analysis. It offers both a programmatic interface and a visual interface that help users analyze stellar and substellar spectra, with support included for a set of precomputed synthetic spectral model grids.