Lightkurve

Lightkurve
Name	Lightkurve
Developer	NASA, Space Telescope Science Institute, University of California, Berkeley
Released	2018
Programming language	Python (programming language)
Operating system	Cross-platform
License	MIT License

Lightkurve is an open-source Python (programming language) package designed for analysis of time-series photometry from space-based telescopes. It provides tools to search, download, visualize, and analyze light curves from missions such as Kepler, K2 (Kepler) and Transiting Exoplanet Survey Satellite while integrating with services from institutions like NASA, Space Telescope Science Institute, and Mikulski Archive for Space Telescopes. The project emphasizes reproducibility, interoperability with scientific libraries, and accessibility for researchers at organizations including University of California, Berkeley, Massachusetts Institute of Technology, and Harvard University.

Overview

Lightkurve is distributed as a Python (programming language) package that wraps mission-specific data access into a unified API, enabling workflows that combine tools from ecosystems developed at Astropy Project, NumPy, SciPy, Matplotlib (library), and Pandas (software). It targets time-domain astrophysics use cases tied to observatories such as Kepler, K2 (Kepler), Transiting Exoplanet Survey Satellite, and archives maintained by Mikulski Archive for Space Telescopes and NASA Exoplanet Archive. The package inter-operates with libraries like batman (code), celerite, emcee, and astroquery, and is commonly used in analyses that cite work from researchers affiliated with Caltech, Princeton University, University of Chicago, and Penn State University.

History and Development

Development began as a community effort motivated by the data volumes produced by Kepler and operational needs of the K2 (Kepler) mission, drawing contributors from institutions such as Space Telescope Science Institute, NASA Ames Research Center, University of California, Berkeley, and University of Oxford. Early design decisions were informed by standards from the FITS (file format) community, practices established by the Astropy Project, and data-access patterns from the Mikulski Archive for Space Telescopes. The project received support and contributions from collaborators at MIT, Harvard-Smithsonian Center for Astrophysics, Max Planck Institute for Astronomy, and amateur groups organized via platforms like GitHub and events including Hackathons and Google Summer of Code.

Features and Functionality

Lightkurve exposes objects and methods to manipulate mission products such as target pixel files, simple aperture photometry, and cotrended light curves produced for Kepler and TESS. Core functionality includes search interfaces that query archives hosted by Mikulski Archive for Space Telescopes and MAST, routines to create custom apertures inspired by methodologies developed in studies at NASA Ames Research Center and Space Telescope Science Institute, and detrending algorithms that incorporate approaches from Principal Component Analysis implementations used at Caltech and Harvard University. Visualization utilities leverage Matplotlib (library) and interoperate with interactive frameworks like Bokeh and Jupyter Notebook instances hosted by Binder. Statistical and modeling workflows connect to packages such as emcee, celerite, batman (code), and scikit-learn.

Data Sources and Compatibility

Lightkurve is compatible with mission archives and catalog services including Kepler, K2 (Kepler), Transiting Exoplanet Survey Satellite, the Mikulski Archive for Space Telescopes, and the NASA Exoplanet Archive. It reads data in FITS (file format) produced by teams at NASA, Space Telescope Science Institute, and instrument builders affiliated with organizations like Ball Aerospace and Lockheed Martin. The package supports formats and cross-matching workflows that integrate with catalogs from Gaia, Sloan Digital Sky Survey, Two Micron All-Sky Survey, and databases maintained by European Space Agency. Compatibility layers facilitate export to analysis environments used at University of Cambridge, University of Edinburgh, and national facilities such as NASA centers.

Usage and Examples

Researchers use Lightkurve for tasks including transit searches, stellar variability studies, asteroseismology, and exoplanet candidate vetting in collaboration with teams at NASA, MIT, Caltech, and UC Berkeley. Example pipelines combine Lightkurve with Astropy Project coordinates routines, astroquery for catalog lookups, and modeling with emcee or celerite to fit signals first reported by missions like Kepler and TESS. Community-led publications leveraging Lightkurve have come from groups at Harvard University, Penn State University, University of Oxford, and Max Planck Institute for Astronomy.

Community and Contributions

The project is maintained on collaborative platforms such as GitHub with contributions from volunteer developers at institutions including Space Telescope Science Institute, NASA Ames Research Center, University of California, Berkeley, MIT, Harvard-Smithsonian Center for Astrophysics, and international partners like Max Planck Society and European Space Agency. Outreach and training occur via workshops at conferences like American Astronomical Society meetings, UK Astronomy Technology Network events, and tutorials hosted by research centers at Princeton University and University of Chicago. Contributions follow governance and licensing practices compatible with MIT License stewardship and community processes influenced by the Astropy Project.

Category:Astronomy software