BatAnalysis -- A Comprehensive Python Pipeline for Swift BAT Time-Tagged Event Data Analysis
Tyler Parsotan, David M. Palmer, Samuele Ronchini, James Delaunay, Aaron Tohuvavohu, Sibasish Laha, Amy Lien, S. Bradley Cenko, Hans Krimm, Craig Markwardt

TL;DR
BatAnalysis is an open-source Python pipeline that enhances the analysis of Swift BAT time-tagged event data, enabling customized, advanced studies of various astrophysical transient sources.
Contribution
The paper introduces new open-source Python tools for flexible, detailed analysis of BAT TTE data, expanding capabilities beyond existing software.
Findings
Successfully analyzed TTE data from multiple transient sources
Enabled detailed spectral and timing analysis with customizable parameters
Demonstrated utility in multi-messenger astrophysics investigations
Abstract
The Swift Burst Alert Telescope (BAT) is a coded aperture gamma-ray instrument with a large field of view that was designed to detect and localize transient events. When a transient is detected, either on-board or externally, the BAT saves time-tagged event (TTE) data which provides the highest quality information of the locations of the photons on the detector plane and their energies. This data can be used to produce spectra, lightcurves, and sky images of a transient event. While these data products are produced by the Swift Data Center and can be produced by current software, they are often preset to certain time and energy intervals which has limited their use in the current time domain and multi-messenger environment. Here, we introduce a new capability for the BatAnalysis python package to download and process TTE data under an open-source pythonic framework that allows for easy…
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Taxonomy
TopicsScientific Computing and Data Management
