A Unified Multi-Wavelength Data Analysis Workflow with gammapy. Constraining the Broadband Emission of FSRQ OP 313
arXiv:2409.20487 · doi:10.1051/0004-6361/202452349
Abstract
The Flat Spectrum Radio Quasar OP~313 entered an enhanced activity phase in November 2023 and has undergone multiple flares since then which have motivated the organisation of several large multi-wavelength campaigns, including two deep observations from the hard X-ray telescope NuSTAR. The broadband emission from OP~313 during these two observations is investigated under a new unified analysis framework, with data spanning from optical to gamma rays. Traditional methods for analyzing blazar emissions often rely on proprietary software tailored to specific instruments, making it challenging to integrate and interpret data from multi-wavelength campaigns comprehensively. This study demonstrates the feasibility of utilizing gammapy, an open-source Python package, and common data formats originally developed for gamma-ray instrumentation, to perform a consistent multi-instrument analysis. This enables a forward folding approach that fully incorporates source observations, detector responses, and various instrumental and astrophysical backgrounds. The methodology is applied as an example to recent data collected from the distant quasar OP~313. We present a comprehensive data reconstruction and analysis for instruments including the Liverpool Telescope's IO:O detector, Swift-UVOT, Swift-XRT, NuSTAR, and Fermi-LAT. The resulting spectral analysis is validated against the native tools for each instrument. Additionally, a multi-wavelength phenomenological model of the source emission, encompassing optical to gamma-ray bands, is developed, incorporating absorption components across different energy regimes. We introduce and validate a new unified framework for multi-wavelength forward folding data analysis based on gammapy and open data formats, demonstrating its application to spectral data from the quasar OP~313.
arXiv comment17 pages, 10 figures github: https://github.com/mireianievas/gammapy_mwl_workflow zenodo: https://zenodo.org/records/13837637
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