easyspec: An Open-source Python Package for Long-slit Spectroscopy

In modern-day astronomy, near-infrared, optical, and ultraviolet spectroscopy are indispensable for studying a wide range of phenomena, from measuring black hole masses to analyzing chemical abundances in stellar atmospheres. However, spectroscopic data reduction is often performed using instrument-...

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Veröffentlicht in:The Astronomical journal Jg. 170; H. 3; S. 166 - 175
Hauptverfasser: de Menezes, Raniere, Massaro, Francesco, Negro, Michela, Raiteri, Claudia M., Peña-Herazo, Harold, Acosta-Pulido, Jose A.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Madison The American Astronomical Society 01.09.2025
IOP Publishing
Schlagworte:
Active galactic nuclei
Algorithms
Astronomy
Astronomy data analysis
Astronomy image processing
Black holes
Data reduction
Infrared astronomy
Markov chains
Measuring instruments
Monte Carlo simulation
Near infrared radiation
Open source software
Pipelines
Red shift
Spectroscopic telescopes
Spectroscopy
Spectrum analysis
Stellar atmospheres
Supermassive black holes
Telescopes
Ultraviolet astronomy
Ultraviolet spectroscopy
ISSN:0004-6256, 1538-3881
Online-Zugang:Volltext
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Zusammenfassung:In modern-day astronomy, near-infrared, optical, and ultraviolet spectroscopy are indispensable for studying a wide range of phenomena, from measuring black hole masses to analyzing chemical abundances in stellar atmospheres. However, spectroscopic data reduction is often performed using instrument-specific pipelines or legacy software well-established and robust within the community that are often challenging to implement and script in modern astrophysical workflows. In this work, we introduce easyspec, a new Python package designed for long-slit spectroscopy, capable of reducing, extracting, and analyzing spectra from a wide range of instruments—provided they deliver raw FITS files, the standard format for most optical telescopes worldwide. This package is built upon the well-established long-slit spectroscopy routines of the Image Reduction and Analysis Facility (IRAF), integrating modern coding techniques and advanced fitting algorithms based on Markov chain Monte Carlo simulations. We present a user-friendly open-source Python package that can be easily incorporated into customized pipelines for more complex analyses. To validate its capabilities, we apply easyspec to the active galactic nucleus G4Jy 1709, observed with the DOLORES spectrograph at the Telescopio Nazionale Galileo, measuring its redshift and estimating its supermassive black hole mass. Finally, we compare our results with a previous IRAF-based study.
Bibliographie:AAS64603
Laboratory Astrophysics, Instrumentation, Software, and Data
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SourceType-Scholarly Journals-1
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ISSN:0004-6256
1538-3881
DOI:10.3847/1538-3881/adf220