easyspec: An open-source Python package for long-slit spectroscopy

TL;DR

easyspec is an open-source Python package that simplifies long-slit spectroscopy data reduction, extraction, and analysis, integrating modern algorithms and enabling easier workflows for astronomers using various instruments.

Contribution

This work introduces easyspec, a Python package that modernizes long-slit spectroscopy data processing by combining IRAF routines with advanced fitting techniques and user-friendly design.

Findings

Successfully reduced and analyzed spectra from a real astronomical source.

Accurately measured redshift and black hole mass using easyspec.

Validated results against previous IRAF-based analysis.

Abstract

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 (MCMC) 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.