Specreduce: An AstroPy-coordinated Toolbox for Spectroscopic Data Reduction

Timothy E. Pickering, Erik Tollerud, Clare Shanahan, Kyle Conroy, Richard O’Steen, Camilla Pacifici, Brett Morris

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

specreduce is an AstroPy-coordinated python package whose goal is to be a toolbox of functions and utilities that are relevant to the reduction of spectroscopic data. It is largely focused on optical/IR spectroscopy where the raw data consists of an image projected from a spectrograph onto a 2D imaging detector. The way the spectral and spatial information is encoded into these 2D images can be quite complex and varied (e.g. multi-object vs multi-fiber vs integral field spectroscopy). Methods and algorithms for handling this variety of data have been implemented across many previous and existing data pipelines. Specreduce aims to collect these best practices into a common, shared space that facilitates more collaboration and easier development of future spectroscopic pipelines.

Original languageEnglish (US)
Title of host publicationSoftware and Cyberinfrastructure for Astronomy VIII
EditorsJorge Ibsen, Gianluca Chiozzi
PublisherSPIE
ISBN (Electronic)9781510675254
DOIs
StatePublished - 2024
Externally publishedYes
EventSoftware and Cyberinfrastructure for Astronomy VIII 2024 - Yokohama, Japan
Duration: Jun 16 2024Jun 21 2024

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume13101
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceSoftware and Cyberinfrastructure for Astronomy VIII 2024
Country/TerritoryJapan
CityYokohama
Period6/16/246/21/24

Keywords

  • astropy
  • community developed
  • data reduction pipelines
  • open source
  • spectroscopy

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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