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Euclid preparation. Predicting star-forming galaxy scaling relations with the spectral stacking code SpectraPyle

Euclid preparation. Predicting star-forming galaxy scaling relations with the spectral stacking code SpectraPyle
Euclid preparation. Predicting star-forming galaxy scaling relations with the spectral stacking code SpectraPyle
We introduce SpectraPyle, a versatile spectral stacking pipeline developed for the Euclid mission's NISP spectroscopic surveys, aimed at extracting faint emission lines and spectral features from large galaxy samples in the Wide and Deep Surveys. Designed for computational efficiency and flexible configuration, SpectraPyle supports the processing of extensive datasets critical to Euclid's non-cosmological science goals. We validate the pipeline using simulated spectra processed to match Euclid's expected final data quality. Stacking enables robust recovery of key emission lines, including Halpha, Hbeta, [O III], and [N II], below individual detection limits. However, the measurement of galaxy properties such as star formation rate, dust attenuation, and gas-phase metallicity are biased at stellar mass below log10(M*/Msol) ~ 9 due to the flux-limited nature of Euclid spectroscopic samples, which cannot be overcome by stacking. The SFR-stellar mass relation of the parent sample is recovered reliably only in the Deep survey for log10(M*/Msol) > 10, whereas the metallicity-mass relation is recovered more accurately over a wider mass range. These limitations are caused by the increased fraction of redshift measurement errors at lower masses and fluxes. We examine the impact of residual redshift contaminants that arises from misidentified emission lines and noise spikes, on stacked spectra. Even after stringent quality selections, low-level contamination (< 6%) has minimal impact on line fluxes due to the systematically weaker emission of contaminants. Percentile-based analysis of stacked spectra provides a sensitive diagnostic for detecting contamination via coherent spurious features at characteristic wavelengths. While our simulations include most instrumental effects, real Euclid data will require further refinement of contamination mitigation strategies.
astro-ph.GA
arXiv
Quai, S.
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Pozzetti, L.
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Talia, M.
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Mancini, C.
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Cassata, P.
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Brun, V. Le
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Bolzonella, M.
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Rossetti, E.
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Moresco, M.
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Zamorani, G.
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Vergani, D.
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Allevato, V.
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Lucia, G. De
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Dickinson, H.J.
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Wang, L.
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Sorce, J.G.
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Amara, A.
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Andreon, S.
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Auricchio, N.
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Baccigalupi, C.
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Baldi, M.
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Bardelli, S.
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Biviano, A.
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Branchini, E.
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Brescia, M.
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Brinchmann, J.
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Camera, S.
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Cañas-Herrera, G.
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Capobianco, V.
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Carbone, C.
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Carretero, J.
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Casas, S.
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Castignani, G.
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Shankar, F.
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Euclid Collaboration
Quai, S.
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Pozzetti, L.
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Talia, M.
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Mancini, C.
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Cassata, P.
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Gabarra, L.
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Brun, V. Le
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Bolzonella, M.
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Rossetti, E.
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Kruk, S.
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Granett, B.R.
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Scarlata, C.
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Moresco, M.
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Zamorani, G.
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Vergani, D.
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Lopez, X. Lopez
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Enia, A.
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Daddi, E.
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Allevato, V.
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Zinchenko, I.A.
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Siudek, M.
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Lucia, G. De
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Dickinson, H.J.
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Lusso, E.
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Hirschmann, M.
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Cimatti, A.
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Wang, L.
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Sorce, J.G.
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Aghanim, N.
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Amara, A.
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Andreon, S.
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Auricchio, N.
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Baccigalupi, C.
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Baldi, M.
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Bardelli, S.
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Biviano, A.
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Branchini, E.
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Brescia, M.
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Brinchmann, J.
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Camera, S.
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Cañas-Herrera, G.
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Capobianco, V.
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Carbone, C.
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Carretero, J.
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Casas, S.
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Castellano, M.
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Castignani, G.
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Shankar, F.
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[Unknown type: UNSPECIFIED]

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Abstract

We introduce SpectraPyle, a versatile spectral stacking pipeline developed for the Euclid mission's NISP spectroscopic surveys, aimed at extracting faint emission lines and spectral features from large galaxy samples in the Wide and Deep Surveys. Designed for computational efficiency and flexible configuration, SpectraPyle supports the processing of extensive datasets critical to Euclid's non-cosmological science goals. We validate the pipeline using simulated spectra processed to match Euclid's expected final data quality. Stacking enables robust recovery of key emission lines, including Halpha, Hbeta, [O III], and [N II], below individual detection limits. However, the measurement of galaxy properties such as star formation rate, dust attenuation, and gas-phase metallicity are biased at stellar mass below log10(M*/Msol) ~ 9 due to the flux-limited nature of Euclid spectroscopic samples, which cannot be overcome by stacking. The SFR-stellar mass relation of the parent sample is recovered reliably only in the Deep survey for log10(M*/Msol) > 10, whereas the metallicity-mass relation is recovered more accurately over a wider mass range. These limitations are caused by the increased fraction of redshift measurement errors at lower masses and fluxes. We examine the impact of residual redshift contaminants that arises from misidentified emission lines and noise spikes, on stacked spectra. Even after stringent quality selections, low-level contamination (< 6%) has minimal impact on line fluxes due to the systematically weaker emission of contaminants. Percentile-based analysis of stacked spectra provides a sensitive diagnostic for detecting contamination via coherent spurious features at characteristic wavelengths. While our simulations include most instrumental effects, real Euclid data will require further refinement of contamination mitigation strategies.

Text
2509.16120v1 - Author's Original
Available under License Creative Commons Attribution.
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Accepted/In Press date: 19 September 2025
Additional Information: 17 pages, 21 figures, Submitted to A&A
Keywords: astro-ph.GA

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Local EPrints ID: 510438
URI: http://eprints.soton.ac.uk/id/eprint/510438
PURE UUID: bec53adf-832a-43cb-a4e9-1f90090d66bd

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Date deposited: 31 Mar 2026 16:46
Last modified: 31 Mar 2026 16:46

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Contributors

Author: S. Quai
Author: L. Pozzetti
Author: M. Talia
Author: C. Mancini
Author: P. Cassata
Author: L. Gabarra
Author: V. Le Brun
Author: M. Bolzonella
Author: E. Rossetti
Author: S. Kruk
Author: B.R. Granett
Author: C. Scarlata
Author: M. Moresco
Author: G. Zamorani
Author: D. Vergani
Author: X. Lopez Lopez
Author: A. Enia
Author: E. Daddi
Author: V. Allevato
Author: I.A. Zinchenko
Author: M. Magliocchetti
Author: M. Siudek
Author: L. Bisigello
Author: G. De Lucia
Author: H.J. Dickinson
Author: E. Lusso
Author: M. Hirschmann
Author: A. Cimatti
Author: L. Wang
Author: J.G. Sorce
Author: N. Aghanim
Author: A. Amara
Author: S. Andreon
Author: N. Auricchio
Author: C. Baccigalupi
Author: M. Baldi
Author: S. Bardelli
Author: A. Biviano
Author: E. Branchini
Author: M. Brescia
Author: J. Brinchmann
Author: S. Camera
Author: G. Cañas-Herrera
Author: V. Capobianco
Author: C. Carbone
Author: J. Carretero
Author: S. Casas
Author: M. Castellano
Author: G. Castignani
Author: F. Shankar
Corporate Author: Euclid Collaboration

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