XXI International Workshop on Neutrino Telescopes

Controlling data systematics in Euclid spectroscopy with simulations and real observations

Oct 2, 2025, 9:50 AM

20m

Main Auditorium (Centro Culturale San Gaetano)

Contributed Talk Data Science and Detector R&D Data Science and Detector R&D

Speaker

Francesca Passalacqua (Istituto Nazionale di Fisica Nucleare)

Description

Euclid is a mission of the European Space Agency (ESA), designed to investigate the content and evolution of the Universe. Launched in July 2023, the satellite will collect data for at least six years, covering one-third of the sky. Euclid holds the promise to provide crucial new constraints on relevant cosmological parameters, including the sum of the neutrino masses.

Accurate cosmological inference from Euclid data requires careful treatment of observational systematics, which could bias the measured galaxy distribution and distort parameter estimation. Galaxy clustering analyses, in particular, depend on a detailed understanding of the purity and completeness of the cosmological sample. The idea is to assess these properties using two complementary approaches: simulations and deep observations of reference fields. While simulations offer a controlled environment with known inputs, they must be computationally efficient and account for instrumental effects that are not fully understood. Indeed, certain detector non-idealities, such as persistence and snowballs, remain difficult to model accurately, limiting the realism of such simulations. However, deeper observations are confined to small sky regions and present complex selection functions, limiting their representativeness of the data sample.

We first present a fully simulated pipeline to assess the systematic effects, such as spectral overlap, which is one of the main challenges of Euclid's slitless spectroscopic technique. We also present a complementary approach in which we simulate only the spectra; those are then injected into real Euclid images and then processed through the full data pipeline. This method naturally inherits instrumental systematics from real data, offering a more realistic characterisation of purity and completeness. Though computationally intensive, it enables the assessment of systematics over larger sky areas and provides a valuable complementary strategy for robust cosmological analyses and neutrino mass investigations.