Performance of the image persistence model for Euclid infrared detectors

TL;DR

This paper evaluates the performance of an empirical image persistence model for Euclid's infrared detectors, crucial for accurate astronomical observations and cosmological measurements, by comparing ground-based and in-orbit calibration data.

Contribution

It presents a ground-derived empirical model of image persistence tailored for Euclid's detectors and assesses its effectiveness using in-orbit calibration data.

Findings

Model accurately predicts persistence effects in Euclid detectors.

Persistence removal improves the quality of astronomical data.

Ground characterization data effectively inform in-orbit calibration.

Abstract

Large-format infrared detectors are at the heart of major ground and space-based astronomical instruments, and the HgCdTe HxRG is the most widely used. The Near Infrared Spectrometer and Photometer (NISP) of the ESA's Euclid mission launched in July 2023 hosts 16 H2RG detectors in the focal plane. Their performance relies heavily on the effect of image persistence, which results in residual images that can remain in the detector for a long time contaminating any subsequent observations. Deriving a precise model of image persistence is challenging due to the sensitivity of this effect to observation history going back hours or even days. Nevertheless, persistence removal is a critical part of image processing because it limits the accuracy of the derived cosmological parameters. We will present the empirical model of image persistence derived from ground characterization data, adapted to the Euclid observation sequence and compared with the data obtained during the in-orbit calibrations of the satellite.