We report a newly identified nonlinearity in H4RG-10 near-infrared detectors operating under moderately elevated-temperature conditions (114 K). This component, that potentially arises from illumination-independent defect currents, introduces additional nonlinearity not captured by conventional correction models. To address this issue, we propose a data-driven nonlinearity correction (NLC) method that models the nonlinear behavior of both the classical response and the defect currents, using dual-illumination measurements and a dark exposure. Applied to H4RG-10 detectors on the PRIME telescope, the method significantly improves signal linearity, especially for pixels with high defect current, while maintaining comparable performance elsewhere. By selecting the optimal correction model per pixel, reliable NLC is achieved across the full array. This study characterizes a nonlinearity intrinsic to H4RG-10 detectors and demonstrates that data-driven post-processing can effectively restore linearity in the presence of large defect currents. Although these effects are unlikely to be significant under nominal operating temperatures, the approach may provide a practical calibration framework for future warm-operation scenarios.
@article{arxiv.2602.13983,
title = {Nonlinearity in H4RG-10 Near-Infrared Detectors at Elevated Temperatures: Characterization and Data-Driven Correction Method},
author = {Ryusei Hamada and Gregory Mosby and Shota Miyazaki and Daisuke Suzuki and Alexander Kutyrev and Joseph Durbak and Yuki Hirao and Takahiro Sumi},
journal= {arXiv preprint arXiv:2602.13983},
year = {2026}
}
Comments
13 pages, 9 figures, accepted for publication in PASP