Optimal and Unbiased Fluxes from Up-the-Ramp Detectors under Variable Illumination
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866910061623771136 |
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| author | Li, Bowen McKinnon, Kevin A. Saydjari, Andrew K. Sayres, Conor Eadie, Gwendolyn M. Casey, Andrew R. Holtzman, Jon A. Brandt, Timothy D. Fernandez-Trincado, Jose G. |
| author_facet | Li, Bowen McKinnon, Kevin A. Saydjari, Andrew K. Sayres, Conor Eadie, Gwendolyn M. Casey, Andrew R. Holtzman, Jon A. Brandt, Timothy D. Fernandez-Trincado, Jose G. |
| contents | Near-infrared (NIR) detectors -- which use non-destructive readouts to measure time-series counts-per-pixel -- play a crucial role in modern astrophysics. Standard NIR flux extraction techniques were developed for space-based observations and assume that source fluxes are constant over an observation. However, ground-based telescopes often see short-timescale atmospheric variations that can dramatically change the number of photons arriving at a pixel. This work presents a new statistical model that shares information between neighboring spectral pixels to characterize time-variable observations and extract unbiased fluxes with optimal uncertainties. We generate realistic synthetic data using a variety of flux and amplitude-of-time-variability conditions to confirm that our model recovers unbiased and optimal estimates of both the true flux and the time-variable signal. We find that the time-variable model should be favored over a constant-flux model when the observed count rates change by more than 3.5%. Ignoring time variability in the data can result in flux-dependent, unknown-sign biases that are as large as ~120% of the flux uncertainty. Using real APOGEE spectra, we find empirical evidence for approximately wavelength-independent, time-dependent variations in count rates with amplitudes much greater than the 3.5% threshold. Our model can robustly measure and remove the time-dependence in real data, improving the quality of data-model comparison. We show several examples where the observed time-dependence quantitatively agrees with independent measurements of observing conditions, such as variable cloud cover and seeing. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2601_10878 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Optimal and Unbiased Fluxes from Up-the-Ramp Detectors under Variable Illumination Li, Bowen McKinnon, Kevin A. Saydjari, Andrew K. Sayres, Conor Eadie, Gwendolyn M. Casey, Andrew R. Holtzman, Jon A. Brandt, Timothy D. Fernandez-Trincado, Jose G. Instrumentation and Methods for Astrophysics Applications Near-infrared (NIR) detectors -- which use non-destructive readouts to measure time-series counts-per-pixel -- play a crucial role in modern astrophysics. Standard NIR flux extraction techniques were developed for space-based observations and assume that source fluxes are constant over an observation. However, ground-based telescopes often see short-timescale atmospheric variations that can dramatically change the number of photons arriving at a pixel. This work presents a new statistical model that shares information between neighboring spectral pixels to characterize time-variable observations and extract unbiased fluxes with optimal uncertainties. We generate realistic synthetic data using a variety of flux and amplitude-of-time-variability conditions to confirm that our model recovers unbiased and optimal estimates of both the true flux and the time-variable signal. We find that the time-variable model should be favored over a constant-flux model when the observed count rates change by more than 3.5%. Ignoring time variability in the data can result in flux-dependent, unknown-sign biases that are as large as ~120% of the flux uncertainty. Using real APOGEE spectra, we find empirical evidence for approximately wavelength-independent, time-dependent variations in count rates with amplitudes much greater than the 3.5% threshold. Our model can robustly measure and remove the time-dependence in real data, improving the quality of data-model comparison. We show several examples where the observed time-dependence quantitatively agrees with independent measurements of observing conditions, such as variable cloud cover and seeing. |
| title | Optimal and Unbiased Fluxes from Up-the-Ramp Detectors under Variable Illumination |
| topic | Instrumentation and Methods for Astrophysics Applications |
| url | https://arxiv.org/abs/2601.10878 |