<i>Euclid</i> preparation
Bibliographic record
Abstract
This paper describes the objectives, design, and findings of the pre-launch ground characterisation campaigns of the Euclid infrared detectors. The aim of the ground characterisations is to evaluate the performance of the detectors, to calibrate the pixel response, and to derive the pixel response correction methods. The detectors have been tested and characterised in the facilities set up for this purpose. The pixel properties, including baseline, bad pixels, quantum efficiency, inter pixel capacitance, quantum efficiency, dark current, readout noise, conversion gain, response non-linearity, and image persistence were measured and characterised for each pixel. We describe in detail the test flow definition that allows us to derive the pixel properties and we present the data acquisition and data quality check software implemented for this purpose. We also outline the measurement protocols of all the pixel properties presented and we provide a comprehensive overview of the performance of the Euclid infrared detectors as derived after tuning the operating parameters of the detectors. The main conclusion of this work is that the performance of the infrared detectors Euclid meets the requirements. Pixels classified as non-functioning accounted for less than 0.2% of all science pixels. The interpixel capacitance (IPC) coupling is minimal, the cross-talk between adjacent pixels is less than 1% between adjacent pixels, and 95% of the pixels show a quantum efficienty (QE) greater than 80% across the entire spectral range of the Euclid mission. The conversion gain is approximately 0.52 ADU/e − , with a variation of less than 1% between channels of the same detector. The reset noise is approximately equal to 23 ADU rms after reference pixel correction. The readout noise of a single frame is approximately 13 e − rms while the signal estimator noise is measured at 7 e − rms in photometric mode and 9 e − rms in spectroscopic acquisition mode. The deviation from linear response at signal levels up to 80 ke − is less than 5% for 95% of the pixels. Median persistence amplitudes are less than 0.3% of the signal, though persistence exhibits significant spatial variation and differences between detectors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.021 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".