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REVIEW 4 major objections 5 minor 33 references

Persistence characteristics of H4RG-15 detectors for ESO instruments

T0 review · 4 major / 5 minor · reviewed 2026-08-03 · deepseek-v4-flash

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Pith's one-line read A six-year, 15-detector lab survey shows that H4RG-15 image persistence is a per-device property: one time-constant spectrum plus a trap map describes it, and only 2 of 15 detectors show the previously feared 65 K peak.

desk verdict Useful empirical survey of persistence in 15 H4RG-15s with a new classification and revised temperature recommendation; pipeline stability is acknowledged but unresolved. read the letter →

arxiv 2607.29435 v1 pith:4QW3AZ64 submitted 2026-07-31 astro-ph.IM physics.ins-det

Elizabeth M. George , Domingo Alvarez Mendez , Nagaraja Naidu Bezawada , Derek J. Ives , Mark Neeser , Benoit Serra This is my paper · ORCID
classification astro-ph.IMphysics.ins-det
keywords imagepersistenceH4RG-15HgCdTedetectorsinfrareddetectorcharacterizationtrapdensitymapdetrappingtimeconstantsoperatingtemperatureoptimizationmodel
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper reports a six-year laboratory campaign that characterized image persistence in fifteen H4RG-15 near-infrared detectors built for the MOONS and MICADO instruments, testing each between 40 and 85 kelvin. It claims that for most detectors the persistence behaviour across the entire array can be captured by a single time-constant spectrum plus a per-pixel trap-density map, and that the detectors fall into five behavioural types: persistence rising with temperature, flat, falling with temperature, a distinct peak near 65 kelvin, and artefacts from high contact resistance. Crucially, only two of the fifteen detectors definitively show the 65 kelvin peak, so the earlier recommendation to avoid operating temperatures between 45 and 75 kelvin should be reconsidered for the majority. Because each detector has a unique optimal temperature, the paper recommends flexible thermal interfaces in instrument design so the operating temperature can be chosen after full characterization.

What carries the argument

The persistence model: detrapping curves from long dark reads are fit to a sum of six exponentials with fixed time constants tau = 1, 10, 100, 1000, 10000, 100000 s; the fitted coefficients form a time-constant spectrum N, normalized to a trap-fraction vector that is fixed across the array, while a second fit per pixel yields a 4096x4096 maximum-trap map (and a trap-density map relative to illumination). This decomposition lets persistence be predicted and subtracted without knowing the underlying defect physics, and the same data can drive simulations.

What would settle it

Take a fully characterized detector, measure its persistence with the standard quick test after installation at the same operating temperature, and compare the observed amplitude and decay with the lab-built trap map; a deviation beyond lab repeatability would falsify the claim that lab characterization predicts in-situ persistence. The paper's own ERIS/NIX observation — a large initial trap amplitude that essentially vanished over time — is already an indicator to check.

Watch

Extended reading notes

Core claim

The central claim is that a single persistence model — a normalized vector of detrapping time constants (1, 10, 100, 1000, 10000, 100000 seconds) plus a full-frame trap-density map — is sufficient to describe and correct image persistence for most H4RG-15 detectors at a given temperature, and that the device-to-device variation in persistence is large enough that operating temperature must be chosen per detector. The paper's key empirical finding is that only 2 of 15 detectors exhibit the previously identified 65 K persistence peak, meaning the blanket recommendation to avoid 45–75 K is not generally valid. The paper also shows that some detectors contain distinct pixel populations (hot-pixe

Load-bearing premise

The lab-measured persistence trap maps and time-constant vectors remain stable and representative after the detector is installed and operated in the final instrument over its lifetime; the paper states this requirement and reports an unexplained decline of persistence in an on-telescope detector.

Editorial extensions

If this is right

  • If the model holds, persistence correction frames can be generated automatically from the exposure history ahead of each science frame, as already deployed for at least one instrument.
  • Operating temperatures for MOONS, MICADO, and HARMONI can be tuned per detector, trading persistence against noise and quantum efficiency.
  • Only detectors with hot-pixel or high-contact-resistance regions need more than a single time-constant spectrum; for the majority, one spectrum and one trap map suffice.
  • The rarity of the 65 K peak means future instruments need not avoid the 45–75 K range as a blanket rule, simplifying cryostat design.
  • The characterization data can be fed into the Pyxel simulator to test observing strategies before the detector is in the instrument.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The documented decline of persistence in one on-telescope detector suggests trap maps may drift over time; a periodic quick-verification test after installation would tell whether recalibration is needed, something the paper leaves open.
  • If the 0.13 eV trap is a process-related defect, a short screening test at 60–65 K on future deliveries could identify 65 K-peak devices early, before cryostat design is frozen.
  • The same characterization protocol could be applied to other HxRG generations (e.g., H2RG) to build a common ESO-wide persistence archive, extending the results beyond H4RG-15.
  • A testable extension: use the trap-density maps to predict persistence for arbitrary illumination patterns (e.g., moving OH lines in MOONS/HARMONI) and validate against on-sky darks; agreement would confirm the model's extrapolation to non-flat illumination.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 5 minor

Summary. This paper reports a systematic characterization of image persistence in 15 H4RG-15 HgCdTe detectors procured for ESO's MOONS, MICADO, and HARMONI instruments. The authors describe a standardized test protocol (LED illumination, 10,000 s soak, 14 h non-destructive readout) and fit detrapping curves with a sum of six exponentials with fixed time constants to produce per-detector time-constant spectra and pixel-level trap-density maps. They classify detector behavior into five categories (increasing, flat, decreasing, 65 K peak, high contact resistance) based on the temperature dependence of median trap density between 40 and 85 K, and they demonstrate the use of these maps in a persistence correction pipeline implemented in the ESO HDRL and in the Pyxel simulator. The paper concludes that each detector is unique and recommends instrument designs with flexible thermal interfaces so operating temperature can be chosen after full detector characterization.

Significance. The main value of this work is the empirical dataset: 15 science-grade H4RG-15 detectors characterized under a consistent protocol, with public access to the modeling framework and an example notebook. The categorization of persistence behavior is practically useful for instrument design, and the implementation of the correction algorithm in operational software is a concrete deliverable. If the stability assumption is validated, the approach could enable automatic persistence correction for ESO NIR instruments. However, the paper's quantitative claims are limited by the absence of uncertainty estimates and by the unresolved temporal-stability counterexample, which temper the strength of the conclusions.

major comments (4)
  1. [§2.1–2.2, Eq. (1), Table 1] The central taxonomy and model parameters are presented without uncertainties. The text states that each temperature is typically measured only once and that per-pixel S/N is insufficient for individual spectral fits. Nevertheless, Table 1 lists median trap densities to 0.1% and assigns detectors to categories based on their temperature dependence. Without error bars, repeat measurements, or goodness-of-fit statistics, categories such as 'flat' versus 'increasing' cannot be robustly separated (e.g., EG20373: 0.6%/0.7% vs SG20369: 0.6%/1.5%). Please report uncertainties on N_i, on the median trap densities, and on the classification, e.g., via bootstrap or repeat measurements.
  2. [§5] The paper states that 'the persistence trap maps and time constant vectors must remain stable over time for this strategy to work,' then immediately reports that the ERIS/NIX detector's persistence amplitude decreased on sky until it is 'almost never seen,' with no explanation. This is a direct counterexample to the stability assumption underlying the correction pipeline and the recommendation to set operating temperature after lab characterization. The manuscript provides no quantitative stability bound, no monitoring protocol, and no on-sky H4RG validation (MOONS commissioning is listed as future work). This external-validity gap must be addressed before the pipeline can be considered operationally validated.
  3. [§5, Figure 6] The example correction shown in Figure 6 appears to be an in-sample demonstration: the input dark frame and the persistence trap maps were collected in the same test campaign (the mask shadow is mentioned). An in-sample fit does not demonstrate predictive performance on new data. Please clarify whether the trap maps were derived from independent exposures, and if not, provide an out-of-sample test, such as prediction on a different cool-down, a different illumination level, or on-sky data.
  4. [§2.2] The two-stage fitting procedure is underspecified: after co-adding regions to obtain a normalized time-constant spectrum, 'every pixel' is fit for total trap number. Given the stated per-pixel S/N limitation, what is the uncertainty on the pixel-level trap maps? The paper does not provide residual maps or validation of the fixed-shape assumption. Please clarify the fitting method and quantify the resulting uncertainties on the trap maps.
minor comments (5)
  1. [§2.2] The text says 'a single vector with 5 values' but Eq. (1) has six time constants (1, 10, 100, 1000, 10000, 100000 s); should be 6.
  2. [Figure 1] Typo in caption: 'tempeartures' should be 'temperatures'.
  3. [Table 1, §3.4] For SG19907 and SG19910, the category 'increasing or 65K peak' makes the phrase 'only 2 of 15 definitively' somewhat misleading; consider stating '2 definitive, 2 ambiguous' explicitly.
  4. [§5] The phrase 'the rare case where a science exposure is contaminated' seems to understate the earlier discussion that persistence is expected in several observing modes; consider rewording.
  5. [References] Several references are to 2026 SPIE proceedings; please ensure DOIs or arXiv identifiers are included where available.

Circularity Check

0 steps flagged · score 2.0 of 10

No significant circularity: core claims are direct measurements; the sum-of-exponentials model is an empirical fit, and the pipeline demonstration is an in-sample application, not an independent derivation.

full rationale

The paper's central content is a characterization campaign: trap densities, time-constant spectra, and temperature-dependent persistence categories are measured and fitted, not derived from the conclusions. Equation (1) is a six-term sum of exponentials whose N_i coefficients are fit to detrapping curves; the single-spectrum-plus-trap-map description is a summary of that fit, so the detector-to-detector diversity in Table 1 and Figure 1 is a measurement result. Section 5's persistence correction uses the same fitted trap maps to compute a persistence frame, and Figure 6 is thus an in-sample demonstration rather than an out-of-sample validation; however, the paper does not claim it as an independent prediction or first-principles derivation. The self-citations to Tulloch and George 2019 and Ives et al. 2020 supply the fitting methodology and a tentative 0.13 eV trap interpretation, but they are not invoked as a uniqueness theorem and do not force the detector categories or the main empirical claims. The acknowledged ERIS/NIX temporal drift is an external-validity limitation, not a circularity: it weakens the long-term applicability of lab-derived trap maps but does not make any equation reduce to its own input. Overall, no quoted step exhibits the required 'Eq. X = Eq. Y by construction' or 'fitted parameter renamed as prediction' pattern, so the appropriate finding is a low score reflecting only minor in-sample/model-reuse caveats.

Assumptions & free parameters 2 free parameters · 4 assumptions · 0 invented entities

The quantitative claims rest on the choice of a six-exponential basis with fixed time constants, the assumption of spatial uniformity of the time-constant spectrum, and the implicit stability of lab measurements over time. The paper itself identifies exceptions (hot pixels, high contact resistance, ERIS/NIX drift).

free parameters (2)
  • Time constant bins τ_i = 1, 10, 100, 1000, 10000, 100000 s
    Chosen by hand as the basis for the exponential-sum model (Eq. 1). The 100000 s bin exceeds the 14-hour measurement window, so its amplitude is weakly constrained.
  • Trap counts N_i per time constant bin = varies per detector and region
    Fitted to the co-added detrapping curves; the normalized spectrum is then fixed and used to fit a total trap count per pixel. These are the central empirical outputs.
assumptions (4)
  • domain assumption Persistence detrapping can be modeled as a sum of exponentials with fixed discrete time constants.
    Eq. 1 assumes a discrete set of detrapping time constants. The authors note this requires no knowledge of the underlying physics and can fail for hot-pixel and high-contact-resistance regions (Section 2.2, Section 3).
  • domain assumption The normalized time-constant spectrum is spatially uniform across the detector for most detectors.
    Section 2.2 fixes the normalized spectrum and fits every pixel for a total trap count. Section 3 concedes this breaks down for regions with hot pixels or high contact resistance.
  • domain assumption Subtracting no-illumination dark frames removes dark current and residual persistence effects.
    Section 2.1 uses dark-frame subtraction to account for dark current over the 14-hour sequence, assuming dark current is identical in both and does not introduce its own persistence.
  • domain assumption Persistence trap maps and time constant vectors remain stable over time and across instrument installation.
    Section 5 states the correction strategy requires stability. EG20370 was stable over 11 cool-downs, but ERIS/NIX persistence decreased with time at the telescope, so this is not guaranteed.

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Cite this review

Pith. "Pith review of Persistence characteristics of H4RG-15 detectors for ESO instruments." pith.science (2026). https://pith.science/paper/4QW3AZ64

@misc{pith2026260729435,
  author       = {Pith},
  title        = {Pith review of: Persistence characteristics of H4RG-15 detectors for ESO instruments},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/4QW3AZ64}},
  note         = {Machine review of arXiv:2607.29435}
}
read the original abstract

As a part of the ESO Instrumentation Program, we already ordered 23 H4RG-15 (2.5 um cut-off) detectors for the instruments MOONS, MICADO, and HARMONI, with more of these detectors planned for future instruments on the ELT as well as possibly other ESO telescopes. As part of our comprehensive detector testing program, we characterize detector persistence at different temperatures between 40 and 85 K, allowing the best-informed choice of operating temperature for the science focal planes. We report the characteristics of persistence as a function of temperature for the 5 MOONS detectors and 10 MICADO detectors that have already been tested between 2019 and 2025. These detectors show a rich variety of persistence behaviour that can be fit with a single persistence model with varying parameters. We produce persistence trap maps and a model for persistence decay for each device, allowing automatic pipeline correction of persistence and also simulation of persistence behaviour of individual detectors using the Pyxel detector simulator. Each detector was unique and had different optimal operation temperatures for reduced persistence. We therefore recommend implementing a flexible thermal interface in the instrument design phase allowing for the detector operating temperature to be optimized after the science detectors have been fully characterized.

Figures

Figures reproduced from arXiv: 2607.29435 by the authors.

Figure 1
Figure 1. Median persistence trap density for each detector at the tempeartures tested. Details of each detector’s [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Top Left: Dark current map of the EG20373 detector at 85 K. Top Right: Persistence detrapping after about [PITH_FULL_IMAGE:figures/full_fig_p007_2.png] view at source ↗
Figure 3
Figure 3. Detector EG20370 waterfall diagram reproduced from Ives et. al 2020. [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figures from the paper (5 more)
Figure 4
Figure 4. Figure 4: Detector SG21540, which is heavily affected at low temperatures by high contact resistance pixels. Top row: [PITH_FULL_IMAGE:figures/full_fig_p009_4.png]
Figure 5
Figure 5. Figure 5: An example of the yaml configuration file to run the persistence model in pyxel. [PITH_FULL_IMAGE:figures/full_fig_p009_5.png]
Figure 6
Figure 6. Figure 6: Left: A 300s dark input frame taken after a saturating flat field exposure in detector 20374, heavily contaminated [PITH_FULL_IMAGE:figures/full_fig_p010_6.png]
Figure 7
Figure 7. Figure 7: Trap Density maps for all detectors at 40 K. [PITH_FULL_IMAGE:figures/full_fig_p012_7.png]
Figure 8
Figure 8. Figure 8: Trap Density maps for all detectors at 80 K. [PITH_FULL_IMAGE:figures/full_fig_p013_8.png]

Discussion (0). Continue with ORCID to comment.

Reference graph

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Pith tools

Reviewed August 3, 2026 · model on record in the stance chip above.