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REVIEW 4 major objections 6 minor 42 references

Assessing the Suitability of H4RG Near Infrared Detectors for Precise Doppler Radial Velocity Measurements

T0 review · 4 major / 6 minor · reviewed 2026-08-14 · deepseek-v4-flash

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Pith's one-line read H4RG near-infrared detectors can support sub-meter-per-second radial-velocity precision, provided persistence and nonlinearity are controlled.

desk verdict A useful first simulation-based error budget linking H4RG detector noise to RV precision, but the sub-m/s optimistic numbers rest on a single H2RG-derived read-noise realization and need error bars and lab validation before being used as requirements. read the letter →

arxiv 1908.11429 v1 pith:SI7ZBIFU submitted 2019-08-29 astro-ph.IM astro-ph.EP

Eric B. Bechter , Andrew J. Bechter , Justin R. Crepp , Jonathan Crass This is my paper · ORCID
classification astro-ph.IMastro-ph.EP
keywords radialvelocityH4RGdetectorsnear-infraredspectroscopydetectornoiseerrorbudgetinterpixelcapacitancepersistenceDopplerspectrographs
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

This paper asks whether the best commercially available near-infrared detectors, H4RG arrays, are good enough for the next generation of precise Doppler radial-velocity spectrographs. Using an end-to-end spectrograph simulation, it quantifies five detector noise sources—read noise, pixel nonlinearity, dark current, persistence, and interpixel capacitance—in units of velocity error. The central result is a detector-noise error budget between 0.32 and 3.5 m/s depending on optimistic or pessimistic assumptions, with read noise alone contributing 37 cm/s for a 30-minute exposure. The authors conclude that sub-meter-per-second near-infrared precision is achievable with HxRG arrays if persistence and nonlinearity are mitigated and detector noise dominates the error budget.

What carries the argument

The central mechanism is the pairing of an end-to-end echelle spectrograph simulator with the HxRG Noise Generator, a tool that emulates residual read noise as a sum of five principal-component patterns: white noise, correlated pink noise, uncorrelated pink noise, alternating column noise, and picture frame noise. Each detector effect is injected into simulated spectral frames and converted to a velocity error by extracting spectra and performing masked cross-correlation. Supporting models map pixel nonlinearity through a cubic correction term, dark current through Poisson residuals after mean subtraction, persistence through a fractional image that decays as 1/t, and interpixel capacitance through convolution with a coupling kernel.

What would settle it

Take a science-grade H4RG-10, operate it at its nominal temperature, acquire dark frames with reference-pixel subtraction and up-the-ramp sampling, and measure the residual noise rms and its principal-component amplitudes. If the measured rms deviates from the 5.4 e- emulated by the noise generator, or if the spatial correlation of the noise differs, the 37 cm/s read-noise contribution and the quadrature budget would need revision.

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Extended reading notes

Core claim

The central claim is that H4RG detectors do not inherently preclude sub-meter-per-second radial-velocity measurements. For an M0V, I = 10 star observed with iLocater-like parameters, the simulations yield a detector-noise error budget whose optimistic and pessimistic quadrature sums are 0.32 and 3.5 m/s. Read noise alone gives 37 cm/s at 30-minute integration, or 32 cm/s with an expected 15% IRS2 improvement; linearity ranges from 0.8 cm/s after correction to 2.6 m/s uncorrected; residual dark current is below 20 cm/s at temperatures at or below 100 K; persistence can reach 2.1 m/s under a 0.1% identical-spectrum remnant; and interpixel capacitance ranges from 5 to 87 cm/s depending on the kernel. The paper therefore concludes that precision radial-velocity spectrographs could reach sub-meter-per-second precision in the near infrared if HxRG arrays are used and errors are dominated by detector noise.

Load-bearing premise

The read-noise simulations assume that the PCA-based HxRG Noise Generator, trained on H2RG data, faithfully reproduces the residual noise of an H4RG after reference-pixel subtraction and up-the-ramp sampling.

Editorial extensions

If this is right

  • Read noise contributes 37 cm/s at a 30-minute exposure, and a 15% IRS2 readout improvement lowers this to 32 cm/s, leaving room for other terms in a sub-meter-per-second budget.
  • Uncorrected pixel nonlinearity can produce multi-meter-per-second errors, but with SPIRou-level correction it drops to 0.8 cm/s, making linearity correction a prerequisite.
  • Persistence is a dominant risk: a 0.1% remnant of an identical spectral type at a 3.5 km/s offset yields 2.1 m/s error, so observing schedules and calibration exposures must be managed.
  • Interpixel capacitance contributes anywhere from 5 to 87 cm/s depending on the kernel, meaning detector choice and IPC characterization matter.
  • The quadrature sum of all detector effects spans 0.32 to 3.5 m/s, and since individual effects partially cancel, this sum is likely an upper limit on the detector-induced velocity error.

Reading between the lines

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

  • The noise generator's principal-component basis comes from H2RG data; if H4RG residual noise has different spatial correlations, the 37 cm/s read-noise figure could shift, so a laboratory comparison on an actual H4RG would settle this.
  • The persistence results suggest that alternating science and etalon calibration frames is risky for sub-meter-per-second instruments, and a dedicated calibration fiber or persistence-model subtraction may be required.
  • Because several detector effects produce opposite-sign velocity shifts, a full end-to-end simulation with all effects turned on simultaneously could yield a total error lower than the quadrature sum.
  • If IRS2 interleaved readout reduces correlated 1/f noise as well as total noise, the read-noise term could fall below 32 cm/s, strengthening the case for sub-meter-per-second performance.
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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 / 6 minor

Summary. This paper presents an end-to-end simulation study of the impact of H4RG near-infrared detector noise on the radial velocity (RV) precision of a high-resolution echelle spectrograph, using the iLocater instrument model as a representative case. Five detector effects are treated one at a time: read noise (via the HxRG Noise Generator built on PCA of NIRSpec H2RG data), pixel nonlinearity (using Artigau's cubic mapping), residual dark current (Poisson draws at literature rates), persistence (fractional parasitic signals from M-star, G-star, and Fabry-Perot sources at various RV offsets), and interpixel capacitance (convolution with 3x3 and 9x9 kernels). For each effect, an RV error is recovered with the iLocater data-reduction pipeline and masked cross-correlation. The results are summarized in Table 1 as optimistic and pessimistic estimates, with quadrature sums of 0.32 m/s and 3.5 m/s, respectively. The authors conclude that sub-meter-per-second RV precision is attainable with H4RG arrays if detector noise dominates the error budget and persistence and nonlinearity are mitigated.

Significance. Assuming the quantitative results hold, this paper addresses a real gap: it connects specific H4RG detector characteristics to Doppler RV error in a form usable for instrument error budgets, and it has already informed the iLocater design reviews. The forward-simulation approach is a strength: noise coefficients, dark currents, persistence fractions, and IPC kernels are taken from the published literature rather than fit to the target RV errors, so Table 1 constitutes a set of falsifiable laboratory predictions. The paper is also transparent about its scope, explicitly listing omitted effects such as random telegraph noise, intra-pixel QE variations, and the brighter-fatter effect, and identifying laboratory validation as the next step. The main significance is as a design-stage error budget method rather than as a final performance demonstration; the optimistic column in particular should be read as an expectation pending H4RG-specific read-noise validation.

major comments (4)
  1. [§3.1, §4.1, Table 1] The read-noise term, which dominates the optimistic quadrature sum in Table 1 (0.31 of the 0.32 m/s total), is computed from a single simulated residual read-noise frame produced by the HxRG Noise Generator. Section 3.1 states that the generator's PCA basis is built from NIRSpec H2RG data, with H4RG represented only by adjusted settings, and the RV impact of read noise depends on the spatial correlation structure of the residual frame across spectral traces, not merely on its 5.4 e− rms. The manuscript reports no repeated-realization statistics for this or any other stochastic entry in Table 1, and no validation that the H2RG-based correlation structure is representative of H4RG readout. I ask for either multiple noise realizations with reported scatter, or an explicit sensitivity test showing that plausible changes in the residual noise correlation structure do not move the optimistic read-noise term above the sub-m/s budget.
  2. [§4.1, Table 1 note [1]] The optimistic read-noise value of 0.31 m/s is obtained by scaling the simulated 0.37 m/s result by a 15% IRS2 noise-reduction estimate taken from a private communication. The paper itself notes that IRS2 also reduces correlated noise and 1/f banding, which would affect the RV error in a way that is not purely proportional to total read noise. Because this scaling sets the largest term of the optimistic column, the manuscript should either give the 15% figure a stated uncertainty and show the sensitivity of the quadrature sum to it, or model the IRS2/interleaved readout mode in the noise generator so the claim does not rest on an unverifiable input.
  3. [§4.2, Table 1 note [2]] The optimistic linearity entry (0.8 cm/s = 0.008 m/s) is asserted by applying SPIRou's measured 0.3% residual linearity to the simulated 30-minute test case, but the mapping from residual nonlinearity fraction to RV error is not shown in the text; the reader cannot reproduce the 0.8 cm/s value from Figure 5 or from equation (1). Please make the scaling explicit (for example, RV error approximately equal to the residual linearity fraction times the uncorrected nonlinearity error), or provide the derivation. This is the one Table 1 entry whose value is assigned by a scaling statement rather than by the simulation pipeline described in Section 2.
  4. [§5, Table 1] The headline range of 0.32–3.5 m/s is presented as a quadrature sum of detector effects, but the spread between the columns is dominated by assumptions about observing conditions and mitigation (persistence spans 0.003–2.1 m/s; linearity 0.008–2.6 m/s) rather than by detector physics alone. As written, a reader cannot tell which terms represent a detector-noise floor and which represent a scenario choice. I recommend an explicit decomposition stating that, after persistence and linearity mitigation, the detector-limited quadrature sum is set by read noise, dark current, and IPC, and reporting that sub-m/s subset separately from the scenario-dependent terms.
minor comments (6)
  1. [§3.2, §4.1, §4.2] In-text references to 'Figure 3.2', 'Figure 4.1', and 'Figure 4.2' do not match the caption numbering (Figures 3, 4, and 5 in the List of Figures); the linearity mapping is Figure 3, the read-noise result is Figure 4, and the nonlinearity result is Figure 5, so the cross-references should be corrected.
  2. [§4.4] The text states that persistence results 'are shown in the vertical panels of Figure 7', but the figure caption describes top, middle, and bottom rows, i.e., horizontal panels; the wording should be changed.
  3. [§3.2] The phrase 'some elements along the electronic patch' appears to be a typo for 'electronic path'.
  4. [§3.3] The sentence 'Examples of dark current frames in HxRGs are can be found in several detector studies' contains a duplicated verb ('are can be'); remove 'are'.
  5. [§4.5] The sentence 'experimentally measured kernels do not exactly follow the mathematical α model exactly' repeats 'exactly'; one instance should be removed.
  6. [§2, Fig 4] The methodology states a median S/N of 187 per collapsed pixel, while the colorbar of Figure 4 spans median S/N values of 2000–10000; the relationship between these two quantities (per-pixel versus collapsed, single order versus full spectrum) should be clarified.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity found: forward simulation with independently adopted detector parameters; conclusion is a conditional error budget.

full rationale

The paper's derivation chain is a forward simulation. Section 2 builds a noise-free synthetic spectrum; Section 3 injects detector noise models whose parameters are taken from external literature (Artigau for nonlinearity and persistence, Teledyne/Beletic for dark current, Kannawadi and SPIRou/WFC3 for IPC, Rauscher's NG for read noise). The RV errors in Figures 4-8 and Table 1 are measured by extracting and cross-correlating the simulated spectra, not by fitting any parameter to the target RV values. The self-citations (refs. 13, 15) supply the iLocater instrument model and error budget as a representative test case; they are not used to justify detector noise amplitudes or to enforce the conclusion. The only notable approximation is that the HxRG Noise Generator is built from NIRSpec H2RG PCA modes with H4RG settings; this is an acknowledged modeling limitation, not a circular reduction, because the read-noise frame's 5.4 e- rms is stated independently and compared with literature. The optimistic 0.32 m/s quadrature sum is an explicitly labeled best-case error budget, not a prediction forced by construction from the claim it supports. No step in the paper reduces to its own input by definition, and no fitted parameter is renamed as a prediction. Therefore no significant circularity is identified.

Assumptions & free parameters 5 free parameters · 5 assumptions · 0 invented entities

All quantitative results are produced by forward simulation driven by noise parameters from prior literature; no parameters are fit to the RV errors themselves. The main assumptions are that the H2RG-based noise generator represents H4RGs, that the iLocater instrument is representative, and that simple models for nonlinearity, persistence, and IPC capture the dominant detector physics.

free parameters (5)
  • Nonlinearity coefficients c2, c3 = c2 = 1.3e-6 ADU^-1, c3 = 1.4e-12 ADU^-2
    Adopted from Artigau 2018, fitted to a small sample of H4RG pixel responses. Used as the uniform nonlinearity model for all pixels in the simulation.
  • IRS2 read noise improvement = 15%
    Quoted from private communication with B. Rauscher (2019); used to scale the read noise RV error from 37 to 32 cm/s in the optimistic case.
  • Post-correction linearity residual = 0.3% deviation at 30e4 ADU
    Taken from SPIRou's linearity correction demonstration and used to assert the optimistic linearity RV error of 0.8 cm/s, without a full simulation.
  • Persistence fraction levels = 0.01%, 0.1%, 1% of primary signal
    Chosen parameter scan values; the 0.1% level defines the pessimistic persistence case (2.1 m/s RV error).
  • IPC coupling fractions alpha, alpha' = alpha = 0.01-0.1, alpha' = 0.02 (WFIRST values)
    Parameter scan and literature values for IPC kernels; central to IPC RV error results.
assumptions (5)
  • domain assumption The HxRG Noise Generator faithfully represents H4RG residual noise after reference pixel subtraction and up-the-ramp sampling.
    Invoked in §3.1; NG is based on NIRSpec H2RG PCA, with adjustments for H4RG. The 37 cm/s read noise result depends on this equivalence.
  • domain assumption The iLocater instrument model is representative of NIR high-resolution RV spectrographs.
    Invoked in §2; all quantitative RV errors are computed using iLocater's bandpass, resolution, sampling, and cross-dispersion.
  • domain assumption All H4RG pixels share the same nonlinearity response curve.
    Invoked in §3.2, based on assertion that variation between pixels is small; if pixel-to-pixel variation is large, the nonlinearity RV error could be larger.
  • domain assumption Persistence decays as 1/t and is proportional to accumulated photons at reset.
    Invoked in §3.4, following Artigau; the 1/t decay and one-minute delay set the persistence fractions used in the RV error estimates.
  • standard math IPC is a fixed linear convolution with the detector frame.
    Invoked in §3.5; the 3x3 and 9x9 kernel models are standard, but IPC spatial variability noted in the discussion is not modeled.

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Cite this review

Pith. "Pith review of Assessing the Suitability of H4RG Near Infrared Detectors for Precise Doppler Radial Velocity Measurements." pith.science (2026). https://pith.science/paper/SI7ZBIFU

@misc{pith2026190811429,
  author       = {Pith},
  title        = {Pith review of: Assessing the Suitability of H4RG Near Infrared Detectors for Precise Doppler Radial Velocity Measurements},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/SI7ZBIFU}},
  note         = {Machine review of arXiv:1908.11429}
}
read the original abstract

At wavelengths longwards of the sensitivity of silicon, hybrid structured mercury-cadmium-telluride (HgCdTe) detectors show promise to enable extremely precise radial velocity (RV) measurements of late-type stars. The most advanced near infrared (NIR) detector commercially available is the HAWAII series (HxRG) of NIR detectors. While the quantum efficiency of such devices has been shown to be approx ninety percent, the noise characteristics of these devices, and how they relate to RV measurements, have yet to be quantified. We characterize the various noise sources generated by H4RG arrays using numerical simulations. We present recent results using our end-to-end spectrograph simulator in combination with the HxRG Noise Generator, which emulates the effects of read noise, parameterized by white noise, correlated and uncorrelated pink noise, alternating column noise, and picture frame noise. The effects of nonlinear pixel response, dark current, persistence, and interpixel capacitance (IPC) on RV precision are also considered. Our results have implications for RV error budgets and instrument noise floors that can be achieved with NIR Doppler spectrographs that utilize this kind of detector.

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Reference graph

Works this paper leans on

42 extracted references · 38 canonical work pages

  1. [1]

    C. D. Dressing and D. Charbonneau , `` The Occurrence of Potentially Habitable Planets Orbiting M Dwarfs Estimated from the Full Kepler Dataset and an Empirical Measurement of the Detection Sensitivity ,'' ApJ 807 , 45 (2015)

    work page 2015

  2. [2]

    R. C. Marchwinski , S. Mahadevan , P. Robertson , et al. , `` Toward Understanding Stellar Radial Velocity Jitter as a Function of Wavelength: The Sun as a Proxy ,'' The Astrophysical Journal 798 , 63 (2015)

    work page 2015

  3. [3]

    Prato , G

    L. Prato , G. N. Mace , E. L. Rice , et al. , `` Radial Velocity Variability of Field Brown Dwarfs ,'' The Astrophysical Journal 808 , 12 (2015)

    work page 2015

  4. [4]

    Mahadevan , L

    S. Mahadevan , L. Ramsey , C. Bender , et al. , `` The habitable-zone planet finder: a stabilized fiber-fed NIR spectrograph for the Hobby-Eberly Telescope ,'' in Ground-based and Airborne Instrumentation for Astronomy IV , Proc. SPIE 8446 , 84461S (2012)

    work page 2012

  5. [5]

    Thibault , P

    S. Thibault , P. Rabou , J.-F. Donati , et al. , `` SPIRou @ CFHT: spectrograph optical design ,'' in Ground-based and Airborne Instrumentation for Astronomy IV , Proc. SPIE 8446 , 844630 (2012)

    work page 2012

  6. [6]

    Quirrenbach , P

    A. Quirrenbach , P. J. Amado , J. A. Caballero , et al. , `` CARMENES: an overview six months after first light ,'' in Ground-based and Airborne Instrumentation for Astronomy VI , Proc. SPIE 9908 , 990812 (2016)

    work page 2016

  7. [7]

    J. R. Crepp , `` Improving planet-finding spectrometers ,'' Science 346 , 809--810 (2014)

    work page 2014

  8. [8]

    Jovanovic , C

    N. Jovanovic , C. Schwab , N. Cvetojevic , et al. , `` Enhancing Stellar Spectroscopy with Extreme Adaptive Optics and Photonics ,'' PASP 128 , 121001 (2016)

    work page 2016

Show all 42 references
  1. [9]

    J. R. Crepp , J. Crass , D. King , et al. , `` iLocater: a diffraction-limited Doppler spectrometer for the Large Binocular Telescope ,'' in Ground-based and Airborne Instrumentation for Astronomy VI , SPIE 9908 , 990819 (2016)

    2016

  2. [10]

    Quirrenbach , P

    A. Quirrenbach , P. J. Amado , I. Ribas , et al. , `` CARMENES: high-resolution spectra and precise radial velocities in the red and infrared ,'' in Ground-based and Airborne Instrumentation for Astronomy VII , Society of Photo-Optical Instrumentation Engineers (SPIE) Conferen...

    2018

  3. [11]

    A. M. Ghez , S. Salim , N. N. Weinberg , et al. , `` Measuring Distance and Properties of the Milky Way's Central Supermassive Black Hole with Stellar Orbits ,'' ApJ 689 , 1044--1062 (2008)

    2008

  4. [12]

    Wizinowich , D

    P. Wizinowich , D. S. Acton , C. Shelton , et al. , `` First Light Adaptive Optics Images from the Keck II Telescope: A New Era of High Angular Resolution Imagery ,'' PASP 112 , 315--319 (2000)

    2000

  5. [13]

    E. B. Bechter, A. J. Bechter, J. R. Crepp, et al. , ``Instrument simulator and data reduction pipeline for the ilocater spectrograph,'' Publications of the Astronomical Society of the Pacific 131 (996), 024504 (2019)

    2019

  6. [14]

    B. J. Rauscher , `` Teledyne H1RG, H2RG, and H4RG Noise Generator ,'' Publications of the Astronomical Society of the Pacific 127 , 1144 (2015)

    2015

  7. [15]

    A. J. Bechter , E. B. Bechter , J. R. Crepp , et al. , `` A radial velocity error budget for single-mode Doppler spectrographs ,'' in Ground-based and Airborne Instrumentation for Astronomy VII , Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series 10702...

    2018

  8. [16]

    Allard , D

    F. Allard , D. Homeier , and B. Freytag , `` Models of very-low-mass stars, brown dwarfs and exoplanets ,'' Philosophical Transactions of the Royal Society of London Series A 370 , 2765--2777 (2012)

    2012

  9. [17]

    B. J. Rauscher , R. G. Arendt , D. J. Fixsen , et al. , ``Principal components analysis of a jwst nirspec detector subsystem,'' Proc.SPIE 8860 , 8860 -- 8860 -- 8 (2013)

    2013

  10. [18]

    B. J. Rauscher, R. G. Arendt, D. J. Fixsen, et al. , ``Improved reference sampling and subtraction: A technique for reducing the read noise of near-infrared detector systems,'' Publications of the Astronomical Society of the Pacific 129 (980), 105003 (2017)

    2017

  11. [19]

    Regan , E

    M. Regan , E. Bergeron , M. Robberto , et al. , `` Determining Detector Temperature using a Self-Calibration Least Squares Process ,'' STScI Technical Report JWST-STScI-001467, SM-12 , 1--11 (2008)

    2008

  12. [20]

    Robberto , `` On the reference pixel correction of NIRCam detectors ,'' STScI Technical Report JWST-STScI-003852, SM-12 , 1--18 (2014)

    M. Robberto , `` On the reference pixel correction of NIRCam detectors ,'' STScI Technical Report JWST-STScI-003852, SM-12 , 1--18 (2014)

    2014

  13. [21]

    A. A. Plazas , C. Shapiro , R. Smith , et al. , `` Nonlinearity and pixel shifting effects in HXRG infrared detectors ,'' Journal of Instrumentation 12 , C04009 (2017)

    2017

  14. [22]

    Biesiadzinski , W

    T. Biesiadzinski , W. Lorenzon , R. Newman , et al. , ``Reciprocity failure in hgcdte detectors: Measurements and mitigation,'' Publications of the Astronomical Society of the Pacific 123 (906), 958--963 (2011)

    2011

  15. [23]

    Artigau , J

    \'E . Artigau , J. Saint-Antoine , P.-L. L \'e vesque , et al. , `` H4RG characterization for high-resolution infrared spectroscopy ,'' in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series , 10709 , 107091P (2018)

    2018

  16. [24]

    C. M. Bacon , Development of long wave infrared detectors for space astronomy . PhD thesis, University of Rochester (2006)

    2006

  17. [25]

    I. S. McLean , Electronic Imaging in Astronomy (2008)

    2008

  18. [26]

    Zandian, M

    M. Zandian, M. Farris, W. McLevige, et al. , ``Performance of science grade hgcdte h4rg-15 image sensors,'' Proc.SPIE 9915 , 9915 -- 9915 -- 11 (2016)

    2016

  19. [27]

    Eric C., M

    P. Eric C., M. William, A. John, et al. , ``Progress in development of h4rg-10 infrared focal plane arrays for wfirst-afta,'' Proc.SPIE 9154 , 9154 -- 9154 -- 8 (2014)

    2014

  20. [28]

    D. N. B. Hall , D. Atkinson , R. Blank , et al. , `` Performance of the first science grade c=2.5 m HAWAII 4RG-15 array in the laboratory and at the telescope ,'' in High Energy, Optical, and Infrared Detectors for Astronomy VII , Proc. SPIE 9915 , 99150W (2016)

    2016

  21. [29]

    J. W. Beletic , R. Blank , D. Gulbransen , et al. , ``Teledyne imaging sensors: infrared imaging technologies for astronomy and civil space,'' Proc.SPIE 7021 , 7021 -- 7021 -- 14 (2008)

    2008

  22. [30]

    R. M. Smith , M. Zavodny , G. Rahmer , et al. , `` Calibration of image persistence in HgCdTe photodiodes ,'' in High Energy, Optical, and Infrared Detectors for Astronomy III , Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series 7021 , 70210K (2008)

    2008

  23. [31]

    R. E. Anderson , M. Regan , J. Valenti , et al. , `` Understanding Persistence: A 3D Trap Map of an H2RG Imaging Sensor ,'' arXiv e-prints , arXiv:1402.4181 (2014)

    2014 arXiv

  24. [32]

    B. A. McLeod and R. Smith , `` Mitigation of H2RG persistence with image illumination ,'' in High Energy, Optical, and Infrared Detectors for Astronomy VII , Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series 9915 , 99150G (2016)

    2016

  25. [33]

    Kannawadi , C

    A. Kannawadi , C. A. Shapiro , R. Mandelbaum , et al. , `` The Impact of Interpixel Capacitance in CMOS Detectors on PSF Shapes and Implications for WFIRST ,'' Publications of the Astronomical Society of the Pacific 128 , 095001 (2016)

    2016

  26. [34]

    Finger , R

    G. Finger , R. Dorn , M. Meyer , et al. , `` Interpixel capacitance in large format CMOS hybrid arrays ,'' in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series , Proc. SPIE 6276 , 62760F (2006)

    2006

  27. [35]

    Hilbert and P

    B. Hilbert and P. McCullough , `` Interpixel Capacitance in the IR Channel: Measurements Made On Orbit ,'' tech. rep. (2011)

    2011

  28. [36]

    B. J. Rauscher , R. G. Arendt , D. J. Fixsen , et al. , `` Principal Component Analysis of Up-the-ramp Sampled IR Array Data ,'' arXiv e-prints , arXiv:1902.02312 (2019)

    2019 arXiv

  29. [37]

    Blank , S

    R. Blank , S. Anglin , J. W. Beletic , et al. , `` H2RG focal plane array and camera performance update ,'' in High Energy, Optical, and Infrared Detectors for Astronomy V , Proc. SPIE 8453 , 845310 (2012)

    2012

  30. [38]

    McCullough , `` Inter-pixel capacitance: prospects for deconvolution ,'' tech

    P. McCullough , `` Inter-pixel capacitance: prospects for deconvolution ,'' tech. rep. (2008)

    2008

  31. [39]

    Donlon, Z

    K. Donlon, Z. Ninkov, and S. Baum, ``Signal dependent interpixel capacitance in hybridized arrays: simulation, characterization, and correction,'' Proc.SPIE 10709 , 10709 -- 10709 -- 8 (2018)

    2018

  32. [40]

    Shapiro , E

    C. Shapiro , E. Huff , and R. Smith , `` Intra-pixel response characterization of a HgCdTe near infrared detector with a pronounced crosshatch pattern ,'' in High Energy, Optical, and Infrared Detectors for Astronomy VIII , Society of Photo-Optical Instrumentation Engineers (S...

    2018

  33. [41]

    Choi and C

    A. Choi and C. M. Hirata , `` Brighter-fatter effect in near-infrared detectors -- II. Auto-correlation analysis of H4RG-10 flats ,'' arXiv e-prints , arXiv:1906.01847 (2019)

    2019 arXiv

  34. [42]

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