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REVIEW 2 major objections 3 minor 39 references

Feasibility of up-the-ramp sampling under variable sky for ground-based spectrographs

T0 review · 2 major / 3 minor · reviewed 2026-07-03 · grok-4.3

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Pith's one-line read Linear ramp fitting for up-the-ramp sampling remains viable in H-band inter-line regions under variable sky but shows no gain and possible losses in K-band due to thermal shot noise.

desk verdict Targeted Monte Carlo study finds UTR viable in H-band but limited by shot noise in K-band for GIRMOS. read the letter →

arxiv 2606.13600 v3 pith:XQAGRQBJ submitted 2026-06-11 astro-ph.IM

Gaia Gaspar , Marcin Sawicki , Nelson Nunes , Rubén J. Díaz , James E. H. Turner This is my paper · ORCID
classification astro-ph.IM
keywords up-the-rampsamplingvariableskynear-infraredspectrographscosmicrayrejectionH-bandK-bandGIRMOSMonteCarlosimulation
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 tests whether up-the-ramp sampling can be used in ground-based near-infrared spectrographs when sky brightness varies on timescales of minutes. It runs Monte Carlo simulations inside the GIRMOS Data Simulator that incorporate measured K-band sky changes from Mauna Kea and detailed noise budgets. The work finds that H-band read-noise-limited targets in inter-line regions gain 3-4 percent observing time while K-band inter-line regions gain nothing and can lose signal-to-noise because of shot noise from the instrument and telescope. Cosmic-ray rejection still recovers more than 98 percent of events with false-positive rates below 0.1 percent even when the sky varies rapidly. These outcomes matter for choosing readout modes in long-integration infrared instruments that must balance data quality against file size and observing efficiency.

What carries the argument

Monte Carlo assessment of linear ramp fitting viability under measured 10-20 s cadence sky variations using high-fidelity flux budgets.

What would settle it

Direct SNR comparison between real GIRMOS UTR and Fowler-sampled data in K-band inter-line regions under documented sky variability.

Watch

Extended reading notes

Core claim

Using Monte Carlo simulations with the GIRMOS Data Simulator incorporating empirical K-band sky variations from Gemini-NIRI, the study finds that in the H-band the advantages of UTR readout hold for read-noise-limited targets in inter-line regions, yielding 3-4% savings in observing time. In the K-band inter-line regions, UTR does not improve SNR and can degrade it due to shot-noise from thermal emission, but cosmic ray rejection recovers over 98% of events with false positive rates below 0.1% even under high sky variability. Over sky emission lines, UTR performance is compromised by degraded SNR and high false flagging rates.

Load-bearing premise

The sky variations measured from Gemini-NIRI on Mauna Kea are representative of GIRMOS conditions and the simulator captures every relevant noise source.

Editorial extensions

If this is right

  • In H-band inter-line regions, UTR provides 3-4% observing time savings for read-noise-limited targets.
  • K-band inter-line regions show no significant SNR improvement and possible degradation from instrument plus telescope thermal shot noise.
  • Cosmic ray rejection recovers more than 98% of events with false-positive rates below 0.1% under high sky variability.
  • Over sky emission lines, both SNR and cosmic-ray flagging accuracy degrade under rapid sky changes.

Reading between the lines

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

  • Other ground-based NIR spectrographs may adopt band-specific readout choices rather than a uniform UTR policy.
  • If actual sky variability at a given site is lower than the Mauna Kea data used here, K-band UTR benefits could increase.
  • The reported nightly data-volume estimates can guide decisions on storage and transfer infrastructure at similar facilities.
  • The same Monte Carlo framework could be rerun with different integration lengths or detector models to test portability.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

2 major / 3 minor

Summary. The paper presents a Monte Carlo feasibility study for up-the-ramp (UTR) sampling on HAWAII-2RG detectors in ground-based NIR spectrographs, using the GIRMOS Data Simulator with high-fidelity flux budgets and empirical K-band sky variability time series measured at 10-20 s cadence from Gemini-NIRI on Mauna Kea. It evaluates the viability of linear ramp fitting under variable sky, quantifies SNR, systematic biases, and cosmic-ray rejection performance, and estimates data volumes, concluding that UTR yields 3-4% observing-time savings for read-noise-limited targets in H-band inter-line regions but provides no SNR gain (or can degrade performance) in K-band due to thermal shot noise, while cosmic-ray rejection recovers >98% of events with false-positive rates <0.1% even under high variability.

Significance. If the simulation results hold, the study supplies concrete, instrument-specific guidance on when UTR readout is advantageous versus conventional sampling for GIRMOS and similar ground-based NIR spectrographs. The use of empirical sky inputs rather than idealized models, combined with the explicit treatment of both inter-line and on-line regions plus nightly data-volume estimates, makes the findings directly actionable for observing strategy and pipeline design. The reported cosmic-ray rejection statistics under realistic variability are a particular strength.

major comments (2)
  1. [Abstract] Abstract: the central quantitative claims (3-4% time savings in H-band inter-line regions; >98% CR recovery with <0.1% false positives) are stated without reported uncertainties, Monte Carlo error bars, or sensitivity tests to the two free parameters (number of reads per ramp; sky variation amplitude). Because these percentages are the primary feasibility metrics, the absence of robustness checks is load-bearing for the strength of the conclusions.
  2. [Methods / Results (Monte Carlo workflow)] The manuscript does not report an explicit validation that the linear-ramp model remains an adequate description once the empirical NIRI sky-variability time series are injected; any residual non-linearity would directly affect the reported SNR and bias values.
minor comments (3)
  1. [Results] The definition of 'inter-line regions' and the precise wavelength intervals used for the H- and K-band statistics should be stated explicitly, ideally with a figure or table reference.
  2. [Figures] Figure captions and axis labels should indicate whether the plotted SNR values are per-resolution-element or per-pixel and whether they include the reported cosmic-ray rejection step.
  3. [Discussion] The nightly data-volume estimates would benefit from a short table comparing UTR versus Fowler sampling for representative numbers of reads and exposure times.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the positive assessment and for identifying two areas where additional quantification would strengthen the conclusions. We address each major comment below and will incorporate the requested robustness checks and validation steps in the revised manuscript.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the central quantitative claims (3-4% time savings in H-band inter-line regions; >98% CR recovery with <0.1% false positives) are stated without reported uncertainties, Monte Carlo error bars, or sensitivity tests to the two free parameters (number of reads per ramp; sky variation amplitude). Because these percentages are the primary feasibility metrics, the absence of robustness checks is load-bearing for the strength of the conclusions.

    Authors: We agree that the absence of reported uncertainties and sensitivity tests weakens the presentation of the key metrics. In the revised manuscript we will (i) report Monte Carlo standard errors on the 3–4 % time-savings figure and on the cosmic-ray recovery/false-positive rates, (ii) add a short sensitivity study that varies the number of reads per ramp (30–60) and the amplitude of the injected sky-variability time series, and (iii) update the abstract to include these error bars and the range of parameter values tested. revision: yes

  2. Referee: [Methods / Results (Monte Carlo workflow)] The manuscript does not report an explicit validation that the linear-ramp model remains an adequate description once the empirical NIRI sky-variability time series are injected; any residual non-linearity would directly affect the reported SNR and bias values.

    Authors: The GIRMOS Data Simulator was constructed under the standard assumption that H2RG pixels respond linearly within the flux and integration-time regime used for GIRMOS (see instrument documentation and prior HAWAII-2RG characterization papers). Nevertheless, the referee is correct that an explicit check against the injected empirical sky series is not presented. We will add a dedicated paragraph (and accompanying figure) that quantifies the residual non-linearity after ramp fitting by (a) comparing the recovered slopes with and without the NIRI variability time series and (b) injecting a small quadratic term consistent with published H2RG non-linearity curves to confirm that the reported SNR and bias values remain unchanged within the Monte Carlo uncertainties. revision: yes

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity

full rationale

The paper is a Monte Carlo feasibility study that injects external empirical sky-variability time series (from Gemini-NIRI) into a pre-existing GIRMOS Data Simulator. All reported SNR values, bias estimates, and cosmic-ray rejection statistics are direct outputs of that external-input simulation workflow; no central claim is obtained by fitting a parameter inside the paper and then relabeling it as a prediction, nor does any derivation reduce to a self-citation chain or self-definitional equation. The study is therefore self-contained against external benchmarks.

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

The study relies on external empirical sky measurements and a pre-existing simulator rather than new fitted parameters or postulated entities. The Monte Carlo tests use these inputs to evaluate the feasibility claim without introducing additional free parameters beyond the reported read counts and integration times.

free parameters (2)
  • number of reads per ramp
    Typical values of 30-60 reads are used for long integrations; these are chosen from standard H2RG practice rather than fitted to new data.
  • sky variation amplitude
    3-10% on minute timescales taken directly from Gemini-NIRI empirical measurements; treated as input rather than fitted inside the study.
assumptions (2)
  • domain assumption Detector response remains linear over the full integration ramp
    Invoked as the basis for linear ramp fitting in UTR sampling; stated in the context of assessing viability under variable sky.
  • domain assumption Sky brightness variations are statistically independent of other noise sources in the Monte Carlo realizations
    Used to isolate the effect of sky variability on ramp fitting and cosmic-ray rejection.

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Cite this review

Pith. "Pith review of Feasibility of up-the-ramp sampling under variable sky for ground-based spectrographs." pith.science (2026). https://pith.science/paper/XQAGRQBJ

@misc{pith2026260613600,
  author       = {Pith},
  title        = {Pith review of: Feasibility of up-the-ramp sampling under variable sky for ground-based spectrographs},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XQAGRQBJ}},
  note         = {Machine review of arXiv:2606.13600}
}
abstract

Many modern near-infrared instruments employ HAWAII-2RG (H2RG) detectors with integration times that can reach 300-600s. Up-the-ramp (UTR) sampling offers advantages over Fowler sampling, including superior cosmic ray rejection and noise reduction, but requires fitting linear ramps from 30-60 reads. Ground-based K-band sky brightness has been reported to vary by 3-10% on timescales of minutes, potentially introducing systematic errors and compromising photometric accuracy. Additionally, UTR data formats involve higher-dimensional FITS files with larger file sizes impacting observatory operations. We present a feasibility study using the GIRMOS Data Simulator with high-fidelity flux budgets and empirical K-band sky variations estimated, for Mauna Kea, from Gemini-NIRI at 10-20s cadence. Using a Monte Carlo approach we assess whether linear ramp fitting remains viable under variable sky conditions, quantify SNRs and systematic biases, and report nightly data volume estimates. Our results show that, in the H-band, the advantages of the UTR readout hold for read-noise-limited targets placed in the inter-line regions, translating into 3-4% savings in observing time. The K-band inter-line regions do not show significant SNR improvement and can even degrade it due to the dominance of shot-noise generated by the thermal emission of the instrument+telescope system. In these regions, cosmic ray rejection recovers $>$ 98% of events with false positive rates below 0.1%, even under high sky variability. Over the sky emission lines, UTR fitting remains possible but its performance is compromised, both by a degradation in SNR and by a high rate of pixels falsely flagged by the cosmic ray rejection algorithm under highly variable sky. These findings address how ground-based conditions affect UTR implementation in near-infrared spectrographs, with GIRMOS as a concrete case of study.

Figures

Figures reproduced from arXiv: 2606.13600 by the authors.

Figure 1
Figure 1. K-band sky brightness variation measured from NIRI observations over [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Noiseless simulated spectra used in this work for the two available GIRMOS resolving powers: R3000 (top [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. Per pixel statistical analysis for the comparison of the MCDS-8 and UTR readout modes for the R3000 [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
Figures from the paper (9 more)
Figure 3
Figure 3. Figure 3: Per-pixel count-rate bias, in percent of the MCDS-8 value for the combined continuum regions (solid histograms), [PITH_FULL_IMAGE:figures/full_fig_p008_3.png]
Figure 4
Figure 4. Figure 4: Same as Figure [PITH_FULL_IMAGE:figures/full_fig_p009_4.png]
Figure 4
Figure 4. Figure 4: Per-pixel median SNR improvement between UTR and MCDS-8 readout modes; values above zero indicate that [PITH_FULL_IMAGE:figures/full_fig_p008_4.png]
Figure 5
Figure 5. Figure 5: False-positive map zoomed into the detector regions analyzed in this work. Colored pixels mark false positive [PITH_FULL_IMAGE:figures/full_fig_p011_5.png]
Figure 5
Figure 5. Figure 5: Region median per-pixel of the ratio between shot-noise and readout-noise. Grey error bars show the 16th–84th [PITH_FULL_IMAGE:figures/full_fig_p009_5.png]
Figure 6
Figure 6. Figure 6: Histograms of selected thresholds per amplifier for the two resolution modes. The thresholds are calculated to [PITH_FULL_IMAGE:figures/full_fig_p012_6.png]
Figure 6
Figure 6. Figure 6: Mean false positive and CR recovery rates for a sweep of sky pulses between 8% (the baseline case presented [PITH_FULL_IMAGE:figures/full_fig_p011_6.png]
Figure 7
Figure 7. Figure 7: Left and middle panels: Examples of CR events that are common to the two constructed libraries. The cutouts [PITH_FULL_IMAGE:figures/full_fig_p015_7.png]
Figure 7
Figure 7. Figure 7: Left and middle panels: Examples of CR events that are common to the two constructed libraries. The cutouts [PITH_FULL_IMAGE:figures/full_fig_p014_7.png]

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Works this paper leans on

39 extracted references · 39 canonical work pages

  1. [1]

    Analysis of the sampling schemes for WFC3-IR

    Robberto, M., “Analysis of the sampling schemes for WFC3-IR.” Instrument Science Report WFC3 2007-12, 27 pages (Jan. 2007)

    work page 2007

  2. [2]

    Detectors for the james webb space telescope near-infrared spectrograph. i. readout mode, noise model, and calibration considerations,

    Rauscher, B. J., Fox, O., Ferruit, P., Hill, R. J., Waczynski, A., Wen, Y., Xia-Serafino, W., Mott, B., Alexander, D., Brambora, C. K., Derro, R., Engler, C., Garrison, M. B., Johnson, T., Manthripragada, S. S., Marsh, J. M., Marshall, C., Martineau, R. J., Shakoorzadeh, K. B., Wilson, D., Roher, W. D., Smith, M., Cabelli, C., Garnett, J., Loose, M., Wong...

    work page 2007

  3. [3]

    Nonlinearity corrections and statistical uncertainties associated with near-infrared arrays,

    Vacca, W. D., Cushing, M. C., and Rayner, J. T., “Nonlinearity corrections and statistical uncertainties associated with near-infrared arrays,”Publications of the Astronomical Society of the Pacific116, 352 (apr 2004)

    work page 2004

  4. [4]

    Demonstration of an Algorithm for Read-Noise Reduction in Infrared Arrays,

    Fowler, A. M. and Gatley, I., “Demonstration of an Algorithm for Read-Noise Reduction in Infrared Arrays,” Astrophysical Journal353, L33 (Apr. 1990)

    work page 1990

  5. [5]

    Optimization of the multiple sampling and signal extraction in nondestructive exposures,

    Kubik, B., Barbier, R., Castera, A., Chabanat, E., Ferriol, S., and Smadja, G., “Optimization of the multiple sampling and signal extraction in nondestructive exposures,”Journal of Astronomical Telescopes, Instruments, and Systems1, 038001 (July 2015)

    work page 2015

  6. [6]

    Optimal fitting and debiasing for detectors read out up-the-ramp,

    Brandt, T. D., “Optimal fitting and debiasing for detectors read out up-the-ramp,”Publications of the Astronomical Society of the Pacific136, 045004 (may 2024)

    work page 2024

  7. [7]

    A quasi-optimal stacking method for up-the-ramp readout images,

    Wang, G., Zhan, H., Luo, Z., Liu, C., Xu, Y., Lin, C., Wei, Y., and Fan, W., “A quasi-optimal stacking method for up-the-ramp readout images,”Astronomical Techniques and Instruments2(2), 119–126 (2025)

    work page 2025

  8. [8]

    Reprocessing WFC3/IR Exposures Affected by Time-Variable Backgrounds

    Brammer, G., “Reprocessing WFC3/IR Exposures Affected by Time-Variable Backgrounds.” Instrument Science Report WFC3 2016-16, 12 pages (Nov. 2016)

    work page 2016

Show all 39 references
  1. [9]

    Wfc3/ir starter guide,

    McCullough, P. R. and Green, J. D., “Wfc3/ir starter guide,” (2025)

    2025

  2. [10]

    The Near-Infrared Spectrograph (NIRSpec) on the James Webb Space Telescope. III. Integral-field spectroscopy,

    B¨ oker, T., Arribas, S., L¨ utzgendorf, N., Alves de Oliveira, C., Beck, T. L., Birkmann, S., Bunker, A. J., Charlot, S., de Marchi, G., Ferruit, P., Giardino, G., Jakobsen, P., Kumari, N., L´ opez-Caniego, M., Maiolino, R., Manjavacas, E., Marston, A., Moseley, S. H., Muzero...

    2022

  3. [11]

    The Habitable-Zone Planet Finder: improved flux image generation algorithms for H2RG up-the-ramp data,

    Ninan, J. P., Bender, C. F., Mahadevan, S., Ford, E. B., Monson, A. J., Kaplan, K. F., Terrien, R. C., Roy, A., Robertson, P. M., Kanodia, S., and Stefansson, G. K., “The Habitable-Zone Planet Finder: improved flux image generation algorithms for H2RG up-the-ramp data,” in [Hi...

    2018

  4. [12]

    Making SPIFFI SPIFFIER: upgrade of the SPIFFI instrument for use in ERIS and per- formance analysis from re-commissioning,

    George, E. M., Gr¨ aff, D., Feuchtgruber, H., Hartl, M., Eisenhauer, F., Buron, A., Davies, R., Genzel, R., Huber, H., Rau, C., Plattner, M., Wiezorrek, E., Weisz, H., Amico, P., Glindemann, A., Hau, G., and Kuntschner, H., “Making SPIFFI SPIFFIER: upgrade of the SPIFFI instru...

    2016

  5. [13]

    Data reduction pipeline for the CHARIS integral-field spectrograph I: detector readout calibration and data cube extraction,

    Brandt, T. D., Rizzo, M., Groff, T., Chilcote, J., Greco, J. P., Kasdin, N. J., Limbach, M. A., Galvin, M., Loomis, C., Knapp, G., McElwain, M. W., Jovanovic, N., Currie, T., Mede, K., Tamura, M., Takato, N., and Hayashi, M., “Data reduction pipeline for the CHARIS integral-fi...

    2017

  6. [14]

    Non-thermal emission in the atmosphere above mauna kea,

    Ramsay, S. K., Mountain, C. M., and Geballe, T. R., “Non-thermal emission in the atmosphere above mauna kea,”Monthly Notices of the Royal Astronomical Society259, 751–760 (12 1992)

    1992

  7. [15]

    Preliminary results of sky brightness measurements in near- infrared at Lenghu, China,

    Li, J., Ma, B., Dong, Z., and Zhang, H., “Preliminary results of sky brightness measurements in near- infrared at Lenghu, China,” in [Ground-based and Airborne Telescopes X], Marshall, H. K., Spyromilio, J., and Usuda, T., eds.,13094, 130945C, International Society for Optics ...

    2024

  8. [16]

    The final design of the Gemini Infrared Multi-Object Spectro- graph: Gemini’s new adaptive optics facility instrument,

    Sivanandam, S., Chapman, S., Muzzin, A., Christie, S., Hickson, P., McConnachie, A., Thibault, S., Atwood, J., Anthony, A., Sawicki, M., Dunn, J., Lee, J.-J., Venn, K., Diaz, R., Goodsell, S., Barbod, S., Tschimmel, M., Barnet, M., Hay, G., Roberts, S., Sivo, G., Lamb, M., Che...

    2024

  9. [17]

    Gemini North Adaptive Optics (GNAO) facility overview and status updates,

    Sivo, G., Scharw¨ achter, J., Lazo, M., Blain, C., Goodsell, S., van Dam, M., Tschimmel, M., Roe, H., Lotz, J., Tomassino-Reed, K., Rambold, W., Raich, C., Cardenes, R., Ebbers, A., Gaggstatter, T., Gigoux, P., Schneider, T., Cavedoni, C., Kang, S., Karewicz, S., Carr, H., Bal...

    2022

  10. [18]

    Simulations of sample-up-the-ramp for space-based obser- vations of faint sources,

    Benford, D. J., Lauer, T. R., and Mott, D. B., “Simulations of sample-up-the-ramp for space-based obser- vations of faint sources,” in [High Energy, Optical, and Infrared Detectors for Astronomy III], Dorn, D. A. and Holland, A. D., eds.,7021, 70211V, International Society for...

    2008

  11. [19]

    Simple improved reference subtraction for H4RG, H2RG, and H1RG near-infrared array detectors,

    Rauscher, B. J., Fixsen, D. J., and Mosby, G., “Simple improved reference subtraction for H4RG, H2RG, and H1RG near-infrared array detectors,”Journal of Astronomical Telescopes, Instruments, and Systems8(2), 028002 (2022)

    2022

  12. [20]

    Observations of the oh airglow emission,

    Maihara, T., Iwamuro, F., Yamashita, T., Hall, D. N. B., Cowie, L. L., Tokunaga, A. T., and Pickles, A., “Observations of the oh airglow emission,”Publications of the Astronomical Society of the Pacific105, 940 (sep 1993)

    1993

  13. [21]

    A calibrated measurement of the near-ir continuum sky brightness using magellan/fire,

    Sullivan, P. W. and Simcoe, R. A., “A calibrated measurement of the near-ir continuum sky brightness using magellan/fire,”Publications of the Astronomical Society of the Pacific124, 1336 (nov 2012)

    2012

  14. [22]

    The Sites: Infrared Sky Background and IR Transmission Spectra

    Gemini Observatory, “The Sites: Infrared Sky Background and IR Transmission Spectra.” Gemini Observa- tory web page: https://www2.gemini.edu/observing/telescopes-and-sites/sites (2026). Accessed 2026-05-13

    2026

  15. [23]

    An Overview of the Gemini Infrared Multi-Object Spectrograph Performance Budgets,

    Lamb, M. P., Sivanandam, S., Tschimmel, M., Muzzin, A., McConnachie, A., Scharwachter, J., Sivo, G., Atwood, J., Chapman, S., Christie, S., Barnet, M., Hickson, P., and Herriot, G., “An Overview of the Gemini Infrared Multi-Object Spectrograph Performance Budgets,” in [Modelin...

    2022

  16. [24]

    Performance Update of the Combined GNAO+GIRMOS Imaging System Based on the Newly-Derived Adaptive Optics Bench,

    Lamb, M., Sivo, G., Sivanandam, S., Tschimmel, M., Scharwachter, J., McConnachie, A., Muzzin, A., Jouve, P., and Correia, C., “Performance Update of the Combined GNAO+GIRMOS Imaging System Based on the Newly-Derived Adaptive Optics Bench,” in [Adaptive Optics Systems IX], Jack...

    2024

  17. [25]

    GIRMOS Performance-Budget Inputs,

    Lamb, M. P., “GIRMOS Performance-Budget Inputs,” (2025). Private communication

    2025

  18. [26]

    A New Software Tool for Computing Earth’s Atmospheric Transmission of Near- and Far- Infrared Radiation,

    Lord, S. D., “A New Software Tool for Computing Earth’s Atmospheric Transmission of Near- and Far- Infrared Radiation,” NASA Technical Memorandum 103957, NASA Ames Research Center (1992)

    1992

  19. [27]

    Object-Oriented Matlab Adaptive Optics Toolbox,

    Conan, R. and Correia, C., “Object-Oriented Matlab Adaptive Optics Toolbox,” in [Adaptive Optics Systems IV], V´ eran, J.-P., Marchetti, E., and Close, L. M., eds.,Proceedings of SPIE9148, 91486C, SPIE (2014)

    2014

  20. [28]

    TIPTOP: A New Tool to Efficiently Predict Your Favorite AO PSF,

    Neichel, B., Beltramo-Martin, O., Plantet, C., Rossi, F., Agapito, G., Fusco, T., Carolo, E., Carla, G., Cirasuolo, M., and van der Burg, R., “TIPTOP: A New Tool to Efficiently Predict Your Favorite AO PSF,” in [Adaptive Optics Systems VII], Schreiber, L., Schmidt, D., and Ver...

    2020

  21. [29]

    The Adaptive Optics System for the Gemini Infrared Multi-Object Spectrograph: Performance Modeling,

    Conod, U., Jackson, K., Turri, P., Chapman, S., Lardi` ere, O., Lamb, M., Correia, C., Sivo, G., Sivanandam, S., and V´ eran, J.-P., “The Adaptive Optics System for the Gemini Infrared Multi-Object Spectrograph: Performance Modeling,”Publications of the Astronomical Society of...

    2023

  22. [30]

    Multi-Object Adaptive Optics for GIRMOS: Final Design, Risks Mitigation, and Science Performance,

    Conod, U., Jackson, K., Lardi` ere, O., V´ eran, J.-P., et al., “Multi-Object Adaptive Optics for GIRMOS: Final Design, Risks Mitigation, and Science Performance,” in [Adaptive Optics Systems IX], Jackson, K. J., Schmidt, D., and Vernet, E., eds.,Proceedings of SPIE13097, 1309...

    2024

  23. [31]

    Results from the commissioning of the Gemini South Adaptive Optics Imager (GSAOI) at Gemini South Observatory,

    Carrasco, E. R., Edwards, M. L., McGregor, P. J., Winge, C., Young, P. J., Doolan, M. C., van Harmelen, J., Rigaut, F. J., Neichel, B., Trancho, G., Artigau, E., Pessev, P., Colazo, F., Tigner, J., Mauro, F., L¨ uhrs, J., and Rambold, W. N., “Results from the commissioning of ...

    2012

  24. [32]

    Cosmic Rays and Other Nonsense in Astronomical CCD Imagers,

    Groom, D., “Cosmic Rays and Other Nonsense in Astronomical CCD Imagers,” in [Scientific Detectors for Astronomy, The Beginning of a New Era], Amico, P., Beletic, J. W., and Belectic, J. E., eds.,Astrophysics and Space Science Library300, 81–93 (Jan. 2004)

    2004

  25. [33]

    Likelihood-based jump detection and cosmic ray rejection for detectors read out up-the- ramp,

    Brandt, T. D., “Likelihood-based jump detection and cosmic ray rejection for detectors read out up-the- ramp,”Publications of the Astronomical Society of the Pacific136, 045005 (may 2024)

    2024

  26. [34]

    The SINS/zC-SINF Survey of z∼2 Galaxy Kinematics: SINFONI Adaptive Optics-assisted Data and Kiloparsec-scale Emission-line Properties,

    F¨ orster Schreiber, N. M., Renzini, A., Mancini, C., Genzel, R., Bouch´ e, N., Cresci, G., Hicks, E. K. S., Lilly, S. J., Peng, Y., Burkert, A., Carollo, C. M., Cimatti, A., Daddi, E., Davies, R. I., Genel, S., Kurk, J. D., Lang, P., Lutz, D., Mainieri, V., McCracken, H. J., ...

    2018

  27. [35]

    Multiply sampled read-limited and background-limited noise perfor- mance,

    Garnett, J. D. and Forrest, W. J., “Multiply sampled read-limited and background-limited noise perfor- mance,” in [Infrared Detectors and Instrumentation], Fowler, A. M., ed.,1946, 395 – 404, International Society for Optics and Photonics, SPIE (1993)

    1946

  28. [36]

    JWST NIRSpec’s Cosmic Ray Experience at L2,

    Rauscher, B. J. and Fixsen, D., “JWST NIRSpec’s Cosmic Ray Experience at L2,”Publications of the Astronomical Society of the Pacific137(9), 095003 (2025)

    2025

  29. [37]

    A Library of Simulated Cosmic Ray Events Impacting JWST HgCdTe Detectors,

    Robberto, M., “A Library of Simulated Cosmic Ray Events Impacting JWST HgCdTe Detectors,” Tech. Rep. Technical Report JWST-STScI-001928, STScI (2010)

    2010

  30. [38]

    Random telegraph signal (RTS) in the Euclid IR H2RGs,

    Kohley, R., Barbier, R., Cl´ emens, J.-C., Conversi, L., Crouzet, P.-E., Ealet, A., Ferriol, S., Gillard, W., Kubik, B., Rosset, C., Secroun, A., Serra, B., and Strada, P., “Random telegraph signal (RTS) in the Euclid IR H2RGs,” in [High Energy, Optical, and Infrared Detectors...

    2018

  31. [39]

    Characterization of random telegraph noise in an H2RG X-ray hybrid CMOS detector,

    Bevidas, W. A. J., Colosimo, J. M., Falcone, A. D., Emeigh, T., Stone, L. R., Nizam, K. M., Bortree, B., Buffington, J. C., Burrows, D. N., Catlin, Z. E., Gremling, K. M., Hossen, M. A., Reichard, C., Scigliani, A. C., Tavana, A. J., and Wages, M., “Characterization of random ...

    2025

Pith tools

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