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Record W2995840624 · doi:10.1117/1.jatis.6.1.011006

Astrometric errors introduced by interpixel capacitive coupling in hybridized arrays

2020· preprint· en· W2995840624 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Astronomical Telescopes Instruments and Systems · 2020
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicScientific Research and Discoveries
Canadian institutionsUniversity of Manitoba
FundersEuropean Space AgencySpace Telescope Science InstituteNational Aeronautics and Space Administration
KeywordsPixelDeconvolutionCapacitive couplingCapacitanceCoupling (piping)PhysicsOpticsPoint spread functionSIGNAL (programming language)Computer scienceMaterials scienceVoltageElectrode

Abstract

fetched live from OpenAlex

Interpixel capacitance (IPC) between adjacent pixels in hybridized arrays gives rise to an electrostatic cross talk. This cross talk causes MTF degradation and blurring of images or spectra collected using these devices. As pixel size is driven down from the 18-μm pixel pitch of the H2RG read out circuits to the 10- or 15-μm H4RGs IPC is driven up resulting in greater cross talk, all else being equal. Mounting evidence indicates that IPC varies as a function of depletion state of the photo-active diodes. For single pixel events, increasing the event intensity corresponds to a decreasing fractional coupling. If left uncorrected, IPC can give rise to systematic errors in precision astrometric and photometric measurements, in particular when dealing with confused point sources or spatially extended structures for shape measurements as demonstrated through comparison of registered sources from ESO HAWK-I and HST ACS WFC datasets. Furthermore, these errors will be the most significant when operating near the sensitivity limit of these devices. Deconvolution-based correction methods are invalidated by this same signal dependence. Instead, a numerical method of successive approximation can be used to correct coupling due to a well-characterized IPC. Examination of single pixel reset data above flat fields could be used to characterize IPC’s functional relationship for neighboring pixels. This higher quality characterization can result in more accurate correction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.279
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it