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Analysis of Dark Current in BRITE Nanostellite CCD Sensors

2018· preprint· en· W3124427358 on OpenAlexfundno aff
Adam Popowicz

Bibliographic record

VenuePreprints.org · 2018
Typepreprint
Languageen
FieldEngineering
TopicCCD and CMOS Imaging Sensors
Canadian institutionsnot available
FundersCanadian Space AgencyKarl-Franzens-Universität GrazUniversität WienUniversity of TorontoÖsterreichische ForschungsförderungsgesellschaftMinisterstwo Edukacji i NaukiFundacja na rzecz Nauki Polskiej
KeywordsDark currentSkyPixelProtonNormalization (sociology)PhysicsOpticsOptoelectronicsDetectorAstronomyNuclear physics

Abstract

fetched live from OpenAlex

The BRightest Target Explorer (BRITE) is the pioneering nanosatellite mission dedicated for photometric observations of the brightest stars in the sky. The BRITE CCD sensors are poorly shielded against extensive flux of energetic particles which constantly induce defects in the silicon lattice. In this paper we investigate the temporal evolution of the generation of the dark current in the BRITE CCDs over almost 4 years after launch. Utilizing several steps of image processing and employing normalization of the results it was possible to obtain useful information about the progress of thermal activity in the sensors. The outcomes show clear and consistent linear increase of induced damage despite the fact that only about 0.14% of CCD pixels were probed. By performing the analysis of temperature dependencies of the dark current, we identified the observed defects as phosphorus-vacancy (PV) pairs, which are common in proton irradiated CCD matrices. Moreover, the Meyer-Neldel empirical rule was confirmed in our dark current data, yielding EMN=24.8 meV for proton-induced PV defects.

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.

How this classification was reachedexpand

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.065
GPT teacher head0.322
Teacher spread0.258 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2018
Admission routes1
Has abstractyes

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