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Record W4405280722 · doi:10.3847/1538-3881/ad8eb1

Calibrating the Clock of JWST

2024· article· en· W4405280722 on OpenAlexfundno aff
A. W. Shaw, D. L. Kaplan, P. Gandhi, Thomas J. Maccarone, E. S. Borowski, C. T. Britt, D. A. H. Buckley, Kevin B. Burdge, P. A. Charles, V. S. Dhillon, R. G. French, C. O. Heinke, R. I. Hynes, C. Knigge, S. P. Littlefair, Devraj Pawar, Richard M. Plotkin, Michael E. Ressler, P. Santos-Sanz, T. Shahbaz, G. R. Sivakoff, Abigail Stevens

Bibliographic record

VenueThe Astronomical Journal · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsnot available
FundersScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of CanadaEuropean CommissionUK Research and InnovationSpace Telescope Science InstituteAgencia Estatal de InvestigaciónMinisterio de Ciencia, Innovación y UniversidadesNational Aeronautics and Space Administration
KeywordsPhysicsMeasure (data warehouse)EclipseAstrophysicsAstronomyRemote sensing

Abstract

fetched live from OpenAlex

Abstract JWST, despite not being designed to observe astrophysical phenomena that vary on rapid timescales, can be an unparalleled tool for such studies. If timing systematics can be controlled, JWST will be able to open up the subsecond infrared timescale regime. Rapid time-domain studies, such as lag measurements in accreting compact objects and solar system stellar occultations, require both precise interframe timing and knowing when a time series begins, down to an absolute accuracy significantly below 1 s. In this work, we present two long-duration observations of the deeply eclipsing double white dwarf system ZTF J153932.16+502738.8, which we use as a natural timing calibrator to measure the absolute timing accuracy of JWST's clock. From our two epochs, we measure an average clock accuracy of 0.12 ± 0.06 s, implying that JWST can be used for subsecond time-resolution studies down to the ∼100 ms level, a factor ∼5 improvement upon the prelaunch clock accuracy requirement. We also find an asymmetric eclipse profile in the F322W2 band, which we suggest has a physical origin.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations4
Published2024
Admission routes1
Has abstractyes

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