Définition et implémentation des corrections instrumentales de la mission spatiale CoRoT
Bibliographic record
Abstract
CoRoT (Convection, Rotation and planetary Transits) is a space mission conceived to the stellar seismology and the search of extra solar planets. Both scientific programs are based on very high precision photometry and require long and uninterrupted observations. For the study of the stellar oscillations, the instrument must be able to measure periodic variations of the order of ten parts per million on some stars of apparent magnitudes ranging from 5.4 to 9.5. For the exoplanet finding, based on the method of planetary transits, the goal is to detect the temporary occultation of the star by the orbiting planet, which results in a weak reduction in the collected stellar flux. For this purpose, the instrument is designed to observe simultaneously several thousands of stars, of apparent magnitudes between 12 and 15.5, and to detect occultation of luminosity as small as a thousand of parts per million.To reach this level of performance, the on board and ground data reductions must be optimized, ensuring the respect of the scientific and technical project constraints. In his context, this thesis plays a very important role on the final photometric performance of the instrument. On the one hand, it defines the on board optimum photometric masks for the asteroseismology channel. These photometric apertures define in an irremediableway the quality of the data that will be treated on the ground. On the other hand, it treats one of the most important ground corrections to reach the photometric performances of both scientific programs: the photometric correction due to the satellite attitude fluctuations (jitter).To approach these two topics this thesis initially describes the CoRoT project and its scientific goals. The main concepts necessary to the comprehension of the origin of the problems dealt with here are presented. The theory of the photometric ground correction for satellite jitter effects is developed and the first validation results obtained on the test bench are shown. Then we describe the jitter reconstitution of each star observed by CoRoT. That is necessary to calculations of jitter photometric corrections. To finalize the theoretical part the development of the optimum mask calculation and its simulation results are presented.The last chapter shows the results obtained on the on-orbit data from a Canadian satellite called MOST, and then it shows the results obtained on the CoRoT on-orbit data. The qualities of both CoRoT on-orbit data and corrections proposed by this work are confirmed. These corrections prove to be an essential step to reach the specified photometric performances.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".