In-flight radiometric calibration of the Metis UV H I Ly-α channel and comparison with UVCS data
Bibliographic record
Abstract
Context. We present the results of the in-flight radiometric calibration performed for the ultraviolet (UV) H I Ly-α channel of the Metis coronagraph on board Solar Orbiter. Aims. The radiometric calibration is a fundamental procedure required to produce data in physical units. The quantity that allows us to pass from raw data into calibrated data is the radiometric calibration factor, ϵ<SUB>UV</SUB>. Methods. To obtain the ϵ<SUB>UV</SUB> results, we used observations of stellar targets transiting the Metis field of view. We derived ϵ<SUB>UV</SUB> by determining the signal of each calibration star by means of the aperture photometry and evaluating its expected flux in the Metis narrow bandpass (121.6 ± 10 nm). The analyzed data cover a time range from the beginning of the Cruise Phase in June 2020, up until August 2021. Results. We find that the UV channel requires a significant additional correction of the response across the field of view, compared to that provided by the vignetting function measured on the ground and refined in flight, specifically tailored to the UV channel. This correction is provided by the ratio of images of the back-illumination of the closed door. Here, we use the stellar measurements to refine and improve such a correction map. After correcting for the spatial disuniformity, a radiometric calibration factor ϵ̅<SUB>UV</SUB> = 0.20 ± 0.03 DN/photon was found. No significant changes in the UV channel throughput were observed during the period from June 2020 to August 2021. In addition, the analysis of a smaller number of stars observed in 2022 and 2023 enabled us to extend the validity of the radiometric calibration to that period, after considering a suitable scaling factor due to the change of operating voltages occurred in April 2022. From this second analysis, the value of the radiometric calibration factor is ϵ̅<SUB>UV</SUB> = 0.11 ± 0.03 DN/photon. In order to support the radiometric calibration results, we performed a comparison between average radial profiles of the H I Ly-α intensity obtained from Metis UV images acquired in 2020─2021 and those measured with the Ultra-Violet Coronagraph Spectrometer (UVCS) on board the Solar and Heliospheric Observatory (SOHO) during the period of the activity minimum of solar cycle 22 in 1996. We found that intensity profiles of these instruments are consistent with each other.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".