Particle monitoring capability of the Solar Orbiter Metis coronagraph through the increasing phase of solar cycle 25
Bibliographic record
Abstract
Context. Galactic cosmic rays (GCRs) and solar particles with energies greater than tens of MeV penetrate spacecraft and instruments hosted aboard space missions. The Solar Orbiter Metis coronagraph is aimed at observing the solar corona in both visible (VL) and ultraviolet (UV) light. Particle tracks are observed in the Metis images of the corona. An algorithm has been implemented in the Metis processing electronics to detect the VL image pixels crossed by cosmic rays. This algorithm was initially enabled for the VL instrument only, since the process of separating the particle tracks in the UV images has proven to be very challenging. Aims. We study the impact of the overall bulk of particles of galactic and solar origin on the Metis coronagraph images. We discuss the effects of the increasing solar activity after the Solar Orbiter mission launch on the secondary particle production in the spacecraft. Methods. We compared Monte Carlo simulations of GCRs crossing or interacting in the Metis VL CMOS sensor to observations gathered in 2020 and 2022. We also evaluated the impact of solar energetic particle events of different intensities on the Metis images. Results. The study of the role of abundant and rare cosmic rays in firing pixels in the Metis VL images of the corona allows us to estimate the efficiency of the algorithm applied for cosmic-ray track removal from the images and to demonstrate that the instrument performance had remained unchanged during the first two years of the Solar Orbiter operations. The outcome of this work can be used to estimate the Solar Orbiter instrument’s deep charging and the order of magnitude for energetic particles crossing the images of Metis and other instruments such as STIX and EUI.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".