Tomography of the Solar Corona with the Metis Coronagraph I: Predictive Simulations with Visible Light Images
Bibliographic record
Abstract
Abstract The Metis coronagraph of the Solar Orbiter (SolO) mission records full-Sun images of the solar corona in Lyman-α ultraviolet (UV) radiation and in visible light polarized brightness (pB). This work investigates the utility of a synoptic observational program of Metis in terms of using its pB-images for tomographic reconstruction of the three-dimensional (3D) distribution of the electron density of the global solar corona. During its lifetime, SolO’s distance to the Sun will range D ≈ 0.3−1.0 au, while its solar latitude will span θ ≈ ±33 •. The limitations that such orbit complexity poses on tomographic reconstructions is explored in this work. Using SolO’s predictive orbital information and 3D MHD simulations of the solar corona, time series of synthetic Metis pB-images were computed and used as data to attempt tomographic reconstruction of the model. These numerical experiments were implemented for two Carrington rotations, corresponding to a solar minimum and a solar maximum, representative of extreme conditions of coronal complexity. For each rotation images were synthesized from three orbital segments, corresponding to extreme geometrical conditions of observation by Metis. For the early phase of the mission (year 2023), simulations were carried from the largest aphelion (D ≈ 0.95 au) and the smallest perihelion (D ≈ 0.29 au), both cases corresponding to low latitude (|θ| < 10 •) positions. For the late phase of the mission (year 2029), a simulation was carried out from the maximum solar latitude position (θ ≈ +33 •), at an intermediate distance (D ≈ 0.5 au). The range of heights that can be reconstructed and the required data-gathering time, both dependent on D, are reported for the six experiments. The extension of the coronal region that can be reconstructed and the accuracy of the reconstruction, both decreasing with increasing solar latitude |θ| as well as with increasing coronal complexity, are discussed in detail in each case. As a general conclusion, a Metis synoptic observational program with a cadence of at least 4 images/day provides enough data to attempt tomographic reconstructions of the coronal electron density during the whole lifetime of the mission, a requirement well within the 2 − 3 hr cadence of the current synoptic program. This program will allow implementation of tomography experimenting with different values for the cadence of the time-series of images used to feed reconstructions. Its cadence will also provide continuous opportunity to select images avoiding highly dynamic events, which compromise the accuracy of tomographic reconstructions.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".