Combined coronal observations of the streamer belt with Metis and EUI instruments on Solar Orbiter
Bibliographic record
Abstract
Context. Comprehensive solar observations from the limb to the extended corona are essential to study the main processes that connect coronal sources of outflows with the heliosphere. In particular, inferring the temperature structure of the solar corona is important to constrain coronal models and to characterise the mechanisms responsible for the plasma heating and acceleration. However, electron temperature is a parameter that is difficult to obtain from direct measurements in the heliocentric range between 3 and 8 R ⊙ . Aims. The aim of this work is to show the potentiality of a method of inferring the coronal temperature by exploiting unprecedented combined visible light and extreme-ultraviolet (EUV) observations acquired by Metis and by the Full Sun Imager (FSI) telescope of the Extreme Ultraviolet Imager (EUI) on Solar Orbiter. Methods. We analysed coordinated observations performed by the two instruments on March 21, 2021. We combined the first image acquired by FSI in the EUV channel at 17.4 nm using its coronagraphic mode with the visible light polarized brightness (pB) Metis data. The intensities measured by Metis and EUI/FSI originate from physical processes that depend differently on electron density and temperature. We propose a method of combining them, allowing us to place constraints on the electron temperature. The electron density, derived from the inversion of the polarized brightness, was used to calculate the expected counts in the FSI passband based on the instrument response function, which is mainly a function of the electron temperature. From the comparison with the measured counts, we were able to infer two different temperature values, corresponding to the two possible solutions, given the analytical shape of the response function. Results. The electron temperature results at a heliocentric distance of 4.25 R ⊙ (i.e. the average height of the Metis/FSI superposition region of the analysed dataset) are (5.3 −1.5 +2.0 ) · 10 5 K and (1.4 −0.2 +0.3 ) · 10 6 K for the east streamer and (5.7 −1.4 +1.9 ) · 10 5 K and (1.4 −0.3 +0.2 ) · 10 6 K for the west streamer. The values derived from the proposed method are consistent with previous estimates in coronal streamers. Conclusions. For the first time, we have analysed combined coronal observations from EUI and Metis, which has given us a unique opportunity to infer, from their measurements, the physical parameters of the streamer belt. The electron temperature results derived in the present work can be considered as a range of possible values that can constrain this parameter at a coronal height of 4.25 R ⊙ . The proposed method is reasonable within the limits of the validity of the assumptions considered in this work.
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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".