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Record W2769251902 · doi:10.1117/12.2304231

METIS-ESA solar orbiter mission internal straylight analysis

2017· article· en· W2769251902 on OpenAlexaboutno aff
Enrico Verroi, G. Naletto, Silvano Fineschi, E. Antonucci, Vania Da Deppo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsStray lightOrbiterPhysicsOpticsMetisTelescopeCoronagraphAstronomyStarsExoplanet

Abstract

fetched live from OpenAlex

METIS is the Multi Element Telescope for Imaging and Spectroscopy for the ESA Solar Orbiter. Its target is the solar corona from a near-Sun orbit in two different spectral bands: the HI UV narrow band at 121.6 nm, and the VL visible light band. METIS adopts a novel inverted externally occulted configuration, where the disk light is shielded by an annular occulter, and an annular aspherical mirror M1 collects the signal coming from the corona. After M1 the coronal light passes through an internal occulter and is then reflected by a second annular mirror M2 toward a narrow filter for the 121.6 nm HI line selection. The visible light reflected by the filter is used to feed a visible light (580 − 640 nm) polarimetric channel. The photospheric light passing through the entrance aperture is back-rejected by a spherical rejection mirror. Since the coronal light is enormously fainter than the photospheric one, a very tough suppression is needed for the internal stray light, in particular the requirement for the stray light suppression is more stringent in the VL than in the UV, because the emission of the corona with respect to the disk emission is different in the two cases, and the requirements are a suppression of at least 10-9 times for the VL and a suppression of at least 10-7 times for the UV channel. This paper presents the stray light analysis for this new coronographic configuration. The complexity of the optomechanical design of METIS, combined with the faintness of the coronal light with respect to the solar disk noise, make a standard ray tracing approach not feasible because it is not sufficient to stop at the first generation of scattered rays in order to check the requirements. Also scattered rays down to the fourth generation must be treated as sources of new scattering light, to analyze the required level of accuracy. If used in a standard ray tracing scattering analysis, this approach is absolutely beyond the computational capabilities today available; therefore we opted for a scattering ray generation with a Montecarlo method in which after a father ray hits a surface, only one ray is generated, randomly selected according to the distribution of the transmitted energy. These rays bring with them all the energy that is otherwise distributed between all the rays of second generation, making the model more realistic and avoiding loss of energy due to the rays sampling. The stray light has been studied in function of the mechanical roughness of the surfaces and the obtained results indicate an instrument stray light blocking performance well within the requirements in both channels.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.010

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.

Opus teacher head0.009
GPT teacher head0.273
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2017
Admission routes1
Has abstractyes

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