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Record W1627484068 · doi:10.1051/0004-6361/201525664

Collisional modelling of the AU Microscopii debris disc

2015· article· en· W1627484068 on OpenAlexaff
Ch. Schüppler, T. Löhne, A. V. Krivov, Steve Ertel, J. P. Marshall, S. Wolf, M. C. Wyatt, J.‐C. Augereau, Stanimir Metchev

Bibliographic record

VenueAstronomy and Astrophysics · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Optical Sensing Technologies
Canadian institutionsWestern University
FundersNational Science CouncilUniversity of New South WalesDeutsche ForschungsgemeinschaftNational Astronomical Observatory of JapanEuropean CommissionNational Institutes of Natural SciencesAgence Nationale de la RechercheNational Radio Astronomy ObservatoryEuropean Research CouncilNational Science Foundation
KeywordsPhysicsAstrophysicsDebrisAstronomyMeteorology

Abstract

fetched live from OpenAlex

AU Microscopii’s debris disc is one of the most famous and best-studied debris discs and one of only two resolved debris discs around M stars. We perform in-depth collisional modelling of the AU Mic disc including stellar radiative and corpuscular forces (stellar winds), aiming at a comprehensive understanding of the dust production and the dust and planetesimal dynamics in the system. Our models are compared to a suite of observational data for thermal and scattered light emission, ranging from the ALMA radial surface brightness profile at 1.3 mm to spatially resolved polarisation measurements in the visible. Most of the data are shown to be reproduced with dust production in a belt of planetesimals with an outer edge at around 40 au and subsequent inward transport of dust by stellar winds. A low dynamical excitation of the planetesimals with eccentricities up to 0.03 is preferred. The radial width of the planetesimal belt cannot be constrained tightly. Belts that are 5 au and 17 au wide, as well as a broad 44 au-wide belt, are consistent with observations. All models show surface density profiles that increase with distance from the star up to ≈40 au, as inferred from observations. The best model is achieved by assuming a stellar mass loss rate that exceeds the solar one by a factor of 50. The models reproduce the spectral energy distribution and the shape of the ALMA radial profile well, but deviate from the scattered light observations more strongly. The observations show a bluer disc colour and a lower degree of polarisation for projected distances <40 au than predicted by the models. These deviations may be reduced by taking irregularly shaped dust grains which have scattering properties different from the Mie spheres used in this work. From tests with a handful of selected dust materials, we favour mixtures of silicate, carbon, and ice of moderate porosity. We also address the origin of the unresolved central excess emission detected by ALMA and show that it cannot stem from an additional inner belt alone. Instead, it should derive, at least partly, from the chromosphere of the central star.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.229
Teacher spread0.208 · 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

Citations54
Published2015
Admission routes1
Has abstractyes

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