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Record W4292457990 · doi:10.1093/mnras/stac2227

Erratum: Eccentric tidal disruption event discs around supermassive black holes: dynamics and thermal emission

2022· erratum· en· W4292457990 on OpenAlexafffund
J. J. Zanazzi, Gordon I. Ogilvie

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2022
Typeerratum
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
FundersScience and Technology Facilities CouncilNatural Sciences and Engineering Research Council of Canada
KeywordsPhysicsSupermassive black holeAstrophysicsThermalThermal emissionAstronomyGalaxyMeteorology

Abstract

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In the original paper (Zanazzi & Ogilvie 2020), we used an incorrect expression for the area element of an eccentric disc. Here, we rectify this error and discuss how this correction affects the thermal emission from eccentric tidal disruption event (TDE) discs. Fig. 1 shows how the corrected area element affects the flux per unit area. Here, we use the same disc model as Zanazzi & Ogilvie (2020). Comparing with fig. 8 of Zanazzi & Ogilvie (2020), we see that the bolometric luminosity per unit area is significantly less near pericentre, and typically does not exceed the luminosity near apocentre (E ≈ |$\pi$|⁠). Same as fig. 8 of Zanazzi & Ogilvie (2020), except we use the Jacobian for the eccentric coordinates (a, E) [equation (6)], instead of the Jacobian for Delaunay variables (Λ, λ) [equation (2)]. The correct Jacobian gives significantly less bolometric flux per unit area near pericentre (E ≈ 0), especially for large eccentricities. Fig. 2 shows the thermal emission from a disc with a constant eccentricity. Comparing with fig. 9 of Zanazzi & Ogilvie (2020), using the correct Jacobian in equation (7) can lead up to an order of magnitude reduction of the disc’s X-ray and far-UV flux for appreciable eccentricities (e ≳ 0.7). Same as fig. 9 of Zanazzi & Ogilvie (2020), except we use the Jacobian for the eccentric coordinates (a, E) [equation (6)], instead of the Jacobian for Delaunay variables (Λ, λ) [equation (2)]. The correct Jacobian leads to less X-ray flux for highly eccentric discs. In this section, we recalculate the spectral energy distributions (SEDs) from section 3.3 of Zanazzi & Ogilvie (2020), using the correct area element [equation (5)]. We use the same underlying disc models, as well as the same non-linear eccentric disc eigenmode solutions, as Zanazzi & Ogilvie (2020). Fig. 3 displays the SEDs, while Fig. 4 shows the UV/optical and X-ray luminosities, from our eccentric disc solutions. The dependence of the thermal emission on all parameters is identical to that discussed in Zanazzi & Ogilvie (2020), but the X-ray and far-UV luminosity are significantly reduced. In particular, the X-ray and UV/optical luminosity predictions from our model are now in a better agreement with those observed from TDE candidates (Fig. 4). Same as fig. 10 of Zanazzi & Ogilvie (2020), except we use the Jacobian for the eccentric coordinates (a, E) [equation (6)], instead of the Jacobian for Delaunay variables (Λ, λ) [equation (2)]. The correct Jacobian leads to less X-ray and far-UV flux from highly eccentric regions of the disc. Same as fig. 11 of Zanazzi & Ogilvie (2020), except we use the Jacobian for the eccentric coordinates (a, E) [equation (6)], instead of the Jacobian for Delaunay variables (Λ, λ) [equation (2)]. The correct Jacobian leads to less X-ray and far-UV flux from highly eccentric regions of the disc. JZ thanks Elliot Lynch for pointing out that we were using the wrong Jacobian for the eccentric disc coordinates. JZ was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) under the funding reference #CITA 490888-16, and a David Crighton Fellowship from DAMTP. GIO acknowledges the support of STFC through grant ST/P000673/1.

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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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.057
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0570.031

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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2022
Admission routes2
Has abstractno

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