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Record W2027399712 · doi:10.1088/0004-637x/780/1/51

THE EFFECTS OF IRRADIATION ON CLOUD EVOLUTION IN ACTIVE GALACTIC NUCLEI

2013· article· en· W2027399712 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsCanadian Institute for Theoretical Astrophysics
Fundersnot available
KeywordsOpacityCloud computingActive galactic nucleusPhotoionizationFocus (optics)Radiation pressureRadiative transferAcceleration

Abstract

fetched live from OpenAlex

We report on the first phase of our study of cloud irradiation. We study irradiation by means of numerical, two-dimensional time-dependent radiation-hydrodynamic simulations of a cloud irradiated by a strong radiation. We adopt a very simple treatment of the opacity, neglect photoionization and gravity, and instead focus on assessing the role of the type and magnitude of the opacity on the cloud evolution. Our main result is that even relatively dense clouds that are radiatively heated (i.e., with significant absorption opacity) do not move as a whole instead they undergo a very rapid and major evolution in its shape, size and physical properties. In particular, the cloud and its remnants become optical thin within less than one sound crossing time and before they can travel over a significant distance (a distance of a few radii of the initial cloud). We also found that a cloud can be accelerated as a whole under quite extreme conditions, e.g., the opacity must be dominated by scattering. However, the acceleration due to the radiation force is relatively small and unless the cloud is optically thin the cloud quickly changes its size and shape. We discuss implications for the modelling and interpetation broad line regions of active galactic nuclei.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.905
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.209
Teacher spread0.204 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations30
Published2013
Admission routes1
Has abstractyes

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