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Supernovae-generated high-velocity compact clouds

2018· article· en· W3099611456 on OpenAlexaff
Almog Yalinewich, Paz Beniamini

Bibliographic record

VenueSpringer Link (Chiba Institute of Technology) · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysical Phenomena and Observations
Canadian institutionsCanadian Institute for Theoretical Astrophysics
Fundersnot available
KeywordsPhysicsSupernovaAstrophysicsSupernova remnantMolecular cloudBremsstrahlungGalactic CenterBlack hole (networking)Context (archaeology)Velocity dispersionAstronomyElectronGalaxyNuclear physics

Abstract

fetched live from OpenAlex

Context. A previous study claimed the discovery of an intermediate-mass black hole (IMBH). This hypothetical black hole was invoked in order to explain the high-velocity dispersion in one of several dense molecular clouds near the Galactic center. The same study considered the possibility that this cloud was due to a supernova explosion, but disqualified this scenario because no X-rays were detected. Aims. We here check whether a supernova explosion could have produced that cloud, and whether this explanation is more likely than an IMBH. More specifically, we wish to determine whether a supernova inside a dense molecular cloud would emit in the X-rays. Methods. We have approached this problem from two different directions. First, we performed an analytic calculation to determine the cooling rate by thermal bremsstrahlung and compared this time to the lifetime of the cloud. Second, we estimated the creation rate of these dense clouds in the central molecular zone (CMZ) region near the Galactic center, where they were observed. Based on this rate, we can place lower bounds on the total mass of IMBHs and clouds and compare this to the masses of the components of the CMZ. Results. We find that the cooling time of the supernova remnant inside a molecular cloud is shorter than its dynamical time. This means that the temperature in such a remnant would be much lower than that of a typical supernova remnant. At such a low temperature, the remnant is not expected to emit in the X-rays. We also find that to explain the rate at which such dense clouds are created requires fine-tuning the number of IMBHs. Conclusions. We find the supernova model to be a more likely explanation for the formation of high-velocity compact clouds than an IMBH.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score0.919

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.239
Teacher spread0.223 · 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 designTheoretical or conceptual
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
Published2018
Admission routes1
Has abstractyes

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