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Record W4399115857 · doi:10.1093/mnras/stae2049

Constraining the physical properties of large-scale jets from black hole X-ray binaries and their impact on the local environment with blast-wave dynamical models

2024· article· en· W4399115857 on OpenAlexafffund
Francesco Carotenuto, R. P. Fender, Alexandra J. Tetarenko, S. Corbel, A. A. Zdziarski, Gouse Ahammad Shaik, A J Cooper, I. Di Palma

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Cosmic Phenomena
Canadian institutionsUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of CanadaHintze Family Charitable FoundationScience and Technology Facilities CouncilSpace Telescope Science InstituteNational Aeronautics and Space Administration
KeywordsPhysicsAstrophysicsScale (ratio)Black hole (networking)Blast waveAstronomyShock waveMechanics

Abstract

fetched live from OpenAlex

ABSTRACT Relativistic discrete ejecta launched by black hole X-ray binaries (BH XRBs) can be observed to propagate up to parsec-scales from the central object. Observing the final deceleration phase of these jets is crucial to estimate their physical parameters and to reconstruct their full trajectory, with implications for the jet powering mechanism, composition, and formation. In this paper, we present the results of the modelling of the motion of the ejecta from three BH XRBs: MAXI J1820$+$070, MAXI J1535–571, and XTE J1752–223, for which high-resolution radio and X-ray observations of jets propagating up to $\sim$15 arcsec ($\sim$0.6 pc at 3 kpc) from the core have been published in the recent years. For each jet, we modelled its entire motion with a dynamical blast-wave model, inferring robust values for the jet Lorentz factor, inclination angle and ejection time. Under several assumptions associated to the ejection duration, the jet opening angle and the available accretion power, we are able to derive stringent constraints on the maximum jet kinetic energy for each source (between $10^{43}$ and $10^{44}$ erg, including also H1743–322), as well as placing interesting upper limits on the density of the ISM through which the jets are propagating (from $n_{\rm ISM} \lesssim 0.4$ cm$^{-3}$ down to $n_{\rm ISM} \lesssim 10^{-4}$ cm$^{-3}$). Overall, our results highlight the potential of applying models derived from gamma-ray bursts to the physics of jets from BH XRBs and support the emerging picture of these sources as preferentially embedded in low-density environments.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.629

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 studies0.0000.002
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 head0.009
GPT teacher head0.183
Teacher spread0.174 · 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 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

Citations13
Published2024
Admission routes2
Has abstractyes

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