Chasing the Break: Tracing the Full Evolution of a Black Hole X-Ray Binary Jet with Multiwavelength Spectral Modeling
Bibliographic record
Abstract
Abstract Black hole (BH) X-ray binaries (XRBs) are ideal targets to study the connection between accretion inflow and jet outflow. Here we present quasi-simultaneous, multiwavelength observations of the Galactic BH system MAXI J1820+070, throughout its 2018–2019 outburst. Our data set includes coverage from the radio through X-ray bands from 17 different instruments/telescopes, and encompasses 19 epochs over a 7 month period, resulting in one of the most well-sampled multiwavelength data sets of a BH XRB outburst to date. With our data, we compile and model the broadband spectra of this source using a phenomenological model that includes emission from the jet, a companion star, and an accretion flow. This modeling allows us to track the evolution of the spectral break in the jet spectrum, a key observable that samples the jet launching region. We find that the spectral break location changes over at least ≈3 orders of magnitude in electromagnetic frequency over this period. Using these spectral break measurements, we link the full cycle of jet behavior, including the rising, quenching, and reignition, to the changing accretion flow properties as the source evolves through its different accretion states. Our analysis shows consistent jet behavior with other sources in similar phases of their outbursts, reinforcing the idea that jet quenching and recovery may be a global feature of BH XRB systems in outburst. Our results also provide valuable evidence supporting a close connection between the geometry of the inner accretion flow and the base of the jet.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".