Magnetic flux plays an important role during a BHXRB outburst in radiative 2T GRMHD simulations
Bibliographic record
Abstract
Black hole (BH) X-ray binaries cycle through different spectral states of accretion over the course of months to years. Although fluctuations in the BH mass accretion rate are generally recognized as the most important component of state transitions, it is becoming increasingly evident that magnetic fields play a similarly important role. In this article, we present the first radiative two-temperature (2T) general relativistic magnetohydrodynamics (GRMHD) simulations in which an accretion disk transitions from a quiescent state at an accretion rate of $\dot{M} \sim 10^{-10} \dot{M}_{\rm Edd}$ to a hard-intermediate state at an accretion rate of $\dot{M} \sim 10^{-2} \dot{M}_{\rm Edd}$. This huge parameter space in mass accretion rate is bridged by artificially rescaling the gas density scale of the simulations. We present two jetted BH models with varying degrees of magnetic flux saturation. We demonstrate that in `Standard and Normal Evolution' models, which are unsaturated with magnetic flux, the hot torus collapses into a thin and cold accretion disk when $\dot{M} \gtrsim 5\times 10^{-3} \dot{M}_{\rm Edd}$. On the other hand, in `Magnetically Arrested Disk' models, which are fully saturated with vertical magnetic flux, the plasma remains mostly hot with substructures that condense into cold clumps of gas when $\dot{M} \gtrsim 1 \times 10^{-2} \dot{M}_{\rm Edd}$. This suggests that the spectral signatures observed during state transitions are closely tied to the level of magnetic flux saturation.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".