The thermodynamic structure and large-scale structure filament in MACS J0717.5+3745
Bibliographic record
Abstract
We present the results of Chandra and XMM-Newton X-ray imaging and spatially resolved spectroscopy, along with new MUSTANG2 90 GHz observations of the thermal Sunyaev-Zeldovich (SZ) effect on MACS J0717.5+3745. This exceptionally massive (3.5 ± 0.6 × 10 15 M ⊙ ) Frontier Fields cluster located at intermediate redshift ( z = 0.5458) is experiencing multiple mergers and hosting an apparent X-ray bright large-scale structure filament. We produced thermodynamical maps from Chandra, XMM-Newton, and ROSAT data using a new method to model the astrophysical and instrumental backgrounds. The temperature peak of 24 ± 4 keV is also the pressure peak of the cluster and it is spatially closely correlated with the SZ peak from the MUSTANG2 data. We characterised a potential shock candidate at the cluster centre, based on the sharp temperature and pressure gradient. We also quantified its temperature-derived Mach number in various directions to span a range of ℳ = (1.7 − 2.0)±0.3. We used Bayesian X-ray analysis methods to disentangle different projected spectral signatures for the filament structure, with the Akaike and Bayes information criteria (AIC and BIC) used to select the most appropriate model to describe the various temperature components. We report an X-ray filament temperature of 3.1 +0.6 −0.3 keV and a density (3.78 ± 0.05)×10 −4 cm −3 , corresponding to an overdensity of ∼400 relative to the critical density of the Universe. We estimate the hot gas mass of the filament to be ∼6.1 × 10 12 M ⊙ , while its total projected weak-lensing measured mass is ∼(6.8 ± 2.7)×10 13 M ⊙ , indicating a hot baryon fraction of 4–10%.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".