Measuring Feedback Using the Intergalactic Medium State and Evolution Inferred from the Soft X‐Ray Background
Bibliographic record
Abstract
We explore the intergalactic medium (IGM) as a potential source of the unresolved soft X-ray background (XRB) and the feasibility of extracting the IGM state and evolution from XRB observations. We build two analytical models, the continuum field model and the halo model, to calculate the IGM XRB mean flux, angular autocorrelation, and cross-correlation with galaxies. Our results suggest that the IGM may contribute a significant fraction to the unresolved soft XRB flux and correlations. We calibrated non-Gaussian errors estimated against our 512 3 moving mesh hydro simulation and estimate that the ROSAT All-Sky Survey plus Sloan Galaxy Photometric Redshift Survey would allow a ~10% accuracy in the IGM XRB-galaxy cross-correlation power spectrum measurement for 800 < l < 5000 and a ~20% accuracy in the redshift-resolved X-ray emissivity-galaxy cross-correlation power spectrum measurement for z ≲ 0.5. At small scales, nongravitational heating, i.e., feedback, dominates over gravity and leaves unique signatures in the IGM XRB, which allows a comparable accuracy in the measurement of the amount of nongravitational heating and the length scales where nongravitational energy balances gravity.
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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 | 0.002 |
| 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 | 0.000 | 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".