Herschel/HerMES: the X-ray-infrared correlation for star-forming galaxies at z∼1
Bibliographic record
Abstract
For the first time, we investigate the X-ray/infrared (IR) correlation for star-forming galaxies (SFGs) at z∼ 1, using SPIRE submm data from the recently launched Herschel Space Observatory and deep X-ray data from the 2-Ms Chandra Deep Field-North survey. We examine the X-ray/IR correlation in the soft X-ray (SX; 0.5–2 keV) and hard X-ray (HX; 2–10 keV) bands by comparing our z∼ 1 SPIRE-detected SFGs to equivalently IR-luminous (LIR > 1010 L⊙) samples in the local/low-redshift Universe. Our results suggest that the X-ray/IR properties of the SPIRE SFGs are on average similar to those of their local counterparts, as we find no evidence for evolution in the LSX/LIR and LHX/LIR ratios with redshift. We note, however, that at all redshifts, both LSX/LIR and LHX/LIR are strongly dependent on IR luminosity, with luminous and ultraluminous IR galaxies (LIRGs and ULIRGs; LIR > 1011 L⊙) having up to an order of magnitude lower values than normal IR galaxies (LIR < 1011 L⊙). We derive a LSX–LIR relation and confirm the applicability of an existing LHX–LIR relation for both local and distant LIRGs and ULIRGs, consistent with a scenario where X-ray luminosity is correlated with the star formation rate.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.003 | 0.001 |
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".