Stripping of the Hot Gas Halos in Member Galaxies of Abell 1795
Bibliographic record
Abstract
Abstract The nearby cluster Abell 1795 is used as a testbed to examine whether hot gas in cluster galaxies is stripped by the ram pressure of the intracluster medium (ICM). The expected X-ray emission in and around Abell 1795 galaxies is likely dominated by the ICM, low-mass X-ray binaries, active galactic nuclei, and hot gas halos. In order to constrain these components, we use archival Chandra X-ray Observatory and Sloan Digital Sky Survey observations of Abell 1795 and identify 58 massive (M ⋆ > 1010 M ⊙) spectroscopic cluster members within 5′ of the Chandra optical axis. X-ray images at 0.5–1.5 and 4–8 keV were created for each cluster member and then stacked into two clustercentric radius bins: inner (0.25 < R clust/R 500 < 1) and outer (1 < R clust/R 500 < 2.5). Surface brightness profiles of inner and outer cluster members are fit using Markov chain Monte Carlo sampling in order to generate model parameters and measure the 0.5–1.5 keV luminosities of each model component. Leveraging effective total Chandra exposure times of 3.4 and 1.7 Ms for inner and outer cluster members, respectively, we report the detection of hot gas halos, in a statistical sense, around outer cluster members. Outer members have 0.5–1.5 keV hot halo luminosities ( ) that are six times larger than the upper limit for inner cluster members (L X < 1.3 × 1039 erg s−1). This result suggests that the ICM is removing hot gas from the halos of Abell 1795 members as they fall into the cluster.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".