The circumgalactic medium of massive galaxies at z~3: a test for stellar feedback, galactic outflows, and cold streams
Bibliographic record
Abstract
We present new results on the kinematics, thermal and ionization state, and spatial distribution of metal-enriched gas in the circumgalactic medium (CGM) of massive galaxies at redshift 3, using the "Eris" suite of cosmological "zoom-in" simulations. The reference run adopts a blastwave scheme for supernova feedback that produces galactic outflows, a star formation recipe based on a high gas density threshold, metal-dependent radiative cooling, and a model for the diffusion of metals and thermal energy. Synthetic spectra through the multiphase CGM produce interstellar absorption line strengths of Lya, CII, CIV, SiII, and SiIV as a function of galactocentric impact parameter (scaled to the virial radius) that are in broad agreement with those observed at high-redshift by Steidel et al. (2010). Only about one third of all the gas within R_vir is outflowing. The fraction of sightlines within one virial radius that intercept optically thick material is 27%, in agreement with recent observations by Rudie et al. (2012). Such optically thick absorption is shown to trace inflowing "cold" streams that penetrate deep inside the virial radius. The streams, enriched to metallicities above 0.01 solar, give origin to strong (log N > 13) CII absorption with a covering factor of 22% within R_vir and 10% within 2 R_vir. Galactic outflows do not cause any substantial suppression of the cold accretion mode. The central galaxy is surrounded by a large OVI halo, with a typical column density log N>14 and a near unity covering factor maintained all the way out to 150 kpc. This matches the trends recently observed in star-forming galaxies at low redshift by Tumlinson et al. (2011). Our zoom-in simulations of this single system appear to reproduce quantitatively the complex baryonic processes that determine the exchange of matter, energy, and metals between galaxies and their surroundings. (Abridged)
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".