REPRODUCING THE STELLAR MASS/HALO MASS RELATION IN SIMULATED ΛCDM GALAXIES: THEORY VERSUS OBSERVATIONAL ESTIMATES
Bibliographic record
Abstract
We examine the present-day total stellar-to-halo mass (SHM) ratio as a function of halo mass for a new sample of simulated field galaxies using fully cosmological, LCDM, high resolution SPH + N-Body simulations.These simulations include an explicit treatment of metal line cooling, dust and self-shielding, H2 based star formation and supernova driven gas outflows. The 18 simulated halos have masses ranging from a few times 10^8 to nearly 10^12 solar masses. At z=0 our simulated galaxies have a baryon content and morphology typical of field galaxies. Over a stellar mass range of 2.2 x 10^3 to 4.5 x 10^10 solar masses, we find extremely good agreement between the SHM ratio in simulations and the present-day predictions from the statistical Abundance Matching Technique presented in Moster et al. (2012). This improvement over past simulations is due to a number systematic factors, each decreasing the SHM ratios: 1) gas outflows that reduce the overall SF efficiency but allow for the formation of a cold gas component 2) estimating the stellar masses of simulated galaxies using artificial observations and photometric techniques similar to those used in observations and 3) accounting for a systematic, up to 30 percent overestimate in total halo masses in DM-only simulations, due to the neglect of baryon loss over cosmic times. Our analysis suggests that stellar mass estimates based on photometric magnitudes can underestimate the contribution of old stellar populations to the total stellar mass, leading to stellar mass errors of up to 50 percent for individual galaxies. These results highlight the importance of using proper techniques to compare simulations with observations and reduce the perceived tension between the star formation efficiency in galaxy formation models and in real galaxies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".