Simulated catalogs and maps of radio galaxies at millimeter wavelengths in Websky
Bibliographic record
Abstract
Abstract We present simulated millimeter-wavelength maps and catalogs of radio galaxies across the full sky that trace the nonlinear clustering and evolution of dark matter halos from the Websky simulation at z < 4.6 and M halo > 1012 m ⊙/h, and the accompanying framework for generating a new sample of radio galaxies from any halo catalog of positions, redshifts, and masses. Object fluxes are generated using a hybrid approach that combines (1) existing astrophysical halo models of radio galaxies from the literature to determine the positions and rank-ordering of the observed fluxes with (2) empirical models from the literature based on fits to the observed distribution of flux densities and (3) spectral indices drawn from an empirically-calibrated frequency-dependent distribution. The resulting population of radio galaxies is in excellent agreement with the number counts, polarization fractions, and distribution of spectral slopes from the data from observations at millimeter wavelengths from 20-200 GHz, including Planck, ALMA, SPT, and ACT. Since the radio galaxies are correlated with the existing cosmic infrared background (CIB), Compton-y (tSZ), and CMB lensing maps from Websky, our model makes new predictions for the cross-correlation power spectra and stacked profiles of radio galaxies and these other components. These simulations will be important for unbiased analysis of a wide variety of observables that are correlated with large-scale structure, such as gravitational lensing and SZ clusters.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".