Projected-field kinetic Sunyaev-Zel'dovich Cross-correlations: halo model and forecasts
Bibliographic record
Abstract
Abstract The kinetic Sunyaev-Zel'dovich (kSZ) effect, i.e., the Doppler boost of cosmic microwave background (CMB) photons caused by their scattering off free electrons in galaxy clusters and groups with non-zero bulk velocity, is a powerful window on baryons in the universe. We present the first halo-model computation of the cross-power spectrum of the “projected-field” kSZ signal with large-scale structure (LSS) tracers. We compare and validate our calculations against previous studies, which relied on N -body-calibrated effective formulas rather than the halo model. We forecast results for CMB maps from the Atacama Cosmology Telescope (AdvACT), Simons Observatory (SO), and CMB-S4, and LSS survey data from the Dark Energy Survey, the Vera C. Rubin Observatory (VRO), and Euclid . In cross-correlation with galaxy number density, for AdvACT × unWISE we forecast an 18 σ projected-field kSZ detection using data already in hand. Combining SO CMB maps and unWISE galaxy catalogs, we expect a 62 σ detection, yielding precise measurements of the gas density profile radial slopes. Additionally, we forecast first detections of the kSZ — galaxy weak lensing cross-correlation with AdvACT × VRO/ Euclid (at 6 σ ) and of the kSZ — CMB weak lensing cross-correlation with SO (at 16 σ ). Finally, ≈ 10-20% precision measurements of the shape of the gas density profile should be possible with CMB-S4 kSZ — CMB lensing cross-correlation without using any external datasets.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".