First measurement of the bulk flow of nearby galaxies using the cosmic microwave background
Bibliographic record
Abstract
Peculiar velocities in the nearby Universe can be measured via the kinetic Sunyaev–Zel'dovich (kSZ) effect. Using a statistical method based on an optimized cross-correlation with nearby galaxies, we extract the kSZ signal generated by plasma halo of galaxies from the cosmic microwave background (CMB) temperature anisotropies observed by the Wilkinson Microwave Anisotropy Probe (WMAP). Marginalizing over the thermal Sunyaev–Zel'dovich contribution from clusters of galaxies, possible unresolved point source contamination, and Galactic foregrounds, we find a kSZ bulk flow signal present at the ∼90 per cent confidence level in the seven-year WMAP data. When only galaxies within 50 h−1 Mpc are included in the kSZ template, we find a bulk flow in the CMB frame of |V| = 533 ± 263 km s−1, in the direction l = 324 ± 27, b = −7 ± 17, consistent with bulk flow measurements on a similar scale using classical distance indicators. We show how this comparison constrains, for the first time, the (ionized) baryonic budget in the local universe. On very large (∼500 h−1 Mpc) scales, we find a 95 per cent upper limit of 470 km s−1, inconsistent with some analyses of bulk flow of clusters from the kSZ. We estimate that the significance of the bulk flow signal may increase to 3σ–5σ using data from the Planck probe.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".