A search for warm/hot gas filaments between pairs of SDSS Luminous Red Galaxies
Bibliographic record
Abstract
Abstract We search the Planck data for a thermal Sunyaev–Zel’dovich (tSZ) signal due to gas filaments between pairs of Luminous Red Galaxies (LRGs) taken from the Sloan Digital Sky Survey Data Release 12 (SDSS/DR12). We identify ∼260 000 LRG pairs in the DR12 catalogue that lie within 6–10 $h^{-1} \, \mathrm{Mpc}$ of each other in tangential direction and within 6 $h^{-1} \, \mathrm{Mpc}$ in radial direction. We stack pairs by rotating and scaling the angular positions of each LRG so they lie on a common reference frame, then we subtract a circularly symmetric halo from each member of the pair to search for a residual signal between the pair members. We find a statistically significant (5.3σ) signal between LRG pairs in the stacked data with a magnitude Δy = (1.31 ± 0.25) × 10−8. The uncertainty is estimated from two Monte Carlo null tests which also establish the reliability of our analysis. Assuming a simple, isothermal, cylindrical filament model of electron overdensity with a radial density profile proportional to rc/r (as determined from simulations), where r is the perpendicular distance from the cylinder axis and rc is the core radius of the density profile, we constrain the product of overdensity and filament temperature to be $\delta _\mathrm{ c} \times (T_{\rm e}/10^7 \, {\rm K}) \times (r_\mathrm{ c}/0.5h^{-1} \, {\rm Mpc}) = 2.7 \pm 0.5$. To our knowledge, this is the first detection of filamentary gas at overdensities typical of cosmological large-scale structure. We compare our result to the BAHAMAS suite of cosmological hydrodynamic simulations (McCarthy et al. 2017) and find a slightly lower, but marginally consistent Comptonization excess, Δy = (0.84 ± 0.24) × 10−8.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".