Beyond BAO: Improving cosmological constraints from BOSS data with measurement of the void-galaxy cross-correlation
Bibliographic record
Abstract
We present a measurement of the anisotropic void-galaxy cross-correlation function in the CMASS galaxy sample of the BOSS DR12 data release. We perform a joint fit to the data for redshift space distortions (RSD) due to galaxy peculiar velocities and anisotropies due to the Alcock-Paczynski (AP) effect, for the first time using a velocity field reconstruction technique to remove the complicating effects of RSD in the void center positions themselves. Fits to the void-galaxy function give a 1% measurement of the AP parameter combination ${D}_{A}(z)H(z)/c=0.4367\ifmmode\pm\else\textpm\fi{}0.0045$ at redshift $z=0.57$, where ${D}_{A}$ is the angular diameter distance and $H$ the Hubble parameter, exceeding the precision obtainable from baryon acoustic oscillations (BAO) by a factor of $\ensuremath{\sim}3.5$ and free of systematic errors. From voids alone we also obtain a 10% measure of the growth rate, $f{\ensuremath{\sigma}}_{8}(z=0.57)=0.501\ifmmode\pm\else\textpm\fi{}0.051$. The parameter degeneracies are orthogonal to those obtained from galaxy clustering. Combining void information with that from BAO and galaxy RSD in the same CMASS sample, we measure ${D}_{A}(0.57)/{r}_{s}=9.383\ifmmode\pm\else\textpm\fi{}0.077$ (at 0.8% precision), $H(0.57){r}_{s}=(14.05\ifmmode\pm\else\textpm\fi{}0.14){10}^{3}\text{ }\text{ }{\mathrm{kms}}^{\ensuremath{-}1}\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$ (1%), and $f{\ensuremath{\sigma}}_{8}=0.453\ifmmode\pm\else\textpm\fi{}0.022$ (4.9%), consistent with cosmic microwave background (CMB) measurements from Planck. These represent a factor $\ensuremath{\sim}2$ improvement in precision over previous results through the inclusion of void information. Fitting a flat cosmological constant $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ model to these results in combination with Planck CMB data, we find up to an 11% reduction in uncertainties on ${H}_{0}$ and ${\mathrm{\ensuremath{\Omega}}}_{m}$ compared to use of the corresponding BOSS consensus values. Constraints on extended models with nonflat geometry and a dark energy of state that differs from $w=\ensuremath{-}1$ show an even greater improvement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".