Cosmology with the Redshift-Space Galaxy Bispectrum Monopole at One-Loop Order
Bibliographic record
Abstract
We study the cosmological information content of the redshift-space galaxy bispectrum monopole at one-loop order in perturbation theory. We incorporate all effects necessary for comparison to data: fourth-order galaxy bias, infrared resummation (accounting for the non-linear evolution of baryon acoustic oscillations), ultraviolet counterterms, non-linear redshift-space distortions, stochastic contributions, projection, and binning effects. The model is implemented using FFTLog, and validated with the PT Challenge suite of $N$-body simulations, whose large volume allows for high-precision tests. Focusing on the mass fluctuation amplitude, $\sigma_8$, and galaxy bias parameters, we find that including one-loop corrections allow us to significantly extend the range of scales over which the bispectrum can be modeled, and greatly tightens constraints on bias parameters. However, this does not lead to noticeable improvements in the $\sigma_8$ errorbar due to the necessary marginalization over a large number of nuisance parameters with conservative priors. Analyzing a BOSS-volume likelihood, we find that the addition of the one-loop bispectrum may lead to improvements on primordial non-Gaussianity constraints by $\lesssim 30\%$ and on $\sigma_8$ by $\approx 10\%$, though we caution that this requires pushing the analysis to short scales where the galaxy bias parameters may not be correctly recovered; this may lead to biases in the recovered parameter values. We conclude that restrictive priors from simulations or higher-order statistics such as the bispectrum multipoles will be needed in order to realize the full information content of the galaxy bispectrum.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".