Two-loop EFT galaxy power spectrum achieves per-mille agreement with simulations to k=0.85 h/Mpc and yields three times narrower unbiased σ8 errors than linear theory.
Title resolution pending
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
citation-role summary
background 2
citation-polarity summary
fields
astro-ph.CO 5verdicts
UNVERDICTED 5roles
background 2representative citing papers
A general analytical expression for the Gaussian covariance of complex multi-tracer power spectra is derived, applied to multipoles and 2D spectra, and validated against Monte Carlo simulations.
Control variates with Zeldovich mocks reduce covariance matrix variance by up to an order of magnitude on large scales in DESI-like mocks.
First MCMC constraints on LSS bootstrap parameters yield ~7% precision on linear growth modifications and ~57% on quadratic kernel modifications from BOSS data, improving to 1% and 25% with larger simulations.
Reanalysis of DESI full-shape clustering data tightens constraints on neutrino mass, spatial curvature, and dark energy equation-of-state parameters relative to BAO-only results.
citing papers explorer
-
Galaxy Power Spectrum at Two-Loop Order: Implications for Weak Lensing Surveys and New Physics
Two-loop EFT galaxy power spectrum achieves per-mille agreement with simulations to k=0.85 h/Mpc and yields three times narrower unbiased σ8 errors than linear theory.
-
Complex yet Hermitian: Gaussian covariance of cross-correlation and multi-tracer power spectra
A general analytical expression for the Gaussian covariance of complex multi-tracer power spectra is derived, applied to multipoles and 2D spectra, and validated against Monte Carlo simulations.
-
Fewer simulations, sharper covariances: Reducing mock covariance noise with Zeldovich approximation control variates
Control variates with Zeldovich mocks reduce covariance matrix variance by up to an order of magnitude on large scales in DESI-like mocks.
-
Probing nonlinear structure formation beyond $\Lambda$CDM with the LSS bootstrap: a joint power spectrum and bispectrum analysis
First MCMC constraints on LSS bootstrap parameters yield ~7% precision on linear growth modifications and ~57% on quadratic kernel modifications from BOSS data, improving to 1% and 25% with larger simulations.
-
Reanalyzing DESI DR1: 2. Constraints on Dark Energy, Spatial Curvature, and Neutrino Masses
Reanalysis of DESI full-shape clustering data tightens constraints on neutrino mass, spatial curvature, and dark energy equation-of-state parameters relative to BAO-only results.