Light-cone mocks demonstrate that analytical corrections for survey-window and integral-constraint effects on PNG in galaxy power spectra lose accuracy below the equality scale and fail when PNG is present, enabling unbiased large-scale measurements.
Super-Sample Covariance in Simulations
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abstract
Using separate universe simulations, we accurately quantify super-sample covariance (SSC), the typically dominant sampling error for matter power spectrum estimators in a finite volume, which arises from the presence of super survey modes. By quantifying the power spectrum response to a background mode, this approach automatically captures the separate effects of beat coupling in the quasilinear regime, halo sample variance in the nonlinear regime and a new dilation effect which changes scales in the power spectrum coherently across the survey volume, including the baryon acoustic oscillation scale. It models these effects at typically the few percent level or better with a handful of small volume simulations for any survey geometry compared with directly using many thousands of survey volumes in a suite of large volume simulations. The stochasticity of the response is sufficiently small that in the quasilinear regime, SSC can be alternately included by fitting the mean density in the volume with these fixed templates in parameter estimation. We also test the halo model prescription and find agreement typically at better than the 10% level for the response.
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Estimators from squeezed bispectrum and collapsed trispectrum recover unbiased small-scale matter power spectrum covariance at the percent level using 25 Quijote simulations.
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Modeling survey-window and integral-constraint effects on PNG in the galaxy power spectrum with light-cone mocks
Light-cone mocks demonstrate that analytical corrections for survey-window and integral-constraint effects on PNG in galaxy power spectra lose accuracy below the equality scale and fail when PNG is present, enabling unbiased large-scale measurements.
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If at First You Don't Succeed, Trispectrum: I. Estimating the Matter Power Spectrum Covariance with Higher-Order Statistics
Estimators from squeezed bispectrum and collapsed trispectrum recover unbiased small-scale matter power spectrum covariance at the percent level using 25 Quijote simulations.