GEO-FPT: a model of the galaxy bispectrum at mildly non-linear scales

The power spectrum and bispectrum of dark matter tracers are key and complementary probes of the Universe. Next-generation surveys will deliver good measurements of the bispectrum, opening the door to improved cosmological constraints and the breaking of parameter degeneracies, from the combination of the power spectrum and bispectrum. Multi-tracer power spectra have been used to suppress cosmic variance and mitigate the effects of nuisance parameters and systematics. We present a bispectrum multi-tracer formalism that can be applied to next-generation survey data. Then we perform a simple Fisher analysis to illustrate qualitatively the improved precision on primordial non-Gaussianity that is expected to come from the bispectrum multi-tracer. In addition, we investigate the parametric dependence of conditional errors from multi-tracer power spectra and multi-tracer bispectra, on the differences between the biases and the number densities of two tracers. Our results suggest that optimal constraints arise from maximising the ratio of number densities, the difference between the linear biases, the difference between the quadratic biases, and the difference between the products b 1 b Φ for each tracer, where b Φ is the bias for the primordial potential.

Section: Introductionmentioning

confidence: 99%

Multi-tracer power spectra and bispectra: formalism

Karagiannis,

Maartens,

Fonseca

et al. 2024

On approximations of the redshift-space bispectrum and power spectrum multipoles covariance matrix

Novell-Masot,

Gil-Marín,

Verde

2024

Self Cite

We investigate, in dark matter and galaxy mocks, the effects of approximating the galaxy power spectrum-bispectrum estimated covariance as a diagonal matrix, for an analysis that aligns with the specifications of recent and upcoming galaxy surveys. We find that, for a joint power spectrum and bispectrum data-vector, with corresponding k-ranges of 0.02 < k[hMpc-1] < 0.15 and 0.02 < k[hMpc-1] < 0.12 each, the diagonal covariance approximation recovers ∼ 10% larger error-bars on the parameters {σ 8,f,α ∥,α ⊥} with respect to the full covariance case, while still underestimating the corresponding true errors on the recovered parameters by ∼ 10%. This is caused by the diagonal approximations weighting the elements of the data-vector in a sub-optimal way, resulting in a less efficient estimator, with poor coverage properties, than the maximum likelihood estimator featuring the full covariance matrix. We further investigate intermediate approximations to the full covariance matrix, with up to ∼ 80% of the matrix elements being zero, which could be advantageous for theoretical and hybrid approaches. We expect these results to be qualitatively insensitive to variations of the total cosmological volume, depending primarily on the bin size and shot-noise, thus making them particularly significant for present and future galaxy surveys.

Catalog-level blinding on the bispectrum for DESI-like galaxy surveys

Novell-Masot,

Gil-Marín,

Verde

et al. 2024

We evaluate the performance of the catalog-level blind analysis technique (blinding) presented in Brieden et al. (2020) in the context of a fixed template power spectrum and bispectrum analysis. This blinding scheme, which is tailored for galaxy redshift surveys similar to the Dark Energy Spectroscopic Instrument (DESI), has two components: the so-called “AP blinding” (concerning the dilation parameters α ∥, α ⊥) and “RSD blinding” (redshift space distortions, affecting the growth rate parameter f). Through extensive testing, including checks for the RSD part in cubic boxes, the impact of AP blinding on mocks with realistic survey sky coverage, and the implementation of a full AP+RSD blinding pipeline, our analysis demonstrates the effectiveness of the technique in preserving the integrity of cosmological parameter estimation when the analysis includes the bispectrum statistic. We emphasize the critical role of sophisticated — and difficult to accidentally unblind — blinding methods in precision cosmology.