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Abstract:

Using an optimal quadratic estimator, we measure the large-scale cross-correlation between maps of the stochastic gravitational-wave intensity, constructed from the first three LIGO-Virgo observing runs, and a suite of tomographic samples of galaxies covering the redshift range z≲2. We do not detect any statistically significant cross-correlation, but the tomographic nature of the data allows us to place constraints on the (bias-weighted) production rate density of gravitational waves by astrophysical sources as a function of cosmic time. Our constraints range from bω˙GW<3.0×10-9 Gyr-1 at z∼0.06 to bω˙GW<2.7×10-7 Gyr-1 at z∼1.5 (95% confidence level), assuming a frequency spectrum of the form f2/3 (corresponding to an astrophysical background of binary mergers), and a reference frequency fref=25 Hz. Although these constraints are ∼2 orders of magnitude higher than the expected signal, we show that a detection may be possible with future experiments.

Abstract:

Marked power spectra provide a computationally efficient way to extract non-Gaussian information from the matter density field using the usual analysis tools developed for the power spectrum without the need for explicit calculation of higher-order correlators. In this work, we explore the optimal form of the mark function used for re-weighting the density field, to maximally constrain cosmology. We show that adding to the mark function or multiplying it by a constant leads to no additional information gain, which significantly reduces our search space for optimal marks. We quantify the information gain of this optimal function and compare it against mark functions previously proposed in the literature. We find that we can gain around ∼2 times smaller errors in 𝜎8 and ∼4 times smaller errors in Ω𝑚 compared to using the traditional power spectrum alone, an improvement of ∼60% compared to other proposed marks when applied to the same data set.