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Higher-order clustering statistics, like the galaxy bispectrum, can addcomplementary cosmological information to what is accessible with two-pointstatistics, like the power spectrum. While the standard way of measuring thebispectrum involves estimating a bispectrum value in a large number of Fouriertriangle bins, the compressed modal bispectrum approximates the bispectrum as alinear combination of basis functions and estimates the expansion coefficientson the chosen basis. In this work, we compare the two estimators by usingparallel pipelines to analyze the real-space halo bispectrum measured in asuite of $N$-body simulations corresponding to a total volume of $\sim 1{,}000\,h^{-3}\,{\rm Gpc}^3$, with covariance matrices estimated from 10,000 mockhalo catalogs. We find that the modal bispectrum yields constraints that areconsistent and competitive with the standard bispectrum analysis: for the halobias and shot noise parameters within the tree-level halo bispectrum model upto $k_{\rm max} \approx 0.06 \, (0.10) \,h\,{\rm Mpc}^{-1}$, only 6 (10) modalexpansion coefficients are necessary to obtain constraints equivalent to thestandard bispectrum estimator using $\sim$ 20 to 1,600 triangle bins, dependingon the bin width. For this work, we have implemented a modal estimator pipelineusing Markov Chain Monte Carlo simulations for the first time, and we discussin detail how the parameter posteriors and modal expansion are robust to, orsensitive to, several user settings within the modal bispectrum pipeline. Thecombination of the highly efficient compression that is achieved and the largenumber of mock catalogs available allows us to quantify how our modalbispectrum constraints depend on the number of mocks that are used to estimatecovariance matrices and the functional form of the likelihood.

Towards cosmological constraints from the compressed modal bispectrum: a robust comparison of real-space bispectrum estimators