arXiv subjects

Zachery Brown

Publications and source records attributed to Zachery Brown.

5 recordsLinked to original sources

arXiv2026

Increasing the sensitivity of full-shape galaxy clustering measurements in configuration-space with three-point statistics

We investigate the cosmological constraining power of a compressed line of sight dependent three point correlation function (3PCF) estimator on small scales (<80 Mpc/h) in configuration space, with a particular focus on emission line galaxies (ELGs) targeted by the Nancy Grace Roman Space Telescope's Galaxy Redshift Survey (GRS), and complementary luminous red galaxy (LRG) samples observed by the Dark Energy Spectroscopic Instrument (DESI). These scales avoid the baryon acoustic oscillation (BAO) feature and are therefore expected to provide information that is largely complementary to standard BAO measurements, while retaining partial overlap with full shape clustering analyses. Our forecasts are based on AbacusSummit simulations at z = 1.1 and z = 0.8, populated with galaxies using halo occupation distribution (HOD) models matched to Roman ELG and DESI LRG samples respectively. The three point measurements are computed with TriCo, a fast configuration space triangle counting code developed for this analysis. After marginalizing over uncertainties in the galaxy halo connection, we find that incorporating the 3PCF yields a substantial improvement over two point statistics alone, tightening the constraint on sigma_8 by a factor of 5 in our fiducial forecast. This gain arises not from a localized feature or specific scale range, but from the cumulative information content across triangle configurations. Restricting to the monopole of the 3PCF captures only part of this information, with the full line of sight dependent measurement providing an additional factor of 2 to 3 improvement over the monopole. Adding line of sight dependent three point information substantially increases the constraining power of small scale configuration space galaxy clustering.

astro-ph.CO↗

arXiv2026

Bounding the Effect of HOD Assumptions on Small-Scale Clustering Constraints

Small-scale galaxy clustering is expected to contain substantial cosmological information, but the extent to which this information constrains halo-based cosmologies independent of an assumed galaxy--halo connection remains unclear. We quantify this dependence using LRG-like mock galaxy catalogs built from 81 cosmologies in the {\tt \textsc{AbacusSummit}} suite. We analyze two-point correlation function multipoles on scales ranging from $5$--$80$ Mpc/$h$ and compare two limiting treatments, the \enquote{floor} and \enquote{ceiling}, of the standard five-parameter HOD model. In the conservative floor case, we impose only broad initial HOD bounds and profile over HOD parameters to determine the minimum constraining power available; we accomplish this with {\tt HODmin}, a two-stage global optimization algorithm written for minimizing $χ^2$ in HOD space. In the optimistic ceiling case, we assume the HOD parameters are known exactly. We find a significant difference between the floor and ceiling when comparing against the same Planck $Λ$CDM mock data vector with identical modeling assumptions: for the floor, $25\%$ of the discrete {\tt \textsc{AbacusSummit}} cosmologies tested are excluded at $3σ$, whereas for the ceiling, $\sim81\%$ are excluded. Many cosmologies agree well with data in the floor, and yet in the ceiling are excluded by multiple orders of magnitude in $χ^2$. We therefore observe the strength of small-scale clustering constraints depends heavily on the amount of prior HOD information assumed. We compare the sensitivity of this effect to various choices like scale cut, angle cut, multipole inclusion, mock phase, and mock HOD model. Our wide floor--ceiling bracket indicates that informative galaxy--halo priors are necessary for extracting strong small-scale clustering constraints.

astro-ph.CO↗

arXiv2025

Beyond the two-point correlation: constraining primordial non-gaussianity with density perturbation moments

Constraining primordial non-Gaussianities (PNGs) in the large-scale cosmic structure (LSS) is an important step in understanding properties of the early universe, specifically in distinguishing between different inflationary models. Measuring PNG relies on evaluating the scale-dependent correlations in the density field. New summary statistics beyond the two- and three-point correlation functions in configuration space and their Fourier-space counterparts, the power- and bi-spectrum may provide increased sensitivity. We introduce a new method for extracting the PNG signal imprinted on the LSS by using the first three Gaussian moments of the normalized correlation in density perturbations, evaluated at varying distance scales. We aim to assess this method's sensitivity to local PNG, parameterized by $f_ {\mathrm{NL}}$. We perform spherical convolutions at a range of scales on dark matter halo simulations to measure the scale-dependent correlations in the density field. From these, we compute the first three moments and compare them to a model expectation vector, parameterized to the second power in $f_{\mathrm{NL}}$. Our method provides about 21% improvement in sensitivity to $f_{\mathrm{NL}}$ with respect to using the two point correlation function alone. Notably, we find that the second moment alone carries nearly as much constraining power as the mean, highlighting the potential of higher-order statistics. Given its simplicity and efficiency, this framework is well-suited for application to current and upcoming large-scale surveys such as DESI.

astro-ph.CO↗

arXiv2021

ConKer: evaluating isotropic correlations of arbitrary order

High order correlations in the cosmic matter density have become increasingly valuable in cosmological analyses. However, computing such correlation functions is computationally expensive. We aim to circumvent these challenges by designing a new method of estimating correlation functions. This is realized in ConKer, an algorithm that performs FFT convolutions of matter distributions with spherical kernels. ConKer is applied to the CMASS sample of the SDSS DR12 galaxy survey and used to compute the isotropic correlation up to correlation order n = 5. We also compare the n = 2 and n = 3 cases to traditional algorithms to verify the accuracy of the new method. We perform a timing study of the algorithm and find that two of the three components of the algorithm are independent of the catalog size, N, while one component is O(N), which starts dominating for catalogs larger than 10M objects. For n < 5 the dominant calculation is O(N^(4/3logN)), where N is the number of the grid cells. For higher n, the execution time is expected to be dominated by a component with time complexity O(N^((n+2)/3)). We find ConKer to be a fast and accurate method of probing high order correlations in the cosmic matter density.

astro-ph.CO↗

arXiv2019

Fast Mock Catalog Generation for Large Scale Structure Modeling

To understand the universe and to interpret the cosmological parameters governing its evolution it is necessary to contrast the data from galaxy surveys with simulation. Typically it entails using computationally expensive N -body simulations. Computational overhead makes it difficult to test the dependence of galaxy large scale structure on multiple cosmological parameters. In this work, we suggest a parametric model to simulate large scale structure. The new method provides a fast way to generate mock catalogs for testing multiple cosmological parameters as well as providing a test bench for code development.

astro-ph.CO↗