Biased Tracer Reconstruction with Halo Mass Information

Abstract

Plenty of crucial information about our universe is encoded in the cosmic large-scale structure (LSS). However, extractions of this information are usually hindered by the nonlinearities of the LSS, which can be largely alleviated by various techniques known as reconstruction. In realistic applications, the efficiencies of these methods are always degraded by many limiting factors, a quite important one being the shot noise induced by the finite number density of biased matter tracers (i.e., luminous galaxies or dark matter halos) in observations. In this work, we explore the gains of biased tracer reconstruction achieved from halo mass information, which can suppress the shot-noise component and dramatically improves the cross-correlation between tracer field and dark matter. To this end, we first closely study the clustering biases and the stochasticity properties of halo fields with various number densities under different weighting schemes, i.e., the uniform, mass, and optimal weightings. Then, we apply the biased tracer reconstruction method to these different weighted halo fields and investigate how linear bias and observational mass scatter affect the reconstruction performance. Our results demonstrate that halo masses are critical information for significantly improving the performance of biased tracer reconstruction, indicating great application potential for substantially promoting the precision of cosmological measurements (especially for baryon acoustic oscillations) in ambitious ongoing and future galaxy surveys.

Constraining Neutrino Cosmologies with Nonlinear Reconstruction

“…We have exclusively considered the nonlinear reconstruction methods based on solving the full nonlinear displacement field (Schmittfull et al 2017;Zhu et al 2017;Shi et al 2018). The applications to halo fields and redshift-space distortions have been studied extensively (see, e.g., Yu et al 2017;Zhu & Yu 2018;Birkin et al 2019;Wang & Pen 2019;Wang et al 2020;Liu et al 2021;Seo et al 2022). There are many other reconstruction methods based on different principles, e.g., iterative methods (Hada & Eisenstein 2018, optimization techniques (Seljak et al 2017;Feng et al 2018;Modi et al 2018), forwarding modeling (Jasche & Wandelt 2013;Wang et al 2014), effective-field-theory-based likelihood (Schmidt et al 2019;Elsner et al 2020), fast action minimization (Nusser & Branchini 2000;Sarpa et al 2019), and machine learning (Mao et al 2021;Shallue & Eisenstein 2022;Flöss & Meerburg 2023), etc., which could also provide an improvement in the cosmological parameter constraints.…”

TOI-2498 b: a hot bloated super-Neptune within the Neptune desert

“…The candidate was alerted as a TOI (TESS Object of Interest, Guerrero et al 2021) based on the identification of a transit signal from the SPOC pipeline (Jenkins 2002;Jenkins et al 2010Jenkins et al , 2020. This pipeline uses the PDCSAP (Presearch Data Conditioning Simple Aperture Photometry; Stumpe et al 2012Stumpe et al , 2014Smith et al 2012) light curves, which removes instrumental and some stellar trends from the SAP (Simple Aperture Photometry) data, but retains local features such as transits.…”

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Cosmological implications from multi-tracer BAO analysis with galaxies and voids

“…Besides, a number of different reconstruction algorithms are proposed, that aim at better estimations of the displacement fields (e.g. Burden et al 2015;Hada & Eisenstein 2018;Sarpa et al 2019;Kitaura et al 2021;Liu et al 2021;Seo et al 2021). BAO reconstruction is now a standard method for measuring BAO from spectroscopic galaxy data (e.g.…”