Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

Redshift-independent distances underpin much of astrophysics, and there exists a plethora of methods to estimate them. However, the extent to which the distances they imply are consistent, while crucial for the integrity of the distance ladder, has been little explored. We construct a statistical framework to assess both internal (between measurements with the same method) and external (between method) consistency by comparing differences between distances to their quoted statistical uncertainties in the National Aeronautics and Space Administration/Infrared Processing and Analysis Center (NASA/IPAC) Extragalactic Data base of Distances (NED-D). 66 of the 76 indicators in NED-D are amenable to a consistency test by having at least two measurements to the same galaxy or at least one measurement to a galaxy also measured by another method. We find that only 12 of these methods produce self-consistent distances across literature determinations, of which seven are also consistent with distances to the same galaxies measured by all other methods. The most consistent six methods (M-stars luminosity, Novae, Masers, Globular Cluster Fundamental Plane, O- and B-type Supergiants, and BL Lac Luminosity) also give similar average distances to the mean of all indicators, while the 7th (Proper Motion) underestimates distances relative to the mean by 17.1 per cent. We also investigate consistency of Cepheid distances in the SH0ES 2022 catalogue, finding no evidence for unaccounted-for systematics. Our NED-D results imply that considerable work remains to obtain reliable distances by a multitude of methods, a crucial endeavour for constructing a multiply cross-checked and fully robust distance ladder.

Abstract:

According to cosmic microwave background (CMB) measurements, baryonic matter constitutes about 5% of the mass-energy density of the universe. A significant population of these baryons, for a long time referred to as “missing”, resides in a low density, warm-hot intergalactic medium (WHIM) outside galaxy clusters, tracing the “cosmic web”, a network of large scale dark matter filaments. Various studies have detected this inter-cluster gas, both by stacking and by observing individual filaments in compact, massive systems. In this paper, we study short filaments (< 10 Mpc) connecting massive clusters (〈M 500〉 ≈ 3 × 1014 M⊙) detected by the Atacama Cosmology Telescope (ACT) using the scattering of CMB light off the ionised gas, a phenomenon known as the thermal Sunyaev-Zeldovich (tSZ) effect. The first part of this work is a search for suitable candidates for high resolution follow-up tSZ observations. We identify four cluster pairs with an intercluster signal above the noise floor (S/N > 2), including two with a tentative > 2σ statistical significance for an intercluster bridge from the ACT data alone. In the second part of this work, starting from the same cluster sample, we directly stack on ∼100 cluster pairs and observe an excess SZ signal between the stacked clusters of y = (7.2+2.3 -2.5) × 10-7 with a significance of 3.3σ. It is the first tSZ measurement of hot gas between clusters in this range of masses at moderate redshift (〈z〉 ≈ 0.5). We compare this to the signal from simulated cluster pairs with similar redshifts and separations in the THE300 and MAGNETICUM Pathfinder cosmological simulations and find broad consistency. Additionally, we show that our measurement is consistent with scaling relations between filament parameters and mass of the embedded halos identified in simulations.

Abstract:

The two-point correlation function of the galaxy spatial distribution is a major cosmological observable that enables constraints on the dynamics and geometry of the Universe. The Euclid mission is aimed at performing an extensive spectroscopic survey of approximately 20–30 million H α -emitting galaxies up to a redshift of about 2. This ambitious project seeks to elucidate the nature of dark energy by mapping the three-dimensional clustering of galaxies over a significant portion of the sky. This paper presents the methodology and software developed for estimating the three-dimensional two-point correlation function within the Euclid Science Ground Segment. The software is designed to overcome the significant challenges posed by the large and complex Euclid dataset, which involves millions of galaxies. The key challenges include efficient pair counting, managing computational resources, and ensuring the accuracy of the correlation function estimation. The software leverages advanced algorithms, including k -d tree, octree, and linked-list data partitioning strategies, to optimise the pair-counting process. These methods are crucial for handling the massive volume of data efficiently. The implementation also includes parallel processing capabilities using shared-memory open multi-processing to further enhance performance and reduce computation times. Extensive validation and performance testing of the software are presented. Those have been performed by using various mock galaxy catalogues to ensure that it meets the stringent accuracy requirement of the Euclid mission. The results indicate that the software is robust and can reliably estimate the two-point correlation function, which is essential for deriving cosmological parameters with high precision. Furthermore, the paper discusses the expected performance of the software during different stages of Euclid Wide Survey observations and forecasts how the precision of the correlation function measurements will improve over the mission’s timeline, highlighting the software’s capability to handle large datasets efficiently.