Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

We present a measurement of the pairwise kinematic Sunyaev-Zel’dovich (kSZ) signal using the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Sample (BGS) Data Release 1 (DR1) galaxy sample overlapping with the Atacama Cosmology Telescope (ACT) CMB temperature map. Our analysis makes use of 1.6 million galaxies with stellar masses $\log M_{\star }/M_{\odot }>10$ , and we explore measurements across a range of aperture sizes ( ${2.1}^{\prime }<{\theta }_{\mathrm{ap}}<{3.5}^{\prime }$ ) and stellar mass selections. This statistic directly probes the velocity field of the large-scale structure, a unique observable of cosmic dynamics and modified gravity. In particular, at low redshifts, this quantity is especially interesting, as deviations from General Relativity are expected to be largest. Notably, our result represents the highest-significance low-redshift ( $z\sim 0.3$ ) detection of the kSZ pairwise effect yet. In our most optimal configuration ( ${\theta }_{\mathrm{ap}}={3.3}^{\prime }$ , $\log M_{\star }>11$ ), we achieve a $5\sigma$ detection. Assuming that an estimate of the optical depth and galaxy bias of the sample exists via e.g., external observables, this measurement constrains the fundamental cosmological combination $H_{0}f{\sigma }_8^2$ . A key challenge is the degeneracy with the galaxy optical depth. We address this by combining CMB lensing, which allows us to infer the halo mass and galaxy population properties, with hydrodynamical simulation estimates of the mean optical depth, $\overline{\tau }$ . We stress that this is a proof-of-concept analysis; with BGS DR2 data we expect to improve the statistical precision by roughly a factor of two, paving the way toward robust tests of modified gravity with kSZ-informed velocity-field measurements at low redshift.

Abstract:

Skew spectra allow us to extract non-Gaussian information by taking the square of a map and finding the power spectrum of this new map with the original map. This allows us to use much of the infrastructure of power spectra and avoid the intricacies of estimating three point statistics. In this paper we present the first extension of skew spectra to arbitrary spin- $s$ fields, as a means to extract non-Gaussian information efficiently from cosmological datasets like cosmic shear or cosmic microwave background polarization. We apply the formalism to weak lensing in the context of large scale structure, and discuss different ways of combining fields to build skew spectra, all while avoiding the problems associated with mass mapping. We provide plots of these new statistics for $\mathrm{\Lambda }$ cold dark matter and vary cosmological parameters.

Abstract:

Radio-AGNs (active galactic nuclei) are observed to be more strongly clustered than non-active galaxies, though it is unclear whether this is simply due to their preference for massive host galaxies, or if they reside in distinct environments beyond this mass dependence. Using data from three fields covered by the MIGHTEE survey, we measure the angular two-point cross-correlation functions with a large, stellar mass-limited population of near-infrared selected galaxies, overcoming limitations of previous single-deep-field studies. By fitting halo occupation distribution models, we infer the galaxy bias parameters, b, for radio-AGN in three redshift ranges with median redshifts of , , and , finding , , and , respectively. The typical dark matter halo mass decreases with increasing redshift: , , and , which we attribute to the increased abundance of cold gas required to fuel AGN activity at earlier times. The AGN duty cycle is determined to be per cent, and we estimate that the total energy radiated by radio-jets over is per halo, which is sufficient to account for the observed excess heating of gas beyond that of gravitational collapse. Comparing the typical dark matter halo masses to the values obtained for the control sample, we find that the halo masses of radio-AGN are , , and times greater than those of the stellar mass- and redshift-matched galaxies. This difference could arise because AGN feedback suppresses stellar mass growth while leaving halo mass unchanged, or because radio-AGN preferentially reside in earlier forming haloes which are more strongly clustered.

Abstract:

Abstract Symbolic regression (SR) has emerged as a powerful method for uncovering interpretable mathematical relationships from data, offering a novel route to both scientific discovery and efficient empirical modelling. This article introduces the Special issue on symbolic regression for the physical sciences, motivated by the Royal Society discussion meeting held in April 2025. The contributions collected here span applications from automated equation discovery and emergent-phenomena modelling to the construction of compact emulators for computationally expensive simulations. The introductory review outlines the conceptual foundations of SR, contrasts it with conventional regression approaches and surveys its main use cases in the physical sciences, including the derivation of effective theories, empirical functional forms and surrogate models. We summarize methodological considerations such as search-space design, operator selection, complexity control, feature selection and integration with modern AI approaches. We also highlight ongoing challenges, including scalability, robustness to noise, overfitting and computational complexity. Finally, we emphasize emerging directions, particularly the incorporation of symmetry constraints, asymptotic behaviour and other theoretical information. Taken together, the papers in this Special issue illustrate the accelerating progress of SR and its growing relevance across the physical sciences. This article is part of the discussion meeting issue ‘Symbolic regression in the physical sciences’.