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Abstract:

The marked power spectrum — a two-point correlation function of a weighted density field — has emerged as a promising tool for extracting cosmological information from the large-scale structure of the Universe. In this work, we present the first comprehensive analytical study of the marked power spectrum's sensitivity to primordial non-Gaussianity (PNG) of the non-local type. We extend previous effective field theory frameworks to incorporate PNG, developing a complete theoretical model that we validate against the Quijote simulation suite. Through a systematic Fisher analysis, we compare the constraining power of the marked power spectrum against traditional approaches combining the power spectrum and bispectrum (P+B). We explore different choices of mark parameters to evaluate their impact on parameter constraints, particularly focusing on equilateral and orthogonal PNG as well as neutrino masses. Our analysis shows that while marking up underdense regions yields optimal constraints in the low shot-noise regime, the marked power spectrum's performance for discrete tracers with BOSS-like number densities does not surpass that of P+B analysis at mildly non-linear scales (k ≲ 0.25 h/Mpc). However, the marked approach offers several practical advantages, including simpler estimation procedures and potentially more manageable systematic effects. Our theoretical framework reveals how the marked power spectrum incorporates higher-order correlation information through terms resembling tree-level bispectra and power spectrum convolutions. This work establishes a robust foundation for applying marked statistics to future large-volume surveys.

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:

Measurements of weak gravitational lensing using the cosmic microwave background and the shapes of galaxies have refined our understanding of the late-time history of the Universe. While optical surveys have been the primary source for cosmic shear measurements, radio continuum surveys offer a promising avenue. Relevant radio sources, principally star-forming galaxies, have populations with higher mean redshifts and are less affected by dust extinction compared to optical sources. We focus on the future mid frequency SKA radio telescope and explore the cross-correlation between radio cosmic shear and CMB lensing convergence (γR × κ CMB). We investigate its potential in constraining the redshift distribution of radio galaxy samples and improving cosmological parameter constraints, including the neutrino sector. Using simulations of the first phase of the SKA and the Simons Observatory as a CMB experiment, we show how this γR × κ CMB cross-correlation can provide ∼ 1 - 10% calibration of the overall radio source redshift distribution, which in turn can significantly tighten otherwise degenerate measurements of radio galaxy bias. For the case of the next-generation full SKA, we find that the full combination of auto- and cross-spectra between γR and κ CMB becomes more powerful than the equivalent case using γO from a Euclid-like survey, with constraints 30% tighter on ΛCDM parameters and narrower bounds on sum of neutrino masses at the level of ∼ 24%. These constraints are also driven by higher redshifts and larger scales than other galaxy-CMB cross-correlations, potentially shedding light on different physical models. Our findings demonstrate the potential of radio weak lensing in improving constraints, and establish the groundwork for future joint analyses of CMB experiments and radio continuum surveys

Abstract:

We apply a suite of different estimators to the Quijote-png halo catalogs to find the best approach to constrain Primordial non-Gaussianity (PNG) at nonlinear cosmological scales, up to kmax = 0.5 h Mpc⁻¹. The set of summary statistics considered in our analysis includes the power spectrum, bispectrum, halo mass function, marked power spectrum, and marked modal bispectrum. Marked statistics are used here for the first time in the context of the PNG study. We perform a Fisher analysis to estimate their cosmological information content, showing substantial improvements when marked observables are added to the analysis. Starting from these summaries, we train deep neural networks to perform likelihood-free inference of cosmological and PNG parameters. We assess the performance of different subsets of summary statistics; in the case of fNL^equil, we find that a combination of the power spectrum and a suitable marked power spectrum outperforms the combination of power spectrum and bispectrum, the baseline statistics usually employed in PNG analysis. A minimal pipeline to analyze the statistics we identified can be implemented either with our ML algorithm or via more traditional estimators, if these are deemed more reliable.