Projected-field kinetic Sunyaev-Zel'dovich Cross-correlations: halo model and forecasts. Issue 3 (15th March 2023)

• Record Type: Journal Article
• Authors: Bolliet, Boris; Colin Hill, J.; Ferraro, Simone; Kusiak, Aleksandra; Krolewski, Alex
• Is Part Of: Journal of cosmology and astroparticle physics. Volume 2023:Issue 3(2023)
• Publication Date: 2023-03-15
• Subjects: CMBR theory -- galaxy surveys -- semi-analytic modeling -- Sunyaev-Zeldovich effect; Cosmology -- Periodicals; Astrophysics -- Periodicals; 523.0105
• DOI: 10.1088/1475-7516/2023/03/039
• Languages: English
• ISSNs: 1475-7516

Abstract

Abstract: The kinetic Sunyaev-Zel'dovich (kSZ) effect, i.e., the Doppler boost of cosmic microwave background (CMB) photons caused by their scattering off free electrons in galaxy clusters and groups with non-zero bulk velocity, is a powerful window on baryons in the universe. We present the first halo-model computation of the cross-power spectrum of the "projected-field" kSZ signal with large-scale structure (LSS) tracers. We compare and validate our calculations against previous studies, which relied on N -body-calibrated effective formulas rather than the halo model. We forecast results for CMB maps from the Atacama Cosmology Telescope (AdvACT), Simons Observatory (SO), and CMB-S4, and LSS survey data from the Dark Energy Survey, the Vera C. Rubin Observatory (VRO), and Euclid . In cross-correlation with galaxy number density, for AdvACT × unWISE we forecast an 18 σ projected-field kSZ detection using data already in hand. Combining SO CMB maps and unWISE galaxy catalogs, we expect a 62 σ detection, yielding precise measurements of the gas density profile radial slopes. Additionally, we forecast first detections of the kSZ — galaxy weak lensing cross-correlation with AdvACT × VRO/ Euclid (at 6 σ ) and of the kSZ — CMB weak lensing cross-correlation with SO (at 16 σ ). Finally, ≈ 10-20% precision measurements of the shape of the gas density profile should be possible with CMB-S4 kSZ — CMB lensing cross-correlation without using any external datasets.