Joint analysis of the thermal Sunyaev–Zeldovich effect and 2MASS galaxies: probing gas physics in the local Universe and beyond

Abstract

We present a first joint analysis of the power spectra of the thermal Sunyaev-Zeldovich (tSZ) effect measured by the Planck and the number density fluctuations of galaxies in the 2MASS redshift survey (2MRS) catalog, including their cross-correlation. Combining these measurements with the cosmic microwave background (CMB) data and CMB lensing of Planck assuming a flat ΛCDM model, we constrain the mass bias parameter asthe Planck cluster mass should be 35% lower than the true mass. The mass bias determined by the 2MRS-tSZ cross-power spectrum alone is consistent with that determined by the tSZ auto-power spectrum alone, suggesting that this large mass bias is not due to obvious systematics in the tSZ data. We find that the 2MRS-tSZ cross-power spectrum is more sensitive to less massive halos than the tSZ auto-power spectrum and it significantly improves a constraint on the mass dependence of the mass bias. The redshift dependence is not strongly constrained since the multipole range in which high redshift clusters mainly contribute to the tSZ auto is dominated by the contaminating sources. We conclude that no strong mass or redshift evolution of the mass bias is needed to explain the data.

New constraints on the mass bias of galaxy clusters from the power spectra of the thermal Sunyaev–Zeldovich effect and cosmic shear

“…(3) for the reason described in Section 3.1. 4 This constraint is different from that shown in Makiya et al (2018) due to the difference of dark matter mass function, the tSZ auto-power spectrum data and the treatment of the non-Gaussian term of the covariance matrix, as noted in Section 2 and 3. have found that the mass bias of Planck clusters is constrained to be B = 1.37 ± 0.20 or (1 − b) = B −1 = 0.73 ± 0.11 (68% C.L.) for σ8 < 0.9.…”

“…The Gaussian term of the covariance matrix is taken from Table 3 of Bolliet et al (2018). In Makiya et al (2018) we calculated the non-Gaussian term at each step of parameter inference. However Carron (2013) pointed out that such a parameter-dependent covariance matrix adds extra artificial information and can bias the parameter constraints.…”

Cross-correlation of the thermal Sunyaev–Zel’dovich effect and weak gravitational lensing: Planck and Subaru Hyper Suprime-Cam first-year data

“…surements. Although the signal of tSZ auto-power spectrum comes from galaxy clusters and groups with a wide range of mass (see, e.g., Makiya et al 2018), mass calibration measurements probe only into massive clusters. The tSZ-WL cross-correlation is sensitive to the structures at lower redshifts compared to the tSZ auto-power spectrum (Battaglia et al 2015).…”

Astrophysics with the Spatially and Spectrally Resolved Sunyaev-Zeldovich Effects

“…However, future CMB mission concepts such as CORE (Delabrouille et al 2018;Remazeilles et al 2018) and PICO could take a dramatic leap forward in sensitivity and spectral coverage versus that of Planck, enabling an increase in the number of detected SZ clusters to a few × 10 5 (Melin et al 2018b). This will open the way for detailed SZ studies with unprecedented precision, allow a vast number of cross-correlation studies, and provide additional constraints on cosmological parameters and neutrino mass and number (e.g., see Hill & Pajer 2013;Bolliet et al 2018;Makiya et al 2018;Salvati et al 2018;The Simons Observatory Collaboration et al 2018).…”