We present a measurement of the relativistic corrections to the thermal Sunyaev–Zel’dovich (SZ) effect spectrum, the rSZ effect, toward the massive galaxy cluster RX J1347.5-1145 by combining submillimeter images from Herschel-SPIRE with millimeter wavelength Bolocam maps. Our analysis simultaneously models the SZ effect signal, the population of cosmic infrared background galaxies, and the galactic cirrus dust emission in a manner that fully accounts for their spatial and frequency-dependent correlations. Gravitational lensing of background galaxies by RX J1347.5-1145 is included in our methodology based on a mass model derived from the Hubble Space Telescope observations. Utilizing a set of realistic mock observations, we employ a forward modeling approach that accounts for the non-Gaussian covariances between the observed astrophysical components to determine the posterior distribution of SZ effect brightness values consistent with the observed data. We determine a maximum a posteriori (MAP) value of the average Comptonization parameter of the intracluster medium (ICM) within R 2500 to be 〈y〉2500 = 1.56 × 10−4, with corresponding 68% credible interval [1.42, 1.63] × 10−4, and a MAP ICM electron temperature of 〈T sz〉2500 = 22.4 keV with 68% credible interval spanning [10.4, 33.0] keV. This is in good agreement with the pressure-weighted temperature obtained from Chandra X-ray observations, 〈T x,pw〉2500 = 17.4 ± 2.3 keV. We aim to apply this methodology to comparable existing data for a sample of 39 galaxy clusters, with an estimated uncertainty on the ensemble mean 〈T sz〉2500 at the ≃ 1 keV level, sufficiently precise to probe ICM physics and to inform X-ray temperature calibration.
Observational data from astronomical imaging surveys contain information about a variety of source populations and environments, and their complexity will increase substantially as telescopes become more sensitive. Even for existing observations, measuring the correlations between pointlike and diffuse emission can be crucial to correctly inferring the properties of any individual component. For this task, information is typically lost, because of conservative data cuts, aggressive filtering, or incomplete treatment of contaminated data. We present the code PCAT-DE, an extension of probabilistic cataloging, designed to simultaneously model pointlike and diffuse signals. This work incorporates both explicit spatial templates and a set of nonparametric Fourier component templates into a forward model of astronomical images, reducing the number of processing steps applied to the observed data. Using synthetic Herschel-SPIRE multiband observations, we demonstrate that point-source and diffuse emission can be reliably separated and measured. We present two applications of this model. For the first, we perform point-source detection/photometry in the presence of galactic cirrus and demonstrate that cosmic infrared background galaxy counts can be recovered in cases of significant contamination. In the second, we show that the spatially extended thermal Sunyaev–Zel’dovich effect signal can be reliably measured even when it is subdominant to the pointlike emission from individual galaxies.
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