Pressure Profiles and Mass Estimates Using High-resolution Sunyaev–Zel’dovich Effect Observations of Zwicky 3146 with MUSTANG-2

Abstract

The galaxy cluster Zwicky 3146 is a sloshing cool core cluster at z = 0.291 that in X-ray imaging does not appear to exhibit significant pressure substructure in the intracluster medium (ICM). The published M 500 values range between 3.88 +0.62 −0.58 to 22.50 ± 7.58 × 10 14 M , where ICM-based estimates with reported errors < 20% suggest that we should expect to find a mass between 6.53 +0.44 −0.44 × 10 14 M (from Planck, with an 8.4σ detection) and 8.52 +1.77 −1.47 × 10 14 M (from ACT, with a 14σ detection). This broad range of masses is suggestive that there is ample room for improvement for all methods. Here, we investigate the ability to estimate the mass of Zwicky 3146 via the Sunyaev-Zel'dovich (SZ) effect with data taken at 90 GHz by MUSTANG-2 to a noise level better than 15 µK at the center, and a cluster detection of 104σ. We derive a pressure profile from our SZ data which is in excellent agreement with that derived from X-ray data. From our SZ-derived pressure profiles, we infer M 500 and M 2500 via three methods -Y -M scaling relations, the virial theorem, and hydrostatic equilibrium -where we employ X-ray constraints from XMM-Newton on the electron density profile when assuming hydrostatic equilibrium. Depending on the model and estimation method, our M 500 estimates range from 6.23 ± 0.59 to 10.6 ± 0.95 × 10 14 M , where our estimate from hydrostatic equilibrium, is 8.29 +1.93 −1.24 (±19.1% stat) +0.74 −0.68 (±8.6% sys, calibration) ×10 14 M . Our fiducial mass, derived from a Y -M relation is 8.16 +0.44 −0.54 (±5.5% stat) +0.46 −0.43 (±5.5% sys, Y -M ) +0.59 −0.55 (±7.0% sys, cal.) ×10 14 M . We investigate the consistency of our mass estimates and potential for otherwise unaddressed systematic errors within the MUSTANG-2 data. The inconsistencies among our mass estimates are not well explained by a potential systematic error in the MUSTANG-2 data.

A high-resolution view of the filament of gas between Abell 399 and Abell 401 from the Atacama Cosmology Telescope and MUSTANG-2

“…2). 5 The data were processed with the MIDAS pipeline, which recovers signals on scales of 9 < θ 180 (Romero et al 2020). The signal-to-noise map, smoothed by a 9 FWHM Gaussian kernel that results in a final 12.7 resolution, is also shown in Fig.…”

“…See Appendix B. 17 This bootstrapping procedure is described in more detail in Appendix A of Romero et al (2020). It consists in finding the intersection of Y (< R) computed from the model and the value for Y (< R 500c ) versus R 500c when assuming the Arnaud et al (2010) scaling relation, but does not account for intrinsic scatter as was done in Hilton et al (2021).…”

JoXSZ: Joint X-SZ fitting code for galaxy clusters

“…The ratio between the Xray and SZ temperatures has an unusual value, it is particularly far from 1 compared to what is expected from clumping effects as estimated from numerical expectations (Nagai & Lau 2011). This might be related to calibration systematics, such as the long-standing Chandra-XMM T systematics (Schellenberger et al 2015), or possible inaccuracies of the transfer function (Romero et al 2020). We emphasise that the conclusions accuracy does not depend exclusively on the correctness of operations that are performed on the data (the fitting code), but also on the lack of systematics in the input quantities (data, PSF, transfer function, instrument calibrations, etc.…”

Pact

“…Our radial coverage towards the centre falls short of the P13 joint XMM-Newton X-ray and Planck SZ profile, which goes down in radius by an extra factor of 2, to 0.02 × R 500 . Such a resolution is achievable in SZ alone, making use of high resolution facilities such as MUSTANG-2 and NIKA-2 (e.g., Ruppin et al 2018;Romero et al 2020), though assembling data for a sample as large or larger than our PACT31 sample with these two facilities would require a very large amount of time (e.g., the NIKA-2 SZ guaranteed-time programme of 300 hours for 45 clusters, Mayet et al 2020).…”