Radio power correlations

2.2 Types of diffuse cluster radio emission

2.2.1 Radio Halos

2.2.1.2 Radio power correlations

With larger statistical samples of radio halos now available, studies of the 1.4 GHz radio halo power have shown it to be correlated with various other radio halo and cluster properties. Since the majority of radio halos have been detected at low redshift,z <0.4, it is not yet clear whether the observed correlations hold for higher redshift sources as well.

Halo size,RH

We mentioned at the beginning of this section that classical radio halos have physical sizes&1 Mpc (GRHs), but that there exist radio halos as small as a few hundred kpc. Giovannini et al.

(2009) found a correlation between the largest linear size of the radio halo and its emitted power which is continuous over the range of sizes. The slope of this correlation is in agreement with that obtained using only GRH sources (Feretti et al., 2012). Moreover, Murgia et al. (2009) studied the range of emissivities in the radio halo samples and found that the variation among radio halos of different size was small, supporting the conclusion that halo size and power are correlated.

Although there are a handful of outliers, all of which have radio powers higher than expected from their observed size (MACSJ0717.5+3745, Bonafede et al. 2009; A1213, Giovannini et al.

2009; and A1351, Giacintucci et al. 2009), the correlation between these two halo properties is relatively tight. This confirms that GRHs and radio halos of smaller size are indeed members of the same class as they share the same properties. We thus expect them to have a common formation mechanisms, unlike radio mini-halos which are discussed in§2.2.3.

X-ray cluster properties:L_X, T, M_X

A link between the radio halo power and the cluster X-ray luminosityL_Xwas first discovered by Liang et al. (2000) using the ten most securely identified radio halos available at the time. This correlation has since been confirmed by several authors, and radio power scaling relations have been defined for X-ray temperatureT, and massM (Bacchi et al., 2003; Cassano et al., 2006b, 2007). Previous studies only considered clusters hosting radio halos. Using an X-ray selected

sample of ROSAT clusters, Brunetti et al. (2007) were the first to observe a bimodality in the P_1.4GHz–L_X plane by determining radio power upper limits for those clusters with no evidence of a radio halo. They found the radio halos to have powers correlated with the LXof the host cluster, however the non-detections lay roughly an order of magnitude below this correlation.

This apparent dichotomy is expected to be related to the dynamical state of the cluster: disturbed systems host radio halos, whereas the upper limits belong to relaxed systems. However, this separation is not perfect and we will discuss the suspected merger connection in more detail in

§2.2.1.3.

Within the population of radio halos, there is some scatter in the P1.4GHz–LX correlation.

A few outliers, generally at lowL_X, host halos that are more powerful than their cluster X-ray luminosity would suggest. Conversely, the USSRHs all lie below the correlation, with radio powers somewhat lower than expected based on the cluster X-ray luminosity.

Finally, the non-thermal radio halo emission in well resolved systems has been found to be spatially correlated with the X-ray structure of the thermal bremsstrahlung emission (Govoni et al., 2001a; Feretti et al., 2001; Giacintucci et al., 2005), suggesting a link between the two plasmas (Govoni et al., 2001a). The slope of this relation is predicted by reacceleration models, however the correlation is not evident once halos with irregular or asymmetric morphologies are considered. From results of magnetic field modelling, Vacca et al. (2010) argue that this disparity may be caused by variations in the magnetic field on scales of∼hundreds of kpc.

SZ cluster properties: YSZ, M500,SZ

TheP_1.4GHz–L_Xrelation is probably the most well studied of the radio power correlations owing to the fact that radio halo campaigns have historically been carried out on X-ray selected samples – X-ray emission has been used to detect galaxy clusters since the 1970’s (Meekins et al., 1971;

Gursky et al., 1971). However, the thermal ICM also radiates at mm-wavelengths via the SZ effect and Moffet and Birkinshaw (1989) were the first to suggest a link between a cluster’s thermal SZ Compton-y parameter and the existence of a radio halo. This correlation has been confirmed (Basu, 2012) using clusters in the Planck 2013 SZ catalogue (Planck Collaboration et al., 2014b).

As in the case of LX, a bimodality is also observed in the P1.4GHz–YSZ domain (Cassano et al., 2013), although the separation appears to be slightly weaker than in X-ray selected samples (Sommer and Basu, 2014). In addition, Sommer and Basu (2014) find that SZ-selected samples appear to have a lower fall-out fraction of clusters without radio halos than that measured using X-ray clusters samples. They argue that this may be due to a combination of the fact that SZ and X-ray ICM emission evolve at different rates during cluster mergers, as well as a bias toward cool-core systems in X-ray selected samples.

One of the expected advantages of SZ-selected cluster samples is that the SZ effect is a more robust proxy for the cluster mass, as compared to the cluster X-ray luminosity (Carlstrom et al., 2002). From this one may expect a tighter correlation between the radio halo power and SZ-derived cluster properties, however, Cassano et al. (2013) find that the uncertainties in the best-fit parameters for theP_1.4GHz −Y_SZrelation are comparable to those for the X-ray selected sample.

No spatial link between (giant) radio halo emission and SZ emission has been found as yet, possibly owing to the relative lack of high-resolution SZ cluster maps. Cluster surveys with the NIKA (Adam et al., 2015), MUSTANG-1.5 (Young et al., 2014) and forthcoming MUSTANG- 2.0 instruments will provide the community with SZ cluster maps of sufficient angular resolution to make such a study possible.

Relaxation parameter,Γ

Wen and Han (2013) defined an optically-derived relaxation parameter, Γ, to quantify a clus- ter’s dynamical state from photometric data. By smoothing the brightness distribution of cluster members,Γis defined as the distance to the optimal plane defined by the distribution asymmetry, ridge flatness, and the normalised model-fitting residual. A negative value indicates a disturbed system, with positive values implying dynamical relaxation. They found an anti-correlation be- tween Γ and the 1.4 GHz radio power, with the more powerful halos hosted in clusters with smaller relaxation parameters. The scatter in the observed scaling relations betweenP1.4GHz and thermal cluster properties discussed above can be reduced by incorporating Γ to create a 3D correlation (Yuan et al., 2015).