Point source confusion in SZ cluster surveys

Bartlett, J. G.; Melin, Jean-Baptiste

doi:10.1051/0004-6361:20053395

Cited by 5 publications

(5 citation statements)

References 31 publications

(65 reference statements)

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“…In this case, contaminating signals from unresolved point‐like radio sources (e.g. Bartlett & Melin 2006) and fore/background galaxy groups (e.g. Hallman et al 2007) could affect the tSZ signal in the cluster outskirts.…”

Section: Discussionmentioning

confidence: 99%

“…However, the situation could be more complicated for the tSZ background. In this case, contaminating signals from unresolved point-like radio sources (e.g., Bartlett & Melin 2006) and fore/background galaxy groups (e.g., Hallman et al 2007) could affect the tSZ signal in the cluster outskirts. In this respect, the possibility of performing multi-frequency observations with the good angular resolution offered by interferometric techniques will surely help in characterizing and removing these contaminations.…”

Section: Discussionmentioning

confidence: 99%

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Reconstructing mass profiles of simulated galaxy clusters by combining Sunyaev-Zeldovich and X-ray images

Ameglio

Borgani

Pierpaoli

et al. 2009

Monthly Notices of the Royal Astronomical Society

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We present a method to recover mass profiles of galaxy clusters by combining data on the thermal Sunyaev-Zeldovich (tSZ) and X-ray imaging, thereby avoiding the use of any information on X-ray spectroscopy. This method, which represents the development of the geometrical deprojection technique presented in a previous paper by Ameglio et al., implements the solution of the hydrostatic equilibrium equation. In order to quantify the efficiency of our mass reconstructions, we apply our technique to a set of hydrodynamical simulations of galaxy clusters. We propose two versions of our method of mass reconstruction. Method 1 is completely modelindependent and assumes the values of gas density and total mass within different radial bins as fitting parameters. Method 2 assumes instead the analytic mass profile proposed by Navarro, Frenk & White (NFW). We find that the main source of bias in recovering the mass profiles is due to deviations from hydrostatic equilibrium, which cause an underestimation of the mass of about 10 per cent at r 500 and up to 20 per cent at the virial radius. Method 1 provides a reconstructed mass which is biased low by about 10 per cent, with a 20 per cent scatter, with respect to the true mass profiles. Method 2 proves to be more stable, reducing the scatter to 10 per cent, but with a larger bias of 20 per cent, mainly induced by the deviations from equilibrium in the outskirts. To better understand the results of Method 2, we check how well it allows us to recover the relation between mass and concentration parameter. When analysing the three-dimensional mass profiles, we find that including in the fit the inner 5 per cent of the virial radius biases high the halo concentration, thus suggesting that the NFW profile is not a perfect fit in the central regions of our simulations including cooling and star formation. Also, at a fixed mass, hotter clusters tend to have larger concentration. Our procedure recovers the concentration parameter essentially unbiased but with a scatter of about 50 per cent. In general, our analysis demonstrates that combining X-ray imaging with spatially resolved tSZ data is a valid alternative to using X-ray spectroscopy to recover the mass of galaxy clusters.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Reconstructing mass profiles of simulated galaxy clusters by combining Sunyaev-Zeldovich and X-ray images

Ameglio

Borgani

Pierpaoli

et al. 2009

Monthly Notices of the Royal Astronomical Society

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show abstract

Section: Discussionmentioning

confidence: 99%

“…However, the situation may be more complicated for the tSZ background. In this case, contaminating signals from unresolved point-like radio sources (e.g., Bartlett & Melin 2006) and fore/background galaxy groups (e.g., Hallman et al 2007) could affect the tSZ signal in the cluster outskirts. In this respect, the possibility of performing multi-frequency observations with good angular resolution will surely help in characterizing and removing these contaminations.…”

Section: Discussionmentioning

confidence: 99%

Joint deprojection of Sunyaev-Zeldovich and X-ray images of galaxy clusters

Ameglio

Borgani

Pierpaoli

et al. 2007

Monthly Notices of the Royal Astronomical Society

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We present two non‐parametric deprojection methods aimed at recovering the three‐dimensional density and temperature profiles of galaxy clusters from spatially resolved thermal Sunyaev–Zeldovich (tSZ) and X‐ray surface brightness maps, thus avoiding the use of X‐ray spectroscopic data. In both methods, the cluster is assumed spherically symmetric and modelled with an onion‐skin structure. The first method follows a direct geometrical approach, in which the deprojection is performed independently for the tSZ and X‐ray images, and the resulting profiles are then combined in order to extract density and temperature. The second method is based on the maximization of a single joint (tSZ and X‐ray) likelihood function. This allows us to simultaneously fit the two signals by following a Monte Carlo Markov Chain (MCMC) approach. These techniques are tested against both an idealized spherical β‐model cluster and a set of clusters extracted from cosmological hydrodynamical simulations with and without instrumental noise. In the first case, the quality of reconstruction is excellent and demonstrates that such methods do not suffer from any intrinsic bias. As for the application to simulations, we projected each cluster along the three orthogonal directions defined by the principal axes of the momentum of inertia tensor. This enables us to check any bias in the deprojection associated to the cluster elongation along the line of sight. After averaging over all the three projection directions, we find an overall good reconstruction, with a small (≲10 per cent) overestimate of the gas density profile. This turns into a comparable overestimate of the gas mass within the virial radius, which we ascribe to the presence of residual gas clumping. Apart from this small bias, the reconstruction has an intrinsic scatter of about 5 per cent, which is dominated by gas clumpiness. Cluster elongation along the line of sight biases the deprojected temperature profile upwards at r≲ 0.2rvir and downwards at larger radii. A comparable bias is also found in the deprojected temperature profile. Overall, this turns into a systematic underestimate of the gas mass, up to 10 per cent. We point out that our recovered temperature profiles are much closer to the mass‐weighted profiles than those obtained from the X‐ray spectroscopic‐like temperature. These results confirm the potentiality of combining tSZ and X‐ray imaging observations to the study of the thermal structure of the intra‐cluster medium out to large cluster‐centric distances.

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“…Apart from radio astronomy (Blain et al 1998;Condon 1974;Condon et al 2012), confusion noise is important for many other types of observations as well, such as FIR observations (Nguyen et al 2010;Magnelli et al 2013;Jeong et al 2005;Väisänen et al 2010;Gáspár & Rieke 2014;Kennedy & Wyatt 2012), X-ray deep observations (Barcons & Fabian 1990;Barcons 1992), gravitational waves (Crowder & Cornish 2004), weak lensing (Melchior & Viola 2012), Sunyaev-Zel'dovich (SZ) cluster surveys (Bartlett & Melin 2006), high precision astrometry (Hogg 2001) and studies of the galactic center (Eckart et al 2012;Stone et al 2012). A typical rule of thumb has been that one reaches diminishing returns when there are more than 1/30 sources per beam.…”

Section: Introductionmentioning

confidence: 99%

De-Confusing blended field images using graphs and bayesian priors

Safarzadeh,

Ferguson,

et al. 2014

Preprint

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We present a new technique for overcoming confusion noise in deep far-infrared Herschel space telescope images making use of prior information from shorter λ < 2µm wavelengths. For the deepest images obtained by Herschel, the flux limit due to source confusion is about a factor of three brighter than the flux limit due to instrumental noise and (smooth) sky background. We have investigated the possibility of de-confusing simulated Herschel PACS-160µm images by using strong Bayesian priors on the positions and weak priors on the flux of sources. We find the blended sources and group them together and simultaneously fit their fluxes. We derive the posterior probability distribution function of fluxes subject to these priors through Monte Carlo Markov Chain (MCMC) sampling by fitting the image. Assuming we can predict FIR flux of sources based on ultraviolet-optical part of their SEDs to within an order of magnitude, the simulations show that we can obtain reliable fluxes and uncertainties at least a factor of three fainter than the confusion noise limit of 3σ c =2.7 mJy in our simulated PACS-160 image. This technique could in principle be used to mitigate the effects of source confusion in any situation where one has prior information of positions and plausible fluxes of blended sources. For Herschel , application of this technique will improve our ability to constrain the dust content in normal galaxies at high redshift.

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Point source confusion in SZ cluster surveys

Cited by 5 publications

References 31 publications

Reconstructing mass profiles of simulated galaxy clusters by combining Sunyaev-Zeldovich and X-ray images

Reconstructing mass profiles of simulated galaxy clusters by combining Sunyaev-Zeldovich and X-ray images

Joint deprojection of Sunyaev-Zeldovich and X-ray images of galaxy clusters

De-Confusing blended field images using graphs and bayesian priors

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