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Farhan Feroz

Publications and source records attributed to Farhan Feroz.

32 records · Page 2Linked to original sources

BAMBI: blind accelerated multimodal Bayesian inference

In this paper we present an algorithm for rapid Bayesian analysis that combines the benefits of nested sampling and artificial neural networks. The blind accelerated multimodal Bayesian inference (BAMBI) algorithm implements the MultiNest package for nested sampling as well as the training of an artificial neural network (NN) to learn the likelihood function. In the case of computationally expensive likelihoods, this allows the substitution of a much more rapid approximation in order to increase significantly the speed of the analysis. We begin by demonstrating, with a few toy examples, the ability of a NN to learn complicated likelihood surfaces. BAMBI's ability to decrease running time for Bayesian inference is then demonstrated in the context of estimating cosmological parameters from Wilkinson Microwave Anisotropy Probe and other observations. We show that valuable speed increases are achieved in addition to obtaining NNs trained on the likelihood functions for the different model and data combinations. These NNs can then be used for an even faster follow-up analysis using the same likelihood and different priors. This is a fully general algorithm that can be applied, without any pre-processing, to other problems with computationally expensive likelihood functions.

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Bayesian analysis of weak gravitational lensing and Sunyaev-Zel'dovich data for six galaxy clusters

We present an analysis of observations made with the Arcminute Microkelvin Imager (AMI) and the Canada-France-Hawaii Telescope (CFHT) of six galaxy clusters in a redshift range of 0.16--0.41. The cluster gas is modelled using the Sunyaev--Zel'dovich (SZ) data provided by AMI, while the total mass is modelled using the lensing data from the CFHT. In this paper, we: i) find very good agreement between SZ measurements (assuming large-scale virialisation and a gas-fraction prior) and lensing measurements of the total cluster masses out to r_200; ii) perform the first multiple-component weak-lensing analysis of A115; iii) confirm the unusual separation between the gas and mass components in A1914; iv) jointly analyse the SZ and lensing data for the relaxed cluster A611, confirming our use of a simulation-derived mass-temperature relation for parameterizing measurements of the SZ effect.

astro-ph.CO↗

Parameterization Effects in the analysis of AMI Sunyaev-Zel'dovich Observations

Most Sunyaev--Zel'dovich (SZ) and X-ray analyses of galaxy clusters try to constrain the cluster total mass and/or gas mass using parameterised models and assumptions of spherical symmetry and hydrostatic equilibrium. By numerically exploring the probability distributions of the cluster parameters given the simulated interferometric SZ data in the context of Bayesian methods, and assuming a beta-model for the electron number density we investigate the capability of this model and analysis to return the simulated cluster input quantities via three rameterisations. In parameterisation I we assume that the T is an input parameter. We find that parameterisation I can hardly constrain the cluster parameters. We then investigate parameterisations II and III in which fg(r200) replaces temperature as a main variable. In parameterisation II we relate M_T(r200) and T assuming hydrostatic equilibrium. We find that parameterisation II can constrain the cluster physical parameters but the temperature estimate is biased low. In parameterisation III, the virial theorem replaces the hydrostatic equilibrium assumption. We find that parameterisation III results in unbiased estimates of the cluster properties. We generate a second simulated cluster using a generalised NFW (GNFW) pressure profile and analyse it with an entropy based model to take into account the temperature gradient in our analysis and improve the cluster gas density distribution. This model also constrains the cluster physical parameters and the results show a radial decline in the gas temperature as expected. The mean cluster total mass estimates are also within 1 sigma from the simulated cluster true values. However, we find that for at least interferometric SZ analysis in practice at the present time, there is no differences in the AMI visibilities between the two models. This may of course change as the instruments improve.

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Further Sunyaev-Zel'dovich observations of two Planck ERCSC clusters with the Arcminute Microkelvin Imager

We present follow-up observations of two galaxy clusters detected blindly via the Sunyaev-Zel'dovich (SZ) effect and released in the Planck Early Release Compact Source Catalogue. We use the Arcminute Microkelvin Imager, a dual-array 14-18 GHz radio interferometer. After radio source subtraction, we find a SZ decrement of integrated flux density -1.08+/-0.10 mJy toward PLCKESZ G121.11+57.01, and improve the position measurement of the cluster, finding the centre to be RA 12 59 36.4, Dec +60 04 46.8, to an accuracy of 20 arcseconds. The region of PLCKESZ G115.71+17.52 contains strong extended emission, so we are unable to confirm the presence of this cluster via the SZ effect.

astro-ph.CO↗

Sunyaev-Zel'dovich observation of the Bullet-like cluster Abell 2146 with the Arcminute Microkelvin Imager

We present 13.9-18.2 GHz observations of the Sunyaev-Zel'dovich (SZ) effect towards Abell 2146 using the Arcminute Microkelvin Imager (AMI). The cluster is detected with a peak SNR ratio of 13 sigma in the radio source subtracted map. Comparison of the SZ and X-ray images suggests that they both have extended regions which lie approximately perpendicular to one another, with their emission peaks significantly displaced. These features indicate non-uniformities in the distributions of the gas temperature and pressure, indicative of a cluster merger. We use a Bayesian cluster analysis to explore the high-dimensional parameter space of the cluster-plus-sources model to obtain cluster parameter estimates in the presence of radio point sources, receiver noise and primordial CMB anisotropy; the probability of SZ + CMB primordial structure + radio sources + receiver noise to CMB + radio sources + receiver noise is 3 x 10^{6}:1. We compare the results from three different cluster models. Our preferred model exploits the observation that the gas fractions do not appear to vary greatly between clusters. Given the relative masses of the two merging systems in Abell 2146, the mean gas temperature can be deduced from the virial theorem (assuming all of the kinetic energy is in the form of internal gas energy) without being affected significantly by the merger event, provided the primary cluster was virialized before the merger. In this model we fit a simple spherical isothermal beta-model, despite the inadequacy of this model for a merging system like Abell 2146, and assume the cluster follows the mass-temperature relation of a virialized, singular, isothermal sphere. We note that this model avoids inferring large-scale cluster parameters internal to r_200 under the widely used assumption of hydrostatic equilibrium. We find that at r_200 M_T= 4.1 \pm 0.5 x 10^{14} h^{-1}M_sun and T=4.5 \pm 0.5 keV.

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Sunyaev-Zel'dovich observations of LoCuSS clusters with the Arcminute Microkelvin Imager: high X-ray luminosity sample

We present observations from the Small Array of the Arcminute Microkelvin Imager (AMI) of eight high X-ray luminosity galaxy cluster systems selected from the Local Cluster Substructure Survey (LoCuSS) sample.We detect the Sunyaev-Zel'dovich (SZ) effect in seven of these clusters. With the assumptions that galaxy clusters are isothermal, have a density profile described by a spherical b -model and obey the theoretical M-T relation, we are able to derive cluster parameters at r200 from our SZ data. With the additional assumption of hydrostatic equilibrium we are able to derive parameters at r500. We present posterior probability distributions for cluster parameters such as mass, radius and temperature (TSZ, MT). Combining our sample with that of AMI Consortium: Rodr'\iguez-Gonzálvez et al. (2011) and using large-radius X-ray temperature estimates (TX) from Chandra and Suzaku observations, we find that there is reasonable correspondence between TX and TSZ,MT values at low TX, but that for clusters with TX above around 6keV the correspondence breaks down with TX exceeding TSZ, MT; we stress that this finding is based on just ten clusters.

astro-ph.CO↗

Sunyaev-Zel'dovich observations of galaxy clusters out to the virial radius with the Arcminute Microkelvin Imager

We present observations using the Small Array of the Arcminute Microkelvin Imager (AMI; 14-18 GHz) of four Abell and three MACS clusters spanning 0.171-0.686 in redshift. We detect Sunyaev-Zel'dovich (SZ) signals in five of these without any attempt at source subtraction, although strong source contamination is present. With radio-source measurements from high-resolution observations, and under the assumptions of spherical $β$-model, isothermality and hydrostatic equilibrium, a Bayesian analysis of the data in the visibility plane detects extended SZ decrements in all seven clusters over and above receiver noise, radio sources and primary CMB imprints. Bayesian evidence ratios range from 10^{11}:1 to 10^{43}:1 for six of the clusters and 3000:1 for one with substantially less data than the others. We present posterior probability distributions for, e.g., total mass and gas fraction averaged over radii internal to which the mean overdensity is 1000, 500 and 200, r_200 being the virial radius. Reaching r_200 involves some extrapolation for the nearer clusters but not for the more-distant ones. We find that our estimates of gas fraction are low (compared with most in the literature) and decrease with increasing radius. These results appear to be consistent with the notion that gas temperature in fact falls with distance (away from near the cluster centre) out to the virial radius.

astro-ph.CO↗

Classifying LISA gravitational wave burst signals using Bayesian evidence

We consider the problem of characterisation of burst sources detected with the Laser Interferometer Space Antenna (LISA) using the multi-modal nested sampling algorithm, MultiNest. We use MultiNest as a tool to search for modelled bursts from cosmic string cusps, and compute the Bayesian evidence associated with the cosmic string model. As an alternative burst model, we consider sine-Gaussian burst signals, and show how the evidence ratio can be used to choose between these two alternatives. We present results from an application of MultiNest to the last round of the Mock LISA Data Challenge, in which we were able to successfully detect and characterise all three of the cosmic string burst sources present in the release data set. We also present results of independent trials and show that MultiNest can detect cosmic string signals with signal-to-noise ratio (SNR) as low as ~7 and sine-Gaussian signals with SNR as low as ~8. In both cases, we show that the threshold at which the sources become detectable coincides with the SNR at which the evidence ratio begins to favour the correct model over the alternative.

gr-qc↗

The search for spinning black hole binaries in mock LISA data using a genetic algorithm

Coalescing massive Black Hole binaries are the strongest and probably the most important gravitational wave sources in the LISA band. The spin and orbital precessions bring complexity in the waveform and make the likelihood surface richer in structure as compared to the non-spinning case. We introduce an extended multimodal genetic algorithm which utilizes the properties of the signal and the detector response function to analyze the data from the third round of mock LISA data challenge (MLDC 3.2). The performance of this method is comparable, if not better, to already existing algorithms. We have found all five sources present in MLDC 3.2 and recovered the coalescence time, chirp mass, mass ratio and sky location with reasonable accuracy. As for the orbital angular momentum and two spins of the Black Holes, we have found a large number of widely separated modes in the parameter space with similar maximum likelihood values.

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The Mock LISA Data Challenges: from Challenge 3 to Challenge 4

The Mock LISA Data Challenges are a program to demonstrate LISA data-analysis capabilities and to encourage their development. Each round of challenges consists of one or more datasets containing simulated instrument noise and gravitational waves from sources of undisclosed parameters. Participants analyze the datasets and report best-fit solutions for the source parameters. Here we present the results of the third challenge, issued in Apr 2008, which demonstrated the positive recovery of signals from chirping Galactic binaries, from spinning supermassive--black-hole binaries (with optimal SNRs between ~ 10 and 2000), from simultaneous extreme-mass-ratio inspirals (SNRs of 10-50), from cosmic-string-cusp bursts (SNRs of 10-100), and from a relatively loud isotropic background with Omega_gw(f) ~ 10^-11, slightly below the LISA instrument noise.

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Use of the MultiNest algorithm for gravitational wave data analysis

We describe an application of the MultiNest algorithm to gravitational wave data analysis. MultiNest is a multimodal nested sampling algorithm designed to efficiently evaluate the Bayesian evidence and return posterior probability densities for likelihood surfaces containing multiple secondary modes. The algorithm employs a set of live points which are updated by partitioning the set into multiple overlapping ellipsoids and sampling uniformly from within them. This set of live points climbs up the likelihood surface through nested iso-likelihood contours and the evidence and posterior distributions can be recovered from the point set evolution. The algorithm is model-independent in the sense that the specific problem being tackled enters only through the likelihood computation, and does not change how the live point set is updated. In this paper, we consider the use of the algorithm for gravitational wave data analysis by searching a simulated LISA data set containing two non-spinning supermassive black hole binary signals. The algorithm is able to rapidly identify all the modes of the solution and recover the true parameters of the sources to high precision.

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Follow-up observations at 16 and 33 GHz of extragalactic sources from WMAP 3-year data: I - Spectral properties

We present follow-up observations of 97 point sources from the Wilkinson Microwave Anisotropy Probe (WMAP) 3-year data, contained within the New Extragalactic WMAP Point Source (NEWPS) catalogue between declinations of -4 and +60 degrees; the sources form a flux-density-limited sample complete to 1.1 Jy (approximately 5 sigma) at 33 GHz. Our observations were made at 16 GHz using the Arcminute Microkelvin Imager (AMI) and at 33 GHz with the Very Small Array (VSA). 94 of the sources have reliable, simultaneous -- typically a few minutes apart -- observations with both telescopes. The spectra between 13.9 and 33.75 GHz are very different from those of bright sources at low frequency: 44 per cent have rising spectra (alpha < 0.0), where flux density is proportional to frequency^-alpha, and 93 per cent have spectra with alpha < 0.5; the median spectral index is 0.04. For the brighter sources, the agreement between VSA and WMAP 33-GHz flux densities averaged over sources is very good. However, for the fainter sources, the VSA tends to measure lower values for the flux densities than WMAP. We suggest that the main cause of this effect is Eddington bias arising from variability.

astro-ph.CO↗

Follow-up observations at 16 and 33 GHz of extragalactic sources from WMAP 3-year data: II - Flux-density variability

Using the Arcminute Microkelvin Imager (AMI) at 16 GHz and the Very Small Array (VSA) at 33 GHz to make follow-up observations of sources in the New Extragalactic WMAP Point Source Catalogue, we have investigated the flux-density variability in a complete sample of 97 sources over timescales of a few months to approximately 1.5 years. We find that 53 per cent of the 93 sources, for which we have multiple observations, are variable, at the 99 per cent confidence level, above the flux density calibration uncertainties of approximately 4 per cent at 16 GHz; the fraction of sources having varied by more than 20 per cent is 15 per cent at 16 GHz and 20 per cent at 33 GHz. Not only is this common occurrence of variability at high frequency of interest for source physics, but strategies for coping with source contamination in CMB work must take this variability into account. There is no strong evidence of a correlation between variability and flux density for the sample as a whole. Using a maximum-likelihood method, we calculate the correlation in the variability at the two frequencies in a subset of sources classified as variable from both the AMI and VSA data and find the Pearson product-moment correlation coefficient to be very high (0.955 +/- 0.034). We also find the degree of variability at 16 GHz (0.202 +/- 0.028) to be very similar to that at 33 GHz (0.224 +/- 0.039). Finally, we have investigated the relationship between variability and spectral index, alpha_13.9^33.75 (where S proportional to nu^-alpha), and find a significant difference in the spectral indices of the variable sources (-0.06 +/- 0.05) and non-variable sources (0.13 +/- 0.04).

astro-ph.CO↗

Multimodal nested sampling: an efficient and robust alternative to MCMC methods for astronomical data analysis

In performing a Bayesian analysis of astronomical data, two difficult problems often emerge. First, in estimating the parameters of some model for the data, the resulting posterior distribution may be multimodal or exhibit pronounced (curving) degeneracies, which can cause problems for traditional MCMC sampling methods. Second, in selecting between a set of competing models, calculation of the Bayesian evidence for each model is computationally expensive. The nested sampling method introduced by Skilling (2004), has greatly reduced the computational expense of calculating evidences and also produces posterior inferences as a by-product. This method has been applied successfully in cosmological applications by Mukherjee et al. (2006), but their implementation was efficient only for unimodal distributions without pronounced degeneracies. Shaw et al. (2007), recently introduced a clustered nested sampling method which is significantly more efficient in sampling from multimodal posteriors and also determines the expectation and variance of the final evidence from a single run of the algorithm, hence providing a further increase in efficiency. In this paper, we build on the work of Shaw et al. and present three new methods for sampling and evidence evaluation from distributions that may contain multiple modes and significant degeneracies; we also present an even more efficient technique for estimating the uncertainty on the evaluated evidence. These methods lead to a further substantial improvement in sampling efficiency and robustness, and are applied to toy problems to demonstrate the accuracy and economy of the evidence calculation and parameter estimation. Finally, we discuss the use of these methods in performing Bayesian object detection in astronomical datasets.

astro-ph↗