arXiv subjects

Martin Hendry

Publications and source records attributed to Martin Hendry.

42 records · Page 3Linked to original sources

arXiv2007

Completeness - I. Revised, reviewed and revived

We have extended and improved the statistical test recently developed by Rauzy for assessing the completeness in apparent magnitude of magnitude-redshift surveys. Our improved test statistic retains the robust properties -- specifically independence of the spatial distribution of galaxies within a survey -- of the $T_c$ statistic introduced in Rauzy's seminal paper, but now accounts for the presence of both a faint and bright apparent magnitude limit. We demonstrate that a failure to include a bright magnitude limit can significantly affect the performance of Rauzy's $T_c$ statistic. Moreover, we have also introduced a new test statistic, $T_v$, defined in terms of the cumulative distance distribution of galaxies within a redshift survey. These test statistics represent powerful tools for identifying and characterising systematic errors in magnitude-redshift data. We apply our completeness test to three major redshift surveys: The Millennium Galaxy Catalogue (MGC), The Two Degree Field Galaxy Redshift Survey (2dFGRS), and the Sloan Digital Sky Survey (SDSS). We confirm that MGC and SDSS are complete up to the published (faint) apparent magnitude limit Furthermore, we show that, unless a bright limit is included for 2dFGRS, the data-set displays significant incompleteness at magnitudes brighter than the published limit of $m_{b_{j}}=19.45$ mag.

astro-ph↗

arXiv2005

Bayesian modeling of source confusion in LISA data

One of the greatest data analysis challenges for the Laser Interferometer Space Antenna (LISA) is the need to account for a large number of gravitational wave signals from compact binary systems expected to be present in the data. We introduce the basis of a Bayesian method that we believe can address this challenge, and demonstrate its effectiveness on a simplified problem involving one hundred synthetic sinusoidal signals in noise. We use a reversible jump Markov chain Monte Carlo technique to infer simultaneously the number of signals present, the parameters of each identified signal, and the noise level. Our approach therefore tackles the detection and parameter estimation problems simultaneously, without the need to evaluate formal model selection criteria, such as the Akaike Information Criterion or explicit Bayes factors. The method does not require a stopping criterion to determine the number of signals, and produces results which compare very favorably with classical spectral techniques.

gr-qc↗

arXiv2005

LISA source confusion: identification and characterization of signals

The Laser Interferometer Space Antenna (LISA) is expected to detect gravitational radiation from a large number of compact binary systems. We present a method by which these signals can be identified and have their parameters estimated. Our approach uses Bayesian inference, specifically the application of a Markov chain Monte Carlo method. The simulation study that we present here considers a large number of sinusoidal signals in noise, and our method estimates the number of periodic signals present in the data, the parameters for these signals and the noise level. The method is significantly better than classical spectral techniques at performing these tasks and does not use stopping criteria for estimating the number of signals present.

gr-qc↗

arXiv1999

What can we learn from the fluxes of 1.2 Jy IRAS sample?

We present a new method for fitting peculiar velocity models to complete flux limited magnitude-redshifts catalogues, using the luminosity function of the sources as a distance indicator. The method is characterized by its robustness. In particular, no assumptions are made concerning the spatial distribution of sources and their luminosity function. Moreover the inclusion of additional observables, such for example the one carrying the Tully-Fisher information, is straightforward. As an illustration of the method, the predicted IRAS peculiar velocity model is herein tested using the fluxes of the IRAS 1.2 Jy sample as the distance indicator. The results suggest that this model, while successful in reproducing locally the cosmic flow, fails to describe the kinematics on larger scales.

astro-ph↗

arXiv1993

Potent and Max-Flow Algorithms

Although Potent purports to use only radial velocities in retrieving the potential velocity field of galaxies, the derivation of transverse components is implicit in the smoothing procedures. Thus the possibility of using nonradial line integrals to derive the velocity field arises. In the case of inhomogeneous distributions of galaxies, the optimal path for integration need not be radial, and can be obtained by using max-flow algorithms. In this paper we present the results of using Dijkstra's algorithm to obtain this optimal path and velocity field.

astro-ph↗

arXiv1993

Bias in Velocity Field Recoveries

We investigate the effect of using different distance estimators on the recovery of the peculiar velocity field of galaxies using Potent. An inappropriate choice of distance estimator will give rise to spurious flows. We discuss methods of minimising these biases and the levels of accuracy required of distance estimators to retrieve velocity fields to a given standard.

astro-ph↗