A. S. Sengupta

Geometric algorithm for efficient coincident detection of gravitational waves

Data from a network of gravitational-wave detectors can be analyzed in coincidence to increase detection confidence and reduce nonstationarity of the background. We propose and explore a geometric algorithm to combine the data from a network of detectors. The algorithm makes optimal use of the variances and covariances that exist among the different parameters of a signal in a coincident detection of events. The new algorithm essentially associates with each trigger ellipsoidal regions in parameter space defined by the covariance matrix. Triggers from different detectors are deemed to be in coincidence if their ellipsoids have a nonzero overlap. Compared to an algorithm that uses uncorrelated windows separately for each of the signal parameters, the new algorithm greatly reduces the background rate thereby increasing detection efficiency at a given false alarm rate.

LIGO-Virgo searches for gravitational waves from coalescing binaries: A status update

Coalescing compact binaries of neutron stars and/or black holes are considered as one of the most promising sources for Earth based gravitational wave detectors. The LIGO-Virgo joint collaborations Compact Binary Coalescence (CBC) group is searching for gravitational waves emitted by these astrophysical systems by matched filtering the data against theoretically modeled template waveforms. A variety of waveform template families are employed depending on the mass range probed by the search and the stage of the inspiral phase targeted: restricted post-Newtonian for systems having total mass less than 35M?, numerical relativity inspired complete inspiral-merger-ringdown waveforms for more massive systems up to 100M? and ringdown templates for modeling perturbed black holes up to 500M?. We give a status update on CBC groups current efforts and upcoming plans in detecting signatures of astrophysical gravitational waves.

Cosmic microwave background power spectrum estimation with non-circular beam and incomplete sky coverage

Over the last decade, measurements of the cosmic microwave background (CMB) anisotropy have spearheaded the remarkable transition of cosmology into a precision science. However, addressing the systematic effects in the increasingly sensitive, high-resolution, full sky measurements from different CMB experiments poses a stiff challenge. The analysis techniques must not only be computationally fast to contend with the huge size of the data, but the higher sensitivity also limits the simplifying assumptions which can then be invoked to achieve the desired speed without compromising the final precision goals. While maximum likelihood is desirable, the enormous computational cost makes the suboptimal method of power spectrum estimation using pseudo-Cl unavoidable for high-resolution data. The debiasing of the pseudo-Cl needs account for non-circular beams, together with non-uniform sky coverage. We provide a (semi)analytic framework to estimate bias in the power spectrum due to the effect of beam non-circularity and non-uniform sky coverage, including incomplete/masked sky maps and scan strategy. The approach is perturbative in the distortion of the beam from non-circularity, allowing for rapid computations when the beam is mildly non-circular. We advocate that it is computationally advantageous to employ soft azimuthally apodized masks whose spherical harmonic transform die down fast with m. We numerically implement our method for non-rotating beams. We present preliminary estimates of the computational cost to evaluate the bias for the upcoming CMB anisotropy probes (l_(max) ~ 3000) , with angular resolution comparable to the Planck surveyor mission. We further show that this implementation and estimate are applicable for rotating beams on equal declination scans, and can possibly be extended to simple approximations to other scan strategies.

Least square ellipsoid fitting using iterative orthogonal transformations

We describe a generalised method for ellipsoid fitting against a minimum set of data points. The proposed method is numerically stable and applies to a wide range of ellipsoidal shapes, including highly elongated and arbitrarily oriented ellipsoids. This new method also provides for the retrieval of rotational angle and length of semi-axes of the fitted ellipsoids accurately. We demonstrate the efficacy of this algorithm on simulated data sets and also indicate its potential use in gravitational wave data analysis.