Testing the normality of the gravitational wave data with a low cost recursive estimate of the kurtosis

We propose a monitoring indicator of the normality of the output of a gravitational wave detector. This indicator is based on the estimation of the kurtosis (i.e., the 4th order statistical moment normalized by the variance squared) of the data selected in a time sliding window. We show how a low cost (because recursive) implementation of such estimation is possible and we illustrate the validity of the presented approach with a few examples using simulated random noises.Comment: 4 pages, 3 figures. In the Proceedings of the 3rd workshop on Physics in Signal and Image Processing (Grenoble), 200

Adaptive filtering techniques for interferometric data preparation: removal of long-term sinusoidal signals and oscillatory transients

We propose an adaptive denoising scheme for poorly modeled non-Gaussian features in the gravitational wave interferometric data. Preliminary tests on real data show encouraging results.Comment: 4 pages, 2 figures. Proceedings of GWDAW99 (Roma, Dec. 1999), to appear in Int. J. Mod. Phys.

Uncertainty and Spectrogram Geometry

International audienceUltimate possibilities of localization for time-frequency representations are first reviewed from a joint perspective, evidencing that Heisenberg-type pointwise limits are not exclusive of sharp localization along trajectories in the plane. Spectrogram reassignment offers such a possibility and, in order to revisit its connection with uncertainty, geometrical properties of spectrograms are statistically investigated in the generic case of white Gaussian noise. Based on Voronoi tessellations and Delaunay triangulations attached to extrema, it is shown that, in a first approximation, local energy ''patches'' are distributed according to a randomized hexagonal lattice with a typical scale within a factor of a few that of minimum uncertainty Gabor logons

Making Reassignment Adjustable: the Levenberg-Marquardt Approach

accepted for publication, to appear in Proc. of IEEE Int. Conf. on Acoust., Speech and Signal Proc. ICASSP-12, Kyoto (Japan), March 25-30, 2012.International audienceThis paper presents a new time-frequency reassignment process of the spectrogram, called the Levenberg-Marquardt reassignment. Compared to the classical one, this new reassignment process uses the second-order derivatives of the phase of the short-time Fourier transform, and provides the user with a setting parameter. This parameter allows him to produce either a weaker or a stronger localization of the signal components in the time-frequency plane

Best chirplet chain: near-optimal detection of gravitational wave chirps

The list of putative sources of gravitational waves possibly detected by the ongoing worldwide network of large scale interferometers has been continuously growing in the last years. For some of them, the detection is made difficult by the lack of a complete information about the expected signal. We concentrate on the case where the expected GW is a quasi-periodic frequency modulated signal i.e., a chirp. In this article, we address the question of detecting an a priori unknown GW chirp. We introduce a general chirp model and claim that it includes all physically realistic GW chirps. We produce a finite grid of template waveforms which samples the resulting set of possible chirps. If we follow the classical approach (used for the detection of inspiralling binary chirps, for instance), we would build a bank of quadrature matched filters comparing the data to each of the templates of this grid. The detection would then be achieved by thresholding the output, the maximum giving the individual which best fits the data. In the present case, this exhaustive search is not tractable because of the very large number of templates in the grid. We show that the exhaustive search can be reformulated (using approximations) as a pattern search in the time-frequency plane. This motivates an approximate but feasible alternative solution which is clearly linked to the optimal one. [abridged version of the abstract]Comment: 23 pages, 9 figures. Accepted for publication in Phys. Rev D Some typos corrected and changes made according to referee's comment

Partition du plan temps-fréquence et réallocation

Le problème que nous abordons est celui du découpage du plan temps-fréquence en vue d'obtenir une description simplifiée d'un signal multicomposante qui rende possible l'extraction de chacune de ses composantes et leur reconstruction. La solution proposée s'appuie sur une nouvelle extension de la méthode de réallocation, qui permet très naturellement d'extraire les différentes composantes à l'aide d'une technique de classification non supervisée. L'originalité de ce travail réside dans la manière dont on extrait l'information qui sert à construire la partition. A cette fin, on utilise non pas la distribution temps-fréquence elle-même, mais le champ de ses vecteurs de réallocation, ce qui apporte aussi un nouvel éclairage sur la question de ce qu'est une composante d'un signal

A learning approach to the detection of gravitational wave transients

We investigate the class of quadratic detectors (i.e., the statistic is a bilinear function of the data) for the detection of poorly modeled gravitational transients of short duration. We point out that all such detection methods are equivalent to passing the signal through a filter bank and linearly combine the output energy. Existing methods for the choice of the filter bank and of the weight parameters rely essentially on the two following ideas: (i) the use of the likelihood function based on a (possibly non-informative) statistical model of the signal and the noise, (ii) the use of Monte-Carlo simulations for the tuning of parametric filters to get the best detection probability keeping fixed the false alarm rate. We propose a third approach according to which the filter bank is "learned" from a set of training data. By-products of this viewpoint are that, contrarily to previous methods, (i) there is no requirement of an explicit description of the probability density function of the data when the signal is present and (ii) the filters we use are non-parametric. The learning procedure may be described as a two step process: first, estimate the mean and covariance of the signal with the training data; second, find the filters which maximize a contrast criterion referred to as deflection between the "noise only" and "signal+noise" hypothesis. The deflection is homogeneous to the signal-to-noise ratio and it uses the quantities estimated at the first step. We apply this original method to the problem of the detection of supernovae core collapses. We use the catalog of waveforms provided recently by Dimmelmeier et al. to train our algorithm. We expect such detector to have better performances on this particular problem provided that the reference signals are reliable.Comment: 22 pages, 4 figure

The Antares Neutrino Telescope and Multi-Messenger Astronomy

Antares is currently the largest neutrino telescope operating in the Northern Hemisphere, aiming at the detection of high-energy neutrinos from astrophysical sources. Such observations would provide important clues about the processes at work in those sources, and possibly help solve the puzzle of ultra-high energy cosmic rays. In this context, Antares is developing several programs to improve its capabilities of revealing possible spatial and/or temporal correlations of neutrinos with other cosmic messengers: photons, cosmic rays and gravitational waves. The neutrino telescope and its most recent results are presented, together with these multi-messenger programs.Comment: 10 pages, 7 figures. Proceedings of the 14th Gravitational Wave Data Analysis Workshop (GWDAW-14) in Roma - January 26th-29th, 201

Short GRBs at the dawn of the gravitational wave era

We derive the luminosity function and redshift distribution of short Gamma Ray Bursts (SGRBs) using (i) all the available observer-frame constraints (i.e. peak flux, fluence, peak energy and duration distributions) of the large population of Fermi SGRBs and (ii) the rest-frame properties of a complete sample of Swift SGRBs. We show that a steep $\phi(L)\propto L^{-a}$ with a>2.0 is excluded if the full set of constraints is considered. We implement a Monte Carlo Markov Chain method to derive the $\phi(L)$ and $\psi(z)$ functions assuming intrinsic Ep-Liso and Ep-Eiso correlations or independent distributions of intrinsic peak energy, luminosity and duration. To make our results independent from assumptions on the progenitor (NS-NS binary mergers or other channels) and from uncertainties on the star formation history, we assume a parametric form for the redshift distribution of SGRBs. We find that a relatively flat luminosity function with slope ~0.5 below a characteristic break luminosity ~3$\times10^{52}$ erg/s and a redshift distribution of SGRBs peaking at z~1.5-2 satisfy all our constraints. These results hold also if no Ep-Liso and Ep-Eiso correlations are assumed. We estimate that, within ~200 Mpc (i.e. the design aLIGO range for the detection of GW produced by NS-NS merger events), 0.007-0.03 SGRBs yr$^{-1}$ should be detectable as gamma-ray events. Assuming current estimates of NS-NS merger rates and that all NS-NS mergers lead to a SGRB event, we derive a conservative estimate of the average opening angle of SGRBs: $\theta_{jet}$~3-6 deg. Our luminosity function implies an average luminosity L~1.5$\times 10^{52}$ erg/s, nearly two orders of magnitude higher than previous findings, which greatly enhances the chance of observing SGRB "orphan" afterglows. Efforts should go in the direction of finding and identifying such orphan afterglows as counterparts of GW events.Comment: 13 pages, 5 figures, 2 tables. Accepted for publication in Astronomy & Astrophysics. Figure 5 and angle ranges corrected in revised versio