A Semi-Parametric Approach to the Detection of Non-Gaussian Gravitational Wave Stochastic Backgrounds

Using a semi-parametric approach based on the fourth-order Edgeworth expansion for the unknown signal distribution, we derive an explicit expression for the likelihood detection statistic in the presence of non-normally distributed gravitational wave stochastic backgrounds. Numerical likelihood maximization exercises based on Monte-Carlo simulations for a set of large tail symmetric non-Gaussian distributions suggest that the fourth cumulant of the signal distribution can be estimated with reasonable precision when the ratio between the signal and the noise variances is larger than 0.01. The estimation of higher-order cumulants of the observed gravitational wave signal distribution is expected to provide additional constraints on astrophysical and cosmological models.Comment: 26 pages, 3 figures, to appear in Phys. Rev.

Measuring neutron-star ellipticity with measurements of the stochastic gravitational-wave background

Galactic neutron stars are a promising source of gravitational waves in the analysis band of detectors such as LIGO and Virgo. Previous searches for gravitational waves from neutron stars have focused on the detection of individual neutron stars, which are either nearby or highly non-spherical. Here we consider the stochastic gravitational-wave signal arising from the ensemble of Galactic neutron stars. Using a population synthesis model, we estimate the single-sigma sensitivity of current and planned gravitational-wave observatories to average neutron star ellipticity $\epsilon$ as a function of the number of in-band Galactic neutron stars $N_\text{tot}$. For the plausible case of $N_\text{tot}\approx 53000$, and assuming one year of observation time with colocated initial LIGO detectors, we find it to be $\sigma_\epsilon=2.1\times10^{-7}$, which is comparable to current bounds on some nearby neutron stars. (The current best $95\%$ upper limits are $\epsilon\lesssim7\times10^{-8}.$) It is unclear if Advanced LIGO can significantly improve on this sensitivity using spatially separated detectors. For the proposed Einstein Telescope, we estimate that $\sigma\epsilon=5.6\times10^{-10}$. Finally, we show that stochastic measurements can be combined with measurements of individual neutron stars in order to estimate the number of in-band Galactic neutron stars. In this way, measurements of stochastic gravitational waves provide a complementary tool for studying Galactic neutron stars

Parameter Estimation in Searches for the Stochastic Gravitational-Wave Background

The stochastic gravitational-wave background (SGWB) is expected to arise from the superposition of many independent and unresolved gravitational-wave signals of either cosmological or astrophysical origin. The spectral content of the SGWB carries signatures of the physics that generated it. We present a Bayesian framework for estimating the parameters associated with different SGWB models using data from gravitational-wave detectors. We apply this technique to recent results from LIGO to produce the first simultaneous 95% confidence level limits on multiple parameters in generic power-law SGWB models and in SGWB models of compact binary coalescences. We also estimate the sensitivity of the upcoming second-generation detectors such as Advanced LIGO/Virgo to these models and demonstrate how SGWB measurements can be combined and compared with observations of individual compact binary coalescences in order to build confidence in the origin of an observed SGWB signal. In doing so, we demonstrate a novel means of differentiating between different sources of the SGWB.Comment: 6 pages, 5 figure

The stochastic background from cosmic (super)strings: popcorn and (Gaussian) continuous regimes

In the era of the next generation of gravitational wave experiments a stochastic background from cusps of cosmic (super)strings is expected to be probed and, if not detected, to be significantly constrained. A popcorn-like background can be, for part of the parameter space, as pronounced as the (Gaussian) continuous contribution from unresolved sources that overlap in frequency and time. We study both contributions from unresolved cosmic string cusps over a range of frequencies relevant to ground based interferometers, such as LIGO/Virgo second generation (AdLV) and Einstein Telescope (ET) third generation detectors, the space antenna LISA and Pulsar Timing Arrays (PTA). We compute the sensitivity (at $2 \sigma$ level) in the parameter space for AdLV, ET, LISA and PTA. We conclude that the popcorn regime is complementary to the continuous background. Its detection could therefore enhance confidence in a stochastic background detection and possibly help determine fundamental string parameters such as the string tension and the reconnection probability.Comment: 21 pages, 11 figures ; revised version after correction of a typo in eq. 4.

Detection regimes of the cosmological gravitational wave background from astrophysical sources

Key targets for gravitational wave (GW) observatories, such as LIGO and the next generation interferometric detector, Advanced LIGO, include core-collapse of massive stars and the final stage of coalescence of compact stellar remnants. The combined GW signal from such events occurring throughout the Universe will produce an astrophysical GW background (AGB), one that is fundamentally different from the GW background by very early Universe processes. One can classify contributions to the AGB for different classes of sources based on the strength of the GW emissions from the individual sources, their peak emission frequency, emission duration and their event rate density distribution. This article provides an overview of the detectability regimes of the AGB in the context of current and planned gravitational wave observatories. We show that there are two important AGB signal detection regimes, which we define as `continuous' and `popcorn noise'. We describe how the `popcorn noise' AGB regime evolves with observation time and we discuss how this feature distinguishes it from the GW background produced from very early Universe processes.Comment: accepted for publication in New Astronomy Reviews; 23 pages and 2 figure

LISACode : A scientific simulator of LISA

A new LISA simulator (LISACode) is presented. Its ambition is to achieve a new degree of sophistication allowing to map, as closely as possible, the impact of the different sub-systems on the measurements. LISACode is not a detailed simulator at the engineering level but rather a tool whose purpose is to bridge the gap between the basic principles of LISA and a future, sophisticated end-to-end simulator. This is achieved by introducing, in a realistic manner, most of the ingredients that will influence LISA's sensitivity as well as the application of TDI combinations. Many user-defined parameters allow the code to study different configurations of LISA thus helping to finalize the definition of the detector. Another important use of LISACode is in generating time series for data analysis developments

Targeted search for the stochastic gravitational-wave background from the galactic millisecond pulsar population

The millisecond pulsars, old-recycled objects spinning with high frequency $\mathcal{O}$(kHz) sustaining the deformation from their spherical shape, may emit gravitational-waves (GW). These are one of the potential candidates contributing to the anisotropic stochastic gravitational-wave background (SGWB) observable in the ground-based GW detectors. Here, we present the results from a likelihood-based targeted search for the SGWB due to millisecond pulsars in the Milky Way, by analyzing the data from the first three observing runs of Advanced LIGO and Advanced Virgo detector. We assume that the shape of SGWB power spectra and the sky distribution is known a priori from the population synthesis model. The information of the ensemble source properties, i.e., the in-band number of pulsars, $N_{obs}$ and the averaged ellipticity, $\mu_\epsilon$ is encoded in the maximum likelihood statistic. We do not find significant evidence for the SGWB signal from the considered source population. The best Bayesian upper limit with $95\%$ confidence for the parameters are $N_{obs}\leq8.8\times10^{4}$ and $\mu_\epsilon\leq1.1\times10^{-7}$, which is comparable to the bounds on mean ellipticity with the GW observations of the individual pulsars. Finally, we show that for the plausible case of $N_{obs}=40,000$, with the one year of observations, the one-sigma sensitivity on $\mu_\epsilon$ might reach $10^{-8}$ and $2.7\times10^{-9}$ for the second-generation detector network having A+ sensitivity and third-generation detector network respectively.Comment: 13 pages, 3 figures, 1 tabl

Prospects for Stochastic Background Searches Using Virgo and LSC Interferometers

We consider the question of cross-correlation measurements using Virgo and the LSC Interferometers (LIGO Livingston, LIGO Hanford, and GEO600) to search for a stochastic gravitational-wave background. We find that inclusion of Virgo into the network will substantially improve the sensitivity to correlations above 200 Hz if all detectors are operating at their design sensitivity. This is illustrated using a simulated isotropic stochastic background signal, generated with an astrophysically-motivated spectrum, injected into 24 hours of simulated noise for the LIGO and Virgo interferometers.Comment: 11 pages, uses IOP style files, submitted to CQG for GWDAW11 proceedings; revised in response to referee comment

Second Einstein Telescope mock data and science challenge: Low frequency binary neutron star data analysis

The Einstein Telescope is a conceived third generation gravitational-wave detector that is envisioned to be an order of magnitude more sensitive than advanced LIGO, Virgo and Kagra, which would be able to detect gravitational-wave signals from the coalescence of compact objects with waveforms starting as low as 1Hz. With this level of sensitivity, we expect to detect sources at cosmological distances. In this paper we introduce an improved method for the generation of mock data and analyse it with a new low latency compact binary search pipeline called gstlal. We present the results from this analysis with a focus on low frequency analysis of binary neutron stars. Despite compact binary coalescence signals lasting hours in the Einstein Telescope sensitivity band when starting at 5 Hz, we show that we are able to discern various overlapping signals from one another. We also determine the detection efficiency for each of the analysis runs conducted and and show a proof of concept method for estimating the number signals as a function of redshift. Finally, we show that our ability to recover the signal parameters has improved by an order of magnitude when compared to the results of the first mock data and science challenge. For binary neutron stars we are able to recover the total mass and chirp mass to within 0.5% and 0.05%, respectively