6 research outputs found
Search method for long-duration gravitational-wave transients from neutron stars
We introduce a search method for a new class of gravitational-wave signals,
namely long-duration O(hours - weeks) transients from spinning neutron stars.
We discuss the astrophysical motivation from glitch relaxation models and we
derive a rough estimate for the maximal expected signal strength based on the
superfluid excess rotational energy. The transient signal model considered here
extends the traditional class of infinite-duration continuous-wave signals by a
finite start-time and duration. We derive a multi-detector Bayes factor for
these signals in Gaussian noise using \F-statistic amplitude priors, which
simplifies the detection statistic and allows for an efficient implementation.
We consider both a fully coherent statistic, which is computationally limited
to directed searches for known pulsars, and a cheaper semi-coherent variant,
suitable for wide parameter-space searches for transients from unknown neutron
stars. We have tested our method by Monte-Carlo simulation, and we find that it
outperforms orthodox maximum-likelihood approaches both in sensitivity and in
parameter-estimation quality.Comment: 20 pages, 9 figures; submitted to PR
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 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.
A Mock Data Challenge for the Einstein Gravitational-Wave Telescope
Einstein Telescope (ET) is conceived to be a third generation
gravitational-wave observatory. Its amplitude sensitivity would be a factor ten
better than advanced LIGO and Virgo and it could also extend the low-frequency
sensitivity down to 1--3 Hz, compared to the 10--20 Hz of advanced detectors.
Such an observatory will have the potential to observe a variety of different
GW sources, including compact binary systems at cosmological distances. ET's
expected reach for binary neutron star (BNS) coalescences is out to redshift
and the rate of detectable BNS coalescences could be as high as one
every few tens or hundreds of seconds, each lasting up to several days. %in the
sensitive frequency band of ET. With such a signal-rich environment, a key
question in data analysis is whether overlapping signals can be discriminated.
In this paper we simulate the GW signals from a cosmological population of BNS
and ask the following questions: Does this population create a confusion
background that limits ET's ability to detect foreground sources? How efficient
are current algorithms in discriminating overlapping BNS signals? Is it
possible to discern the presence of a population of signals in the data by
cross-correlating data from different detectors in the ET observatory? We find
that algorithms currently used to analyze LIGO and Virgo data are already
powerful enough to detect the sources expected in ET, but new algorithms are
required to fully exploit ET data.Comment: accepted for publication in Physical Review D -- 18 pages, 8 figure
Long gravitational-wave transients and associated detection strategies for a network of terrestrial interferometers
Searches for gravitational waves (GWs) traditionally focus on persistent sources (e.g., pulsars or the stochastic background) or on transients sources (e.g., compact binary inspirals or core-collapse supernovae), which last for time scales of milliseconds to seconds. We explore the possibility of long GW transients with unknown waveforms lasting from many seconds to weeks. We propose a novel analysis technique to bridge the gap between short O(s) “burst” analyses and persistent stochastic analyses. Our technique utilizes frequency-time maps of GW strain cross power between two spatially separated terrestrial GW detectors. The application of our cross power statistic to searches for GW transients is framed as a pattern recognition problem, and we discuss several pattern-recognition techniques. We demonstrate these techniques by recovering simulated GW signals in simulated detector noise. We also recover environmental noise artifacts, thereby demonstrating a novel technique for the identification of such artifacts in GW interferometers. We compare the efficiency of this framework to other techniques such as matched filtering