Related papers: Adaptive clustering procedure for continuous gravi…
The two interferometric LIGO gravitational-wave observatories provide the most sensitive data to date to study the gravitational-wave Universe. As part of a global network, they have just completed their third observing run in which they…
Pulsar Timing Arrays search for nanohertz-frequency gravitational waves by regularly observing ensembles of millisecond pulsars over many years to look for correlated timing residuals. Recently the first evidence for a stochastic…
Searches for gravitational wave bursts that are triggered by the observation of astronomical events require a different mode of analysis than all-sky, blind searches. For one, much more prior information is usually available in a triggered…
The gravitational wave sky is starting to become very crowded, with the fourth science run (O4) at LIGO expected to detect $\mathcal{O}(100)$ compact object coalescence signals. Data analysis issues start to arise as we look further…
Coherent wide parameter-space searches for continuous gravitational waves are typically limited in sensitivity by their prohibitive computing cost. Therefore semi-coherent methods (such as StackSlide) can often achieve a better sensitivity.…
We present results from searches of recent LIGO and Virgo data for continuous gravitational wave signals (CW) from spinning neutron stars and for a stochastic gravitational wave background (SGWB). The first part of the talk is devoted to CW…
Searches for gravitational waves from compact binary coalescences employ a process called matched filtering, in which gravitational wave strain data is cross-correlated against a bank of waveform templates. Data from every observing run of…
We study the effect of spins on searches for gravitational waves from compact binary coalescences in realistic simulated early advanced LIGO data. We construct a detection pipeline including matched filtering, signal-based vetoes, a…
The first successful detection of gravitational waves by ground-based observatories, such as the Laser Interferometer Gravitational-Wave Observatory (LIGO), marked a breakthrough in our comprehension of the Universe. However, due to the…
Recent gravitational-wave transient catalogs have used \pastro{}, the probability that a gravitational-wave candidate is astrophysical, to select interesting candidates for further analysis. Unlike false alarm rates, which exclusively…
We introduce a fully-coherent method for searching for gravitational wave signals generated by the merger of black hole and/or neutron star binaries. This extends the coherent analysis previously developed and used for targeted…
In this work, we apply Convolutional Neural Networks (CNNs) to detect gravitational wave (GW) signals of compact binary coalescences, using single-interferometer data from LIGO detectors. As novel contribution, we adopted a resampling…
The detection of gravitational waves is considered to be one of the most magnificent discoveries of the century. Due to the high computational cost of matched filtering pipeline, there is a hunt for an alternative powerful system. I…
Non-Gaussian noise transients in interferometric gravitational-wave detectors increase the background in searches for short-duration and un-modelled signals. We describe a method for vetoing noise transients by ranking the statistical…
The pulsar timing array community has recently reported the first evidence of a low-frequency stochastic gravitational wave background. With longer observational timespans we expect to be able to resolve individual gravitational wave…
There are at present ${\cal O}(100)$ gravitational-wave candidates from compact binary mergers reported in the astronomical literature. As detector sensitivities are improved, the catalog will swell in size: first to ${\cal O}(1000)$ events…
Gravitational wave detection requires an in-depth understanding of the physical properties of gravitational wave signals, and the noise from which they are extracted. Understanding the statistical properties of noise is a complex endeavor,…
In consensus clustering, a clustering algorithm is used in combination with a subsampling procedure to detect stable clusters. Previous studies on both simulated and real data suggest that consensus clustering outperforms native algorithms.…
The detection and characterization of post-merger gravitational wave signals from binary neutron star mergers remains challenging with current ground-based detectors. We present a convolutional neural network framework designed for…
We present a novel gravitational wave detection algorithm that conducts a matched filter search stochastically across the compact binary parameter space rather than relying on a fixed bank of template waveforms. This technique is…