Related papers: Machine Learning based Glitch Veto for inspiral bi…
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,…
Strongly lensed gravitational waves (GWs) from binary coalescence manifest as repeated chirps from the original merger. At the detectors, the phase of the lensed GWs and its arrival time differences will be consistent modulo a fixed…
The number of astrophysical sources detected by Advanced LIGO and Virgo is expected to increase as the detectors approach their design sensitivity. Gravitational wave detectors are also sensitive to transient noise sources created by the…
The sensitivity of searches for astrophysical transients in data from the LIGO is generally limited by the presence of transient, non-Gaussian noise artifacts, which occur at a high-enough rate such that accidental coincidence across…
As the sensitivity of the international gravitational wave detector network increases, observing binary neutron star signals will become more common. Moreover, since these signals will be louder, the chances of detecting them before their…
We develop a Conformer neural network, called Conformer Binary neTwork Search, or CoBiTS, for distinguishing binary black hole (BBH) gravitational wave (GW) signals from non-Gaussian and non-stationary noise artifacts in the data from…
Using simple, intuitive arguments, we discuss the expected accuracy with which astrophysical parameters can be extracted from an observed gravitational wave signal. The observation of a chirp like signal in the data allows for measurement…
Gravitational-wave data from advanced-era interferometric detectors consists of background Gaussian noise, frequent transient artefacts, and rare astrophysical signals. Multiple search algorithms exist to detect the signals from compact…
Parameter estimation on gravitational wave signals from compact binary coalescence (CBC) requires the evaluation of computationally intensive waveform models, typically the bottleneck in the analysis. This cost will increase further as low…
Machine learning can be a powerful tool to discover new signal types in astronomical data. We here apply it to search for long-duration transient gravitational waves triggered by pulsar glitches, which could yield physical insight into the…
With the advanced LIGO and Virgo detectors taking observations the detection of gravitational waves is expected within the next few years. Extracting astrophysical information from gravitational wave detections is a well-posed problem and…
The recent completion of Advanced LIGO suggests that gravitational waves (GWs) may soon be directly observed. Past searches for gravitational-wave transients have been impacted by transient noise artifacts, known as glitches, introduced…
The detection rate for compact binary mergers has grown as the sensitivity of the global network of ground based gravitational wave detectors has improved, now reaching the stage where robust automation of the analyses is essential.…
Gravitational wave searches rely on a combination of methods, including matched filtering, coherent analyses, and more recent machine learning based pipelines. For compact binary coalescences, where signals originate from the relativistic…
We present an algorithm for the identification of transient noise artifacts (glitches) in cross-correlation searches for long O(10s) gravitational-wave transients. The algorithm utilizes the auto-power in each detector as a discriminator…
Overlapping signals represent one of the major data analysis challenges in next-generation gravitational wave detectors. We leverage Transformers and Normalizing Flows, state-of-the-art machine learning algorithms, to address the parameter…
We propose a new internal calibration process using chirp pulses. Our method is utilized to mitigate thermal drift, which is unwanted changes and usually occurs in active elements such as a high power amplifier and low noise amplifier. The…
The properties of the population of merging binary black holes encode some of the uncertain physics of the evolution of massive stars in binaries. The binary black hole merger rate and chirp mass distribution are being measured by…
Gravitational-wave observatories become more sensitive with each observing run, increasing the number of detected gravitational-wave signals. A limiting factor in identifying these signals is the presence of transient non-Gaussian noise,…
Instrumental artefacts, such as glitches, can significantly compromise the scientific output of LISA. Our methodology employs advanced Bayesian techniques, including Reversible Jump Markov Chain Monte Carlo and parallel tempering to find…