Related papers: Testing the LIGO Inspiral Analysis with Hardware I…
Profile-Guided Optimization (PGO) is an excellent means to improve the performance of a compiled program. Indeed, the execution path data it provides helps the compiler to generate better code and better cacheline packing. At the time of…
The nature of black holes is one of most exciting issues in gravitational physics. If there is an exotic compact object as the compact as a black hole but without a horizon, gravitational wave echoes may be produced after the merger. In…
Parameter estimation of gravitational wave data is often computationally expensive, requiring simplifying assumptions such as circularisation of binary orbits. Although, if included, the sub-dominant effects like orbital eccentricity may…
The contribution gives an overview of the LCFIVertex package, providing software tools for high-level event reconstruction at the International Linear Collider using vertex-detector information. The package was validated using a fast Monte…
Modern chip designs are increasingly complex, making it difficult for developers to glean meaningful insights about hardware behavior while real workloads are running. Hardware introspection aims to solve this by enabling the hardware…
We study whether binary black hole template banks can be used to search for the gravitational waves emitted by general binary coalescences. To recover binary signals from noisy data, matched-filtering techniques are typically required. This…
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…
Gravitational-wave observatories like LIGO are large-scale, terrestrial instruments housed in infrastructure that spans a multi-kilometer geographic area and which must be actively controlled to maintain operational stability for long…
One of the types of signals for which the LIGO interferometric gravitational wave detectors will search is a stochastic background of gravitational radiation. We review the technique of searching for a background using the…
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…
High-frequency inductive power transfer (IPT) has garnered significant attention in recent years due to its long transmission distance and high efficiency. The inductance values L and quality factors Q of the transmitting and receiving…
We compare two multi-detector detection strategies, namely, the coincidence and the coherent, for the detection of spinless inspiraling compact binary gravitational wave signals. The coincident strategy treats the detectors as if they are…
Advancements in gravitational-wave interferometers, particularly the next generation, are poised to profoundly impact gravitational wave astronomy and multimessenger astrophysics. A hybrid quantum algorithm is proposed to carry out quantum…
Recent advances in the description of compact binary systems have produced gravitational waveforms that include inspiral, merger and ring-down phases. Comparing results from numerical simulations with those of post-Newtonian (PN), and…
A network of three or more gravitational wave detectors simultaneously taking data is required to generate a well-localized sky map for gravitational wave sources, such as GW170817. Local seismic disturbances often cause the LIGO and Virgo…
After their successful first observing run (September 12, 2015 - January 12, 2016), the Advanced LIGO detectors were upgraded to increase their sensitivity for the second observing run (November 30, 2016 - August 26, 2017). The Advanced…
A screening experiment attempts to identify a subset of important effects using a relatively small number of experimental runs. Given the limited run size and a large number of possible effects, penalized regression is a popular tool used…
Machine Learning (ML) is increasingly used to automate impactful decisions, which leads to concerns regarding their correctness, reliability, and fairness. We envision highly-automated software platforms to assist data scientists with…
The probability that interferometric detectors such as LIGO and VIRGO will successfully detect inspiraling compact binaries depends in part on our knowledge of the expected gravitational wave forms. The best approximations to the true wave…
The sensitivity of gravitational wave searches for binary black holes is estimated via the injection and posterior recovery of simulated gravitational wave signals in the detector data streams. When a search reports no detections, the…