output
20032025
most citedGW170817: Observation of Gravitational Waves from a Binary Neutron Star Inspiral

9.8k citations

Showing gr-qcShow all

21 papers · 1 filter

gr-qc202315 cited

A stochastic search for intermittent gravitational-wave backgrounds

Jessica Lawrence, Kevin Turbang, Andrew Matas +3

A likely source of a gravitational-wave background (GWB) in the frequency band of the Advanced LIGO, Virgo and KAGRA detectors is the superposition of signals from the population o…

gr-qc202218 cited

Targeted search for the kinematic dipole of the gravitational-wave background

Adrian Ka-Wai Chung, Alexander C. Jenkins, Joseph D. Romano +1

There is growing interest in using current and future gravitational-wave interferometers to search for anisotropies in the gravitational-wave background. One guaranteed anisotropic…

gr-qc2022

Constraints on r-modes and mountains on millisecond neutron stars in binary systems

P. B. Covas, M. A. Papa, R. Prix +1

Continuous gravitational waves are nearly monochromatic signals emitted by asymmetries in rotating neutron stars. These signals have not yet been detected. Deep all-sky searches fo…

gr-qc202169 cited

All-sky Search for Continuous Gravitational Waves from Isolated Neutron Stars in the Early O3 LIGO Data

The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration +1587

We report on an all-sky search for continuous gravitational waves in the frequency band 20-2000\,Hz and with a frequency time derivative in the range of

gr-qc202047 cited

Common-spectrum process versus cross-correlation for gravitational-wave searches using pulsar timing arrays

Joseph D. Romano, Jeffrey S. Hazboun, Xavier Siemens +1

The North American Nanohertz Observatory for Gravitational Waves (NANOGrav) has recently reported strong statistical evidence for a common-spectrum red-noise process for all pulsar…

gr-qc202020 cited

Frequentist versus Bayesian analyses: Cross-correlation as an (approximate) sufficient statistic for LIGO-Virgo stochastic background searches

Andrew Matas, Joseph D. Romano

Sufficient statistics are combinations of data in terms of which the likelihood function can be rewritten without loss of information. Depending on the data volume reduction, the u…