Related papers: Identifying extra high frequency gravitational wav…
A common theoretical approach to understanding neural networks is to take an infinite-width limit, at which point the outputs become Gaussian process (GP) distributed. This is known as a neural network Gaussian process (NNGP). However, the…
As performance of dedicated facilities continually improved, massive pulsar candidates are being received, which makes selecting valuable pulsar signals from candidates challenging. In this paper, we designed a deep convolutional neural…
Typical sources of gravitational wave bursts are supernovae, for which no accurate models exist. This calls for search methods with high efficiency and robustness to be used in the data analysis of foreseen interferometric detectors. A set…
The existing matched filtering method for gravitational wave (GW) search relies on a template bank. The computational efficiency of this method scales with the size of the templates within the bank. Higher-order modes and eccentricity will…
As a powerful tool for modeling complex relationships, hypergraphs are gaining popularity from the graph learning community. However, commonly used frameworks in deep hypergraph learning focus on hypergraphs with edge-independent vertex…
We consider the electromagnetic (EM) response of a Gaussian beam passing through a static magnetic field to be the high-frequency gravitational waves (HFGW) as generated by several devices discussed at this conference. It is found that…
GPR full-waveform inversion optimizes the subsurface property model iteratively to match the entire waveform information. However, the model gradients derived from wavefield continuation often contain errors, such as ghost values and…
We propose a deep learning algorithm for seismic interface and pocket detection with neural networks trained by synthetic high-frequency displacement data efficiently generated by the frozen Gaussian approximation (FGA). In seismic imaging…
We propose GravNet (Global detector network to search for high-frequency gravitational waves), a novel experimental scheme enabling the search for gravitational waves in the MHz to GHz frequency range. Such high-frequency gravitational…
Atmospheric gravity waves occur in the Earths atmosphere caused by an interplay between gravity and buoyancy forces. These waves have profound impacts on various aspects of the atmosphere, including the patterns of precipitation, cloud…
In this paper, we report on the construction of a deep Artificial Neural Network (ANN) to localize simulated gravitational wave signals in the sky with high accuracy. We have modelled the sky as a sphere and have considered cases where the…
In decision-making systems, it is important to have classifiers that have calibrated uncertainties, with an optimisation objective that can be used for automated model selection and training. Gaussian processes (GPs) provide uncertainty…
Gravitational waves carry unique information about high-energy astrophysical events such as the inspiral and merger of neutron stars and black holes, core collapse in massive stars, and other sources. Large gravitational wave (GW) detectors…
Based on the DUSTGRAIN-pathfinder suite of simulations, we investigate observational degeneracies between nine models of modified gravity and massive neutrinos. Three types of machine learning techniques are tested for their ability to…
We present a new method to search for long transient gravitational waves signals, like those expected from fast spinning newborn magnetars, in interferometric detector data. Standard search techniques are computationally unfeasible (matched…
Studies have shown that the use of pulsar timing arrays (PTAs) is among the approaches with the highest potential to detect very low-frequency gravitational waves in the near future. Although the capture of gravitational waves (GWs) by PTAs…
Detections of gravitational waves (GW) in the frequency band 35 Hz to 500 Hz have led to the birth of GW astronomy. Expected signals above 500 Hz, such as the quasinormal modes of lower mass black holes and neutron star mergers signatures…
Recent work has shown that modified gravitational wave (GW) propagation can be a powerful probe of dark energy and modified gravity, specific to GW observations. We use the technique of Gaussian processes, that allows the reconstruction of…
There exist corresponding metric perturbations of the relic gravitational waves (GWs) in the region of approximately h~10^(-30)-10^(-32)in the GHz band. A detector for these GWs is described in which we measure the perturbative photon flux…
For image classification problems, various neural network models are commonly used due to their success in yielding high accuracies. Convolutional Neural Network (CNN) is one of the most frequently used deep learning methods for image…