Related papers: Modeling the Time Evolution of Compact Binary Syst…
We demonstrate a machine learning based approach which can learn the time-dependent electronic excitation dynamics of small molecules subjected to ion irradiation. Ensembles of recurrent neural networks are trained on data generated by…
The recurrent neural network and its variants have shown great success in processing sequences in recent years. However, this deep neural network has not aroused much attention in anomaly detection through predictively process monitoring.…
Pulsar timing arrays (PTAs) can detect the low-frequency stochastic gravitational-wave background (GWB) generated by an ensemble of supermassive black hole binaries (BHBs). Accurate determination of BHB merger timescales is essential for…
We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time series data. We preprocessed over 94 GB of Kepler light curves from MAST to classify according to ten distinct physical…
The availability of accurate numerical waveforms is an important requirement for the creation and calibration of reliable waveform models for gravitational wave astrophysics. For black hole-neutron star binaries, very few accurate waveforms…
A yet undetected class of GW signals is represented by the close encounters between compact objects in highly-eccentric e~1 orbits, that can occur in binary systems formed in dense environments such as globular clusters. The expected…
Most studies of mass transfer in binary systems assume circular orbits at the onset of Roche lobe overflow. However, there are theoretical and observational indications that mass transfer could occur in eccentric orbits. In particular,…
We have trained a fully convolutional spatio-temporal model for fast and accurate representation learning in the challenging exemplar application area of fusion energy plasma science. The onset of major disruptions is a critically important…
Gravitational waves (GWs) from binary neutron stars (BNSs) offer valuable understanding of the nature of compact objects and hadronic matter, and the science potential will be greatly enhanced by the third-generation (3G) GW detectors,…
With the fast development of various positioning techniques such as Global Position System (GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly available nowadays. Mining valuable knowledge from…
The recurrent neural network with the long short-term memory cell (LSTM-NN) is employed to simulate the long-time dynamics of open quantum system. The bootstrap method is applied in the LSTM-NN construction and prediction, which provides a…
The angular momentum (AM) content of massive stellar cores helps to determine the natal spin rates of neutron stars and black holes. Asteroseismic measurements of low-mass stars have proven that stellar cores rotate slower than predicted by…
Recent observations of compact binary systems have provided evidence for black holes with masses below standard expectations. When paired with neutron stars (NSs), such low-mass black holes (BHs) have the potential to be detected by future…
We report on recent results obtained in the post-Newtonian framework for the modelling of the gravitational waves emitted by binary systems of spinning compact objects (black holes and/or neutron stars). These new results are obtained at…
Gravitational-wave (GW) signals from coalescing compact binaries carry enormous information about the source dynamics and are an excellent tool to probe unknown astrophysics and fundamental physics. Though the updated catalog of compact…
Binary black hole (BBH) systems residing in the centers of galaxies evolve within complex astrophysical environments. These environments, comprising dark matter (DM) halos and baryonic accretion disks, can significantly alter the orbital…
We review the current status of attempts to numerically model the merger of neutron star-neutron star (NSNS) and black hole-neutron star (BHNS) binary systems, and we describe the understanding of such events that is emerging from these…
We present a novel machine learning framework tailored to detect massive black hole binaries observed by spaceborne gravitational wave detectors like the Laser Interferometer Space Antenna (LISA) and predict their future merger times. The…
Numerical relativity simulations of compact binaries with the Z4c and BSSNOK formulations are compared. The Z4c formulation is advantageous in every case considered. In simulations of non-vacuum spacetimes the constraint violations due to…
We present a fast method for obtaining fully analytical approximations for gravitational waveforms produced by merging of neutron stars and/or black holes for the earliest stages of the merger process. The obtained analytical formula is…