202 citations · 1.1k across the 29 of their papers we have counts for
29 papers
Millisecond-Scale Neural Operator Surrogates for Double-Null Free-Boundary Grad-Shafranov Equilibria
Plamen G. Krastev
The Grad-Shafranov (GS) equation governs ideal magnetohydrodynamic equilibrium in tokamak plasmas. Free-boundary GS solvers are central to diverted-equilibrium modeling, but nonlin…
A Deep Learning Approach to Extracting Nuclear Matter Properties from Neutron Star Observations
Plamen G. Krastev
Understanding the equation of state of dense QCD matter remains a major challenge in both nuclear physics and astrophysics. Neutron star observations from electromagnetic and gravi…
Deep Learning Detection and Classification of Gravitational Waves from Neutron Star-Black Hole Mergers
Richard Qiu, Plamen Krastev, Kiranjyot Gill +1
The Laser Interferometer Gravitational-Wave Observatory (LIGO) and Virgo Interferometer Collaborations have now detected all three classes of compact binary mergers: binary black h…
Translating neutron star observations to nuclear symmetry energy via artificial neural networks
Plamen G. Krastev
One of the most significant challenges involved in efforts to understand the equation of state of dense neutron-rich matter is the uncertain density dependence of the nuclear symme…
Detection and Parameter Estimation of Gravitational Waves from Binary Neutron-Star Mergers in Real LIGO Data using Deep Learning
Plamen G. Krastev, Kiranjyot Gill, V. Ashley Villar +1
One of the key challenges of real-time detection and parameter estimation of gravitational waves from compact binary mergers is the computational cost of conventional matched-filte…
Real-Time Detection of Gravitational Waves from Binary Neutron Stars using Artificial Neural Networks
Plamen G. Krastev
The groundbreaking discoveries of gravitational waves from binary black-hole mergers and, most recently, coalescing neutron stars started a new era of Multi-Messenger Astrophysics…