468 citations · 1k across the 30 of their papers we have counts for
30 papers
Quantum-inspired nonlinear Galerkin ansatz for high-dimensional HJB equations
Chuhao Sun, Asaf Cohen, James Stokes +1
Neural networks are increasingly recognized as a powerful numerical solution technique for partial differential equations (PDEs) arising in diverse scientific computing domains, in…
Digital quantum simulation of Schrödinger dynamics using adaptive approximations of potential functions
Tenzan Araki, James Stokes, Shravan Veerapaneni
Digital quantum simulation (DQS) of continuous-variable quantum systems in the position basis requires efficient implementation of diagonal unitaries approximating the time evoluti…
Gauge Equivariant Neural Networks for 2+1D U(1) Gauge Theory Simulations in Hamiltonian Formulation
Di Luo, Shunyue Yuan, James Stokes +1
Gauge Theory plays a crucial role in many areas in science, including high energy physics, condensed matter physics and quantum information science. In quantum simulations of latti…
Toward Neural Network Simulation of Variational Quantum Algorithms
Oliver Knitter, James Stokes, Shravan Veerapaneni
Variational quantum algorithms (VQAs) utilize a hybrid quantum-classical architecture to recast problems of high-dimensional linear algebra as ones of stochastic optimization. Desp…
Scalable neural quantum states architecture for quantum chemistry
Tianchen Zhao, James Stokes, Shravan Veerapaneni
Variational optimization of neural-network representations of quantum states has been successfully applied to solve interacting fermionic problems. Despite rapid developments, sign…
Quantum-inspired variational algorithms for partial differential equations: Application to financial derivative pricing
Tianchen Zhao, Chuhao Sun, Asaf Cohen +2
Variational quantum Monte Carlo (VMC) combined with neural-network quantum states offers a novel angle of attack on the curse-of-dimensionality encountered in a particular class of…