6 papers
RELift: Learned Coarse-to-Fine Propagators for Time-Dependent PDEs with Applications to Electron Dynamics
Hardeep Bassi, Yuanran Zhu, Erika Ye +5
We present RELift (Restrict, Evolve, Lift), a two-phase learning framework that couples coarse-grid numerical solvers with neural operators to super-resolve and forecast fine-grid…
From noisy observables to accurate ground state energies: a quantum classical signal subspace approach with denoising
Hardeep Bassi, Yizhi Shen, Harish S. Bhat +1
We propose a hybrid quantum-classical algorithm for ground state energy (GSE) estimation that remains robust to highly noisy data and exhibits low sensitivity to hyperparameter tun…
Second-Order Adjoint Method for Quantum Optimal Control
Harish S. Bhat
We derive and implement a second-order adjoint method to compute exact gradients and Hessians for a prototypical quantum optimal control problem, that of solving for the minimal en…
Nonlinear Optimal Control of Electron Dynamics within Hartree-Fock Theory
Harish S. Bhat, Hardeep Bassi, Christine M. Isborn
Consider the problem of determining the optimal applied electric field to drive a molecule from an initial state to a desired target state. For even moderately sized molecules, sol…
Scalable learning of potentials to predict time-dependent Hartree-Fock dynamics
Harish S. Bhat, Prachi Gupta, Christine M. Isborn
We propose a framework to learn the time-dependent Hartree-Fock (TDHF) inter-electronic potential of a molecule from its electron density dynamics. Though the entire TDHF Hamiltoni…
Incorporating Memory into Propagation of 1-Electron Reduced Density Matrices
Harish S. Bhat, Hardeep Bassi, Karnamohit Ranka +1
For any linear system with unreduced dynamics governed by invertible propagators, we derive a closed, time-delayed, linear system for a reduced-dimensional quantity of interest. Th…