10 citations · 10 across the 2 of their papers we have counts for
6 papers
Learning dynamic quantum circuits for efficient state preparation
Faisal Alam, Bryan K. Clark
Dynamic quantum circuits (DQCs) incorporate mid-circuit measurements and gates conditioned on these measurement outcomes. DQCs can prepare certain long-range entangled states in co…
Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning
Abid Khan, Prateek Vaish, Yaoqi Pang +8
The ability to perform ab initio molecular dynamics simulations using potential energies calculated on quantum computers would allow virtually exact dynamics for chemical and bioch…
Classical Post-processing for Unitary Block Optimization Scheme to Reduce the Effect of Noise on Optimization of Variational Quantum Eigensolvers
Xiaochuan Ding, Bryan K. Clark
Variational Quantum Eigensolvers (VQE) are a promising approach for finding the classically intractable ground state of a Hamiltonian. The Unitary Block Optimization Scheme (UBOS)…
Constant-depth preparation of matrix product states with adaptive quantum circuits
Kevin C. Smith, Abid Khan, Bryan K. Clark +2
Adaptive quantum circuits, which combine local unitary gates, midcircuit measurements, and feedforward operations, have recently emerged as a promising avenue for efficient state p…
Pre-optimizing variational quantum eigensolvers with tensor networks
Abid Khan, Bryan K. Clark, Norm M. Tubman
The variational quantum eigensolver (VQE) is a promising algorithm for demonstrating quantum advantage in the noisy intermediate-scale quantum (NISQ) era. However, optimizing VQE f…
Simulating Neutral Atom Quantum Systems with Tensor Network States
James Allen, Matthew Otten, Stephen Gray +1
In this paper, we describe a tensor network simulation of a neutral atom quantum system under the presence of noise, while introducing a new purity-preserving truncation technique…