activity
20002022
most citedImproved Techniques for Preparing Eigenstates of Fermionic Hamiltonians

142 citations · 789 across the 22 of their papers we have counts for

collaborators

22 papers

quant-ph2022

Non-convex Quadratic Programming Using Coherent Optical Networks

Farhad Khosravi, Ugur Yildiz, Artur Scherer +1

We investigate the possibility of solving continuous non-convex optimization problems using a network of interacting quantum optical oscillators. We propose a native encoding of co…

quant-ph2021★ 6 cited

Mixed-Integer Programming Using a Bosonic Quantum Computer

Farhad Khosravi, Artur Scherer, Pooya Ronagh

We propose a scheme for solving mixed-integer programming problems in which the optimization problem is translated to a ground-state preparation problem on a set of bosonic quantum…

quant-ph2021

Reflection-Based Adiabatic State Preparation

Jessica Lemieux, Artur Scherer, Pooya Ronagh

We propose a circuit-model quantum algorithm for eigenpath traversal that is based on a combination of concepts from Grover's search and adiabatic quantum computation. Our algorith…

quant-ph2021★ 13 cited

A Benchmarking Study of Quantum Algorithms for Combinatorial Optimization

Krishanu Sankar, Artur Scherer, Satoshi Kako +8

We study the performance scaling of three quantum algorithms for combinatorial optimization: measurement-feedback coherent Ising machines (MFB-CIM), discrete adiabatic quantum comp…

quant-ph2018★ 109 cited

Black-box quantum state preparation without arithmetic

Yuval R. Sanders, Guang Hao Low, Artur Scherer +1

Black-box quantum state preparation is an important subroutine in many quantum algorithms. The standard approach requires the quantum computer to do arithmetic, which is a key cont…

quant-ph2018★ 65 cited

Simulating the dynamics of time-dependent Hamiltonians with a truncated Dyson series

Maria Kieferova, Artur Scherer, Dominic Berry

We provide a general method for efficiently simulating time-dependent Hamiltonian dynamics on a circuit-model based quantum computer. Our approach is based on approximating the tru…