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20182021
most citedQuantum approximate algorithm for NP optimization problems with constraints

10 citations · 15 across the 2 of their papers we have counts for

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7 papers · 1 filter

quant-ph2021

Quantum walk-based vehicle routing optimisation

Tavis Bennett, Edric Matwiejew, Sam Marsh +1

This paper demonstrates the applicability of the Quantum Walk-based Optimisation Algorithm(QWOA) to the Capacitated Vehicle Routing Problem (CVRP). Efficient algorithms are develop…

quant-ph20215 cited

A framework for optimal quantum spatial search using alternating phase-walks

S. Marsh, J. B. Wang

We present a novel methodological framework for quantum spatial search, generalising the Childs & Goldstone () algorithm via alternating applications of marked-vertex…

quant-ph2021

Deterministic spatial search using alternating quantum walks

S. Marsh, J. B. Wang

This paper examines the performance of spatial search where the Grover diffusion operator is replaced by continuous-time quantum walks on a class of interdependent networks. We pro…

quant-ph2020

Quantum walk-based portfolio optimisation

N. Slate, E. Matwiejew, S. Marsh +1

This paper proposes a highly efficient quantum algorithm for portfolio optimisation targeted at near-term noisy intermediate-scale quantum computers. Recent work by Hodson et al. (…

quant-ph202010 cited

Quantum approximate algorithm for NP optimization problems with constraints

Yue Ruan, Samuel Marsh, Xilin Xue +3

The Quantum Approximate Optimization Algorithm (QAOA) is an algorithmic framework for finding approximate solutions to combinatorial optimization problems, derived from an approxim…

quant-ph2019

Combinatorial optimisation via highly efficient quantum walks

Samuel Marsh, Jingbo Wang

We present a highly efficient quantum circuit for performing continuous time quantum walks (CTQWs) over an exponentially large set of combinatorial objects, provided that the objec…