High robustness quantum walk search algorithm with qudit Householder\n traversing coin, machine learning study

2021/11/21 by Hristo Tonchev, Tonchev, Hristo, Petar Danev +1
Computer Science · #Atomic Physics (physics.atom-ph) #FOS: Physical sciences #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Physics (quant-ph) #Quantum-Dot Cellular Automata

paper · pdf · doi:10.48550/arxiv.2111.10926

openalex publication_date 2021/11/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this work the quantum random walk search algorithm with walk coin\nconstructed by generalized Householder reflection and phase multiplier has been\nstudied. The coin register is one qudit with arbitrary dimension. Monte Carlo\nsimulations, in combination with supervised machine learning, are used to find\nwalk coins making the quantum algorithm more robust to deviations in the coin's\nparameters. By applying deep neural network we make prediction for the\nparameters of an optimal coin with arbitrary size and estimate the stability\nfor such coin.\n

Citations

• Search of clustered marked states with lackadaisical quantum walks
• Optimizing the walk coin in the quantum random walk search algorithm through machine learning

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