Quantum walks with memory - goldfish, elephants and wise old men

TL;DR

This paper introduces a discrete-time quantum walk model with memory, revealing how memory influences speed, entanglement, and localization, with implications for quantum information processing and potential classical simulation.

Contribution

The study presents a novel quantum walk model with memory using recycled coins and a history-dependent coin flip, analyzing its effects on speed, entanglement, and localization.

Findings

Memory enhances quantum ballistic speed-up in 1D walks.

Memory destroys spatial entanglement in 2D walks.

Multi-coined walks with memory avoid localization and can accelerate diffusion.

Abstract

Quantum walks have emerged as an interesting approach to quantum information processing, exhibiting many unique properties compared to the analogous classical random walk. Here we introduce a model for a discrete-time quantum walk with memory by endowing the walker with multiple recycled coins and using a physical memory function via a history dependent coin flip. By numerical simulation we observe several phenomena. First in one dimension, walkers with memory have persistent quantum ballistic speed up over classical walks just as found in previous studies of multi-coined walks with trivial memory function. However, measurement of the multi-coin state can dramatically shift the mean of the spatial distribution. Second, we consider spatial entanglement in a two-dimensional quantum walk with memory and find that memory destroys entanglement between the spatial dimensions, even when entangling coins are employed. Finally, we explore behaviour in the presence of spatial randomness and find that in contrast to single coined walks, multi-coined walks do not localise and in fact a memory function can speed up the walk relative to a fully decohered multi-coin walker with trivial memory. We explicitly show how to construct linear optics circuits implementing the walks, and discuss prospects for classical simulation.