Abstract

Non-Markovianity may significantly speed up quantum dynamics when the system interacts strongly with an infinite large reservoir, of which the coupling spectrum should be fine-tuned. The potential benefits are evident in many dynamics schemes, especially the continuous-time quantum walk. Difficulty exists, however, in producing closed-form solutions with controllable accuracy against the complexity of memory kernels. Here, we introduce a new multiple-scale perturbation method that works on integro-differential equations for general study of memory effects in dynamical systems. We propose an open-system model in which a continuous-time quantum walk is enclosed in a non-Markovian reservoir, that naturally corresponds to an error correction algorithm scheme. By applying the multiple-scale method we show how emergence of different time scales is related to transition of system dynamics into the non-Markovian regime. We find that up to two long-term modes and two short-term modes exist in regular networks, limited by their intrinsic symmetries. In addition to the effective approximation by our perturbation method on general forms of reservoirs, the speed-up of quantum walks assisted by non-Markovianity is also confirmed, revealing the advantage of reservoir engineering in designing time-sensitive quantum algorithms.

Highlights

  • Many mathematical techniques have been developed to identify intrinsic timescales in dynamical systems

  • We present a multiple-scale perturbation method that works on integro-differential equations in the form of Eq (1), which can be used to unravel the functional importance hidden in the memory kernel and its related complex dynamics

  • We study its application to a continuous-time quantum walk on some network G enclosed by a general nonMarkovian reservoir E

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Summary

INTRODUCTION

Many mathematical techniques have been developed to identify intrinsic timescales in dynamical systems. We further apply the perturbation method to a continuous-time quantum walk enclosed in a non-Markovian reservoir Such a model naturally follows an error correction algorithm scheme, with the reservoir a collection of independent “error” sites. Remaining questions in this crossover study of nonMarkovian memory effect and continuous-time quantum walks include the possibility that there are more than two independently important timescales in the non-Markovian model. We could apply our method to quantum walks on complex networks [39] where the statistics of disorder could take unpredictable new forms

MULTIPLE-SCALE INTEGRO-DIFFERENTIAL PERTURBATION METHOD
CONTINUOUS-TIME QUANTUM WALKS
Quantum walk in a reservoir
Perturbation expansion
Example
Comparison of perturbation methods
Non-Markovianity
General reservoirs
REGULAR NETWORKS
Binary quantum walk
Complete network
Star network
CONCLUSION
G21 8 G30

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