Abstract

The goal of entanglement distillation is to turn a large number of weakly entangled states into a smaller number of highly entangled ones. Practical entanglement distillation schemes offer a tradeoff between the fidelity to the target state, and the probability of successful distillation. Exploiting such tradeoffs is of interest in the design of quantum repeater protocols. Here, we present a number of methods to assess and optimize entanglement distillation schemes. We start by giving a numerical method to compute upper bounds on the maximum achievable fidelity for a desired probability of success. We show that this method performs well for many known examples by comparing it to well-known distillation protocols. This allows us to show optimality for many well-known distillation protocols for specific states of interest. As an example, we analytically prove optimality of the distillation protocol utilized within the Extreme Photon Loss (EPL) entanglement generation scheme, even in the asymptotic limit. We proceed to present a numerical method that can improve an existing distillation scheme for a given input state, and we present an example for which this method finds an optimal distillation protocol. An implementation of our numerical methods is available as a Julia package.

Highlights

  • Entanglement distillation forms an important element of many proposals for quantum repeaters [1,2,3,4,5], as well as networked quantum computers [6,7]

  • We analytically prove optimality of the distillation protocol utilized within the Extreme Photon Loss entanglement generation scheme, even in the asymptotic limit

  • We proceed to present a numerical method that can improve an existing distillation scheme for a given input state, and we present an example for which this method finds an optimal distillation protocol

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Summary

INTRODUCTION

Entanglement distillation forms an important element of many proposals for quantum repeaters [1,2,3,4,5], as well as networked quantum computers [6,7]. The success probability psucc dictates the rate at which we can hope to produce highfidelity entanglement between different nodes in the network This rate imposes requirements on the coherence times of the memory if multiple entangled pairs are generated such that they should undergo further processing, for example, to generate more complex entangled states in a multinode network. In such a scenario, one may wish to obtain a higher probability of success at the expense of a lower fidelity (or vice versa) in relation to the local storage capabilities of the nodes.

OVERVIEW
OPTIMIZATION METHODS
General form
Simplifying the optimization problem
Reliable upper bounds using SDP relaxations
PPT relaxations
Bose symmetric extensions
Optimizing existing schemes
STATES AND DISTILLATION SCHEMES
Isotropic states
Bell diagonal states
Numerical examples
Optimal fidelity and success probability
R states
Remote entanglement generation
Optimal fidelity and probability of success
Optimality with respect to distillable entanglement
S states
DISCUSSION
1: Depolarize the two available copies of the state to the isotropic state form:
Interpolating and extrapolating between and from the fixed schemes
D MA B
Optimizing fidelity
Optimizing probability of success
Optimal fidelity of DEJMPS
Optimal probability of success of DEJMPS
EPL-D is distillation-optimal

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