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arXiv:1903.09655

Entanglement theory in distributed quantum information processing

隼汰 山崎

Published Mar 22, 2019• 1 citation
arXivHTMLPDF

Abstract

Distributed quantum information processing is a promising platform for scaling up quantum information processing, where small- and intermediate-scale quantum devices are connected by a network of quantum channels for communicating quantum information, so as to cooperate in achieving larger-scale information processing. In such distributed settings, entangled states shared among the multiple devices serve as a resource for achieving nonlocal information processing tasks by local operations and classical communication (LOCC), where transformations of multipartite entangled states play central roles. This thesis analyzes properties of quantum entanglement in these small- and intermediate-scale settings and multipartite settings. The first part of this thesis investigates a communication task, quantum state merging, on the small and intermediate scales. The second part of this thesis analyzes multipartite entanglement in distributed quantum information processing. These analyses clarify fundamental limitations and potential applications of distributed quantum information processing to characterize properties of quantum entanglement in the small- and intermediate-scale settings and multipartite settings, providing a paradigm for investigating multipartite entanglement in distributed quantum information processing over networks beyond the state convertibility under LOCC.

DOI
10.48550/arxiv.1903.09655

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Distributed quantum information processing is a promising platform for scaling up quantum information processing, where small- and intermediate-scale quantum devices are connected by a network of quantum channels for communicating quantum information, so as to cooperate in achieving larger-scale information processing. In such distributed settings, entangled states shared among the multiple devices serve as a resource for achieving nonlocal information processing tasks by local operations and classical communication (LOCC), where transformations of multipartite entangled states play central roles. This thesis analyzes properties of quantum entanglement in these small- and intermediate-scale settings and multipartite settings. The first part of this thesis investigates a communication task, quantum state merging, on the small and intermediate scales. The second part of this thesis analyzes multipartite entanglement in distributed quantum information processing. These analyses clarify fundamental limitations and potential applications of distributed quantum information processing to characterize properties of quantum entanglement in the small- and intermediate-scale settings and multipartite settings, providing a paradigm for investigating multipartite entanglement in distributed quantum information processing over networks beyond the state convertibility under LOCC.
Abstract Encoding and decoding quantum information in a multipartite quantum system are indispensable for quantum error correction and also play crucial roles in multiparty tasks in distributed quantum information processing such as quantum secret sharing. To quantitatively characterize nonlocal properties of multipartite quantum transformations for encoding and decoding, we analyze the entanglement costs of encoding and decoding quantum information in a multipartite quantum system distributed among spatially separated parties connected by a network. This analysis generalizes previous studies of entanglement costs for preparing bipartite and multipartite quantum states and implementing bipartite quantum transformations by entanglement‐assisted local operations and classical communication (LOCC). We identify conditions for the parties being able to encode or decode quantum information in the distributed quantum system deterministically and exactly, when inter‐party quantum communication is restricted to a tree‐topology network. In our analysis, we reduce the multiparty tasks of implementing the encoding and decoding to sequential applications of one‐shot zero‐error quantum state splitting and merging for two parties. While encoding and decoding are inverse tasks of each other, our results suggest that a quantitative difference in entanglement cost between encoding and decoding arises due to the difference between quantum state merging and splitting.
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Abstract Distributed quantum information processing is essential for building quantum networks and enabling more extensive quantum computations. In this regime, several spatially separated parties share a multipartite quantum system, and the most natural set of operations is Local Operations and Classical Communication (LOCC). As a pivotal part in quantum information theory and practice, LOCC has led to many vital protocols such as quantum teleportation. However, designing practical LOCC protocols is challenging due to LOCC’s intractable structure and limitations set by near-term quantum devices. Here we introduce LOCCNet, a machine learning framework facilitating protocol design and optimization for distributed quantum information processing tasks. As applications, we explore various quantum information tasks such as entanglement distillation, quantum state discrimination, and quantum channel simulation. We discover protocols with evident improvements, in particular, for entanglement distillation with quantum states of interest in quantum information. Our approach opens up new opportunities for exploring entanglement and its applications with machine learning, which will potentially sharpen our understanding of the power and limitations of LOCC. An implementation of LOCCNet is available in Paddle Quantum, a quantum machine learning Python package based on PaddlePaddle deep learning platform.
Entanglement is one of the fundamental features of quantum information science. Though bipartite entanglement has been analyzed thoroughly in theory and shown to be an important resource in quantum computation and communication protocols, the theory of entanglement shared between more than two parties, which is called multipartite entanglement, is still not complete. This book contains Dr. Wei Cui's research regarding the classification of multipartite entanglement and the transformation property between different multipartite states by local operators and classical communications (LOCC), which are two fundamental questions in the theory of multipartite entanglement.
In this thesis, we investigate two different aspects of entanglement and classical communication in distributed quantum computation (DQC). In the first part, we analyze implementable computation over a given quantum network resource by introducing a new concept, quantum network coding for quantum computation. We consider a setting of networks where quantum communication for each edge of a network is restricted to sending one-qubit, but classical communication is unrestricted. Specifically, we analyze implementable kkk-qubit unitary operations over a certain class of networks, called cluster networks. We show that any two-qubit unitary operation is implementable over the butterfly network and the grail network, which are fundamental primitive networks for network coding. We also obtain necessary and sufficient conditions for the probabilistic implementability of unitary operations over cluster networks. In the second part, we investigate resource tradeoffs in DQC. First, we show that entanglement required for local state discrimination can be substituted by less entanglement by increasing the rounds of classical communication. Second, we develop a new framework of deterministic joint quantum operations by using a causal relation between the outputs and inputs of the local operations without predefined causal order, called "classical communication" without predefined causal order (CC*). We show that local operations and CC* (LOCC*) is equivalent to the separable operation (SEP). This result indicates that entanglement-assisted LOCC implementing SEP can be simulated by LOCC* without entanglement. We also investigate the relationship between LOCC* and another formalism for deterministic joint quantum operations without assuming predefined causal order based on the quantum process formalism. As a result, we construct an example of non-LOCC SEP by using LOCC*.
Recent advances in quantum technology facilitate the realization of information processing using quantum computers at least on the small and intermediate scales of up to several dozens of qubits. We investigate entanglement cost required for one-shot quantum state merging, aiming at quantum state transformation on these scales. In contrast to existing coding algorithms achieving nearly optimal approximate quantum state merging on a large scale, we construct algorithms for exact quantum state merging so that the algorithms are applicable to any given state of an arbitrarily small-dimensional system. In the algorithms, the entanglement cost can be reduced depending on a structure of the given state derived from the Koashi-Imoto decomposition. We also provide improved converse bounds for exact quantum state merging achievable for qubits but not necessarily achievable in general. As for approximate quantum state merging, we obtain algorithms and improved converse bounds by applying smoothing to those for exact state merging. Our results are applicable to distributed quantum information processing and multipartite entanglement transformation on small and intermediate scales.