Distributed Partial Quantum Consensus of Qubit Networks with Connected Topologies

• URL: http://arxiv.org/abs/2402.14256v1
• Date: Thu, 22 Feb 2024 03:44:45 GMT
• Title: Distributed Partial Quantum Consensus of Qubit Networks with Connected Topologies
• Authors: Xin Jin, Zhu Cao, Yang Tang, Juergen Kurths
• Abstract summary: Two partial quantum consensus protocols, based on the Lyapunov method for chain graphs and the geometry method for connected graphs, are proposed. The numerical simulation over a qubit network is demonstrated to verify the validity and the effectiveness of the theoretical results.
• Score: 13.978557505365604
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we consider the partial quantum consensus problem of a qubit network in a distributed view. The local quantum operation is designed based on the Hamiltonian by using the local information of each quantum system in a network of qubits. We construct the unitary transformation for each quantum system to achieve the partial quantum consensus, i.e., the directions of the quantum states in the Bloch ball will reach an agreement. A simple case of two-qubit quantum systems is considered first, and a minimum completing time of reaching partial consensus is obtained based on the geometric configuration of each qubit. Furthermore, we extend the approaches to deal with the more general N-qubit networks. Two partial quantum consensus protocols, based on the Lyapunov method for chain graphs and the geometry method for connected graphs, are proposed. The geometry method can be utilized to deal with more general connected graphs, while for the Lyapunov method, the global consensus can be obtained. The numerical simulation over a qubit network is demonstrated to verify the validity and the effectiveness of the theoretical results.

Related papers

• Quantum Advantage in Distributed Sensing with Noisy Quantum Networks [37.23288214515363]
  We show that quantum advantage in distributed sensing can be achieved with noisy quantum networks. We show that while entanglement is needed for this quantum advantage, genuine multipartite entanglement is generally unnecessary.
  arXiv  Detail & Related papers  (2024-09-25T16:55:07Z)
• Success probabilities in time-reversal based hybrid quantum state transfer [0.0]
  We consider two memory nodes of a quantum network connected by flying qubits. We show how and why the probability of interfacing successfully is determined by the overlap of the spectral shape of the actual flying qubit and the ideal shape.
  arXiv  Detail & Related papers  (2024-01-16T04:38:10Z)
• Tight One-Shot Analysis for Convex Splitting with Applications in Quantum Information Theory [23.18400586573435]
  We establish a one-shot error exponent and a one-shot strong converse for convex splitting with trace distance as an error criterion. This leads to new one-shot exponent results in various tasks such as communication over quantum wiretap channels, secret key distillation, one-way quantum message compression, quantum measurement simulation, and quantum channel coding with side information at the transmitter.
  arXiv  Detail & Related papers  (2023-04-24T12:47:37Z)
• Quantum circuits for the Ising spin networks [0.0]
  We introduce an improved method for constructing quantum circuits for 4-valent Ising spin networks. This has practical implications for the implementation of quantum circuits.
  arXiv  Detail & Related papers  (2023-04-07T09:42:29Z)
• QuanGCN: Noise-Adaptive Training for Robust Quantum Graph Convolutional Networks [124.7972093110732]
  We propose quantum graph convolutional networks (QuanGCN), which learns the local message passing among nodes with the sequence of crossing-gate quantum operations. To mitigate the inherent noises from modern quantum devices, we apply sparse constraint to sparsify the nodes' connections. Our QuanGCN is functionally comparable or even superior than the classical algorithms on several benchmark graph datasets.
  arXiv  Detail & Related papers  (2022-11-09T21:43:16Z)
• Quantum Network Tomography with Multi-party State Distribution [10.52717496410392]
  characterization of quantum channels in a quantum network is of paramount importance. We introduce the problem of Quantum Network Tomography. We study this problem in detail for the case of arbitrary star quantum networks with quantum channels described by a single Pauli operator.
  arXiv  Detail & Related papers  (2022-06-06T21:47:09Z)
• Efficient Bipartite Entanglement Detection Scheme with a Quantum Adversarial Solver [89.80359585967642]
  Proposal reformulates the bipartite entanglement detection as a two-player zero-sum game completed by parameterized quantum circuits. We experimentally implement our protocol on a linear optical network and exhibit its effectiveness to accomplish the bipartite entanglement detection for 5-qubit quantum pure states and 2-qubit quantum mixed states.
  arXiv  Detail & Related papers  (2022-03-15T09:46:45Z)
• Quantum algorithms for grid-based variational time evolution [36.136619420474766]
  We propose a variational quantum algorithm for performing quantum dynamics in first quantization. Our simulations exhibit the previously observed numerical instabilities of variational time propagation approaches.
  arXiv  Detail & Related papers  (2022-03-04T19:00:45Z)
• Quantum Entropic Causal Inference [30.939150842529052]
  We put forth a new theoretical framework for merging quantum information science and causal inference by exploiting entropic principles. We apply our proposed framework to an experimentally relevant scenario of identifying message senders on quantum noisy links.
  arXiv  Detail & Related papers  (2021-02-23T15:51:34Z)
• Relaxation to Equilibrium in a Quantum Network [0.0]
  We study the relaxation to equilibrium for a fully connected quantum network with CNOT gates. We give a number of results for the equilibration in these systems, including analytic estimates.
  arXiv  Detail & Related papers  (2020-09-28T22:15:35Z)
• Quantum State Discrimination on Reconfigurable Noise-Robust Quantum Networks [6.85316573653194]
  A fundamental problem in Quantum Information Processing is the discrimination amongst a set of quantum states of a system. In this paper, we address this problem on an open quantum system described by a graph, whose evolution is defined by a Quantum Walk. We optimize the parameters of the network to obtain the highest probability of correct discrimination.
  arXiv  Detail & Related papers  (2020-03-25T19:07:03Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.