Circuit Implementation of Discrete-Time Quantum Walks on Complex Networks

• URL: http://arxiv.org/abs/2408.15653v1
• Date: Wed, 28 Aug 2024 09:11:47 GMT
• Title: Circuit Implementation of Discrete-Time Quantum Walks on Complex Networks
• Authors: Rei Sato, Kazuhiro Saito,
• Abstract summary: Quantum walks are powerful tools for various graph-based applications. We present a circuit design for implementing discrete-time quantum walks on complex networks.
• Score: 2.0257616108612373
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we propose a circuit design for implementing quantum walks on complex networks. Quantum walks are powerful tools for various graph-based applications such as spatial search, community detection, and node classification. Although many quantum-walk-based graph algorithms have been extensively studied, specific quantum circuits for implementing these algorithms have not yet been provided. To address this issue, we present a circuit design for implementing the discrete-time quantum walk on complex networks. We investigate the functionality of our circuit using the small-sized Watts-and-Strogatz model as the complex network model, comparing it with theoretical calculations. This work offers a new approach to constructing quantum circuits for implementing quantum walks on arbitrary complex networks.

Related papers

• Quantum Compiling with Reinforcement Learning on a Superconducting Processor [55.135709564322624]
  We develop a reinforcement learning-based quantum compiler for a superconducting processor. We demonstrate its capability of discovering novel and hardware-amenable circuits with short lengths. Our study exemplifies the codesign of the software with hardware for efficient quantum compilation.
  arXiv  Detail & Related papers  (2024-06-18T01:49:48Z)
• Distributed quantum architecture search [0.0]
  Variational quantum algorithms, inspired by neural networks, have become a novel approach in quantum computing. Quantum architecture search tackles this by adjusting circuit structures along with gate parameters to automatically discover high-performance circuit structures. We propose an end-to-end distributed quantum architecture search framework, where we aim to automatically design distributed quantum circuit structures for interconnected quantum processing units with specific qubit connectivity.
  arXiv  Detail & Related papers  (2024-03-10T13:28:56Z)
• Entanglement-Assisted Quantum Networks: Mechanics, Enabling Technologies, Challenges, and Research Directions [66.27337498864556]
  This paper presents a comprehensive survey of entanglement-assisted quantum networks. It provides a detailed overview of the network structure, working principles, and development stages. It also emphasizes open research directions, including architecture design, entanglement-based network issues, and standardization.
  arXiv  Detail & Related papers  (2023-07-24T02:48:22Z)
• The Basis of Design Tools for Quantum Computing: Arrays, Decision Diagrams, Tensor Networks, and ZX-Calculus [55.58528469973086]
  Quantum computers promise to efficiently solve important problems classical computers never will. A fully automated quantum software stack needs to be developed. This work provides a look "under the hood" of today's tools and showcases how these means are utilized in them, e.g., for simulation, compilation, and verification of quantum circuits.
  arXiv  Detail & Related papers  (2023-01-10T19:00:00Z)
• On the quantum simulation of complex networks [0.0]
  Continuous-time quantum walk algorithms assume that we can simulate the dynamics of quantum systems where the Hamiltonian is given by the adjacency matrix of the graph. We extend the state-of-the-art results on quantum simulation to graphs that contain a small number of hubs, but that are otherwise sparse.
  arXiv  Detail & Related papers  (2022-12-12T18:55:31Z)
• Parametric Synthesis of Computational Circuits for Complex Quantum Algorithms [0.0]
  The purpose of our quantum synthesizer is enabling users to implement quantum algorithms using higher-level commands. The proposed approach for implementing quantum algorithms has a potential application in the field of machine learning.
  arXiv  Detail & Related papers  (2022-09-20T06:25:47Z)
• Analysis of arbitrary superconducting quantum circuits accompanied by a Python package: SQcircuit [0.0]
  Superconducting quantum circuits are a promising hardware platform for realizing a fault-tolerant quantum computer. We develop a framework to construct a superconducting quantum circuit's quantized Hamiltonian from its physical description. We implement the methods described in this work in an open-source Python package SQcircuit.
  arXiv  Detail & Related papers  (2022-06-16T17:24:51Z)
• Optimizing Tensor Network Contraction Using Reinforcement Learning [86.05566365115729]
  We propose a Reinforcement Learning (RL) approach combined with Graph Neural Networks (GNN) to address the contraction ordering problem. The problem is extremely challenging due to the huge search space, the heavy-tailed reward distribution, and the challenging credit assignment. We show how a carefully implemented RL-agent that uses a GNN as the basic policy construct can address these challenges.
  arXiv  Detail & Related papers  (2022-04-18T21:45:13Z)
• Quantum circuit debugging and sensitivity analysis via local inversions [62.997667081978825]
  We present a technique that pinpoints the sections of a quantum circuit that affect the circuit output the most. We demonstrate the practicality and efficacy of the proposed technique by applying it to example algorithmic circuits implemented on IBM quantum machines.
  arXiv  Detail & Related papers  (2022-04-12T19:39:31Z)
• Fast Swapping in a Quantum Multiplier Modelled as a Queuing Network [64.1951227380212]
  We propose that quantum circuits can be modeled as queuing networks. Our method is scalable and has the potential speed and precision necessary for large scale quantum circuit compilation.
  arXiv  Detail & Related papers  (2021-06-26T10:55:52Z)
• Realising and compressing quantum circuits with quantum reservoir computing [2.834895018689047]
  We show how a random network of quantum nodes can be used as a robust hardware for quantum computing. Our network architecture induces quantum operations by optimising only a single layer of quantum nodes. In the few-qubit regime, sequences of multiple quantum gates in quantum circuits can be compressed with a single operation.
  arXiv  Detail & Related papers  (2020-03-21T03:29:16Z)

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.