Quantum City: simulation of a practical near-term metropolitan quantum
network
- URL: http://arxiv.org/abs/2211.01190v2
- Date: Thu, 3 Nov 2022 12:20:18 GMT
- Title: Quantum City: simulation of a practical near-term metropolitan quantum
network
- Authors: Raja Yehia, Simon Neves, Eleni Diamanti and Iordanis Kerenidis
- Abstract summary: We present the architecture and analyze the applications of a metropolitan-scale quantum network that requires only limited hardware resources for end users.
Using NetSquid, a quantum network simulation tool based on discrete events, we assess the performance of several quantum network protocols involving two or more users in various configurations.
Our results show that practical quantum-enhanced network functionalities are within reach today and can prepare the ground for further applications when more advanced technology becomes available.
- Score: 3.0969191504482247
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: We present the architecture and analyze the applications of a
metropolitan-scale quantum network that requires only limited hardware
resources for end users. Using NetSquid, a quantum network simulation tool
based on discrete events, we assess the performance of several quantum network
protocols involving two or more users in various configurations in terms of
topology, hardware and trust choices. Our analysis takes losses and errors into
account and considers realistic parameters corresponding to present or
near-term technology. Our results show that practical quantum-enhanced network
functionalities are within reach today and can prepare the ground for further
applications when more advanced technology becomes available.
Related papers
- Leveraging Pre-Trained Neural Networks to Enhance Machine Learning with Variational Quantum Circuits [48.33631905972908]
We introduce an innovative approach that utilizes pre-trained neural networks to enhance Variational Quantum Circuits (VQC)
This technique effectively separates approximation error from qubit count and removes the need for restrictive conditions.
Our results extend to applications such as human genome analysis, demonstrating the broad applicability of our approach.
arXiv Detail & Related papers (2024-11-13T12:03:39Z) - Simulators for Quantum Network Modelling: A Comprehensive Review [0.10742675209112622]
We present a review of, to the best of our knowledge, currently used toolkits for modeling quantum networks.
With these toolkits and standardized validation techniques, we can lay down the foundations for more accurate and reliable quantum network simulators.
arXiv Detail & Related papers (2024-08-21T21:07:46Z) - A Quantum-Classical Collaborative Training Architecture Based on Quantum
State Fidelity [50.387179833629254]
We introduce a collaborative classical-quantum architecture called co-TenQu.
Co-TenQu enhances a classical deep neural network by up to 41.72% in a fair setting.
It outperforms other quantum-based methods by up to 1.9 times and achieves similar accuracy while utilizing 70.59% fewer qubits.
arXiv Detail & Related papers (2024-02-23T14:09:41Z) - Practical limitations on robustness and scalability of quantum Internet [0.7499722271664144]
We study the limitations on the scaling and robustness of quantum Internet.
We present practical bottlenecks for secure communication, delegated computing, and resource distribution among end nodes.
For some examples of quantum networks, we present algorithms to perform different quantum network tasks of interest.
arXiv Detail & Related papers (2023-08-24T12:32:48Z) - Connecting Quantum Cities: Simulation of a Satellite-Based Quantum
Network [2.3746609573239756]
We present and analyse an architecture for a European-scale quantum network using satellite links to connect Quantum Cities.
We benchmark the performance of such a network linking distant locations in Europe in terms of quantum key distribution rates.
Our results highlight the key parameters and the limits of current satellite quantum communication links and can be used to assist the design of future missions.
arXiv Detail & Related papers (2023-07-21T14:22:29Z) - Resource Saving via Ensemble Techniques for Quantum Neural Networks [1.4606049539095878]
We propose the use of ensemble techniques, which involve constructing a single machine learning model based on multiple instances of quantum neural networks.
In particular, we implement bagging and AdaBoost techniques, with different data loading configurations, and evaluate their performance on both synthetic and real-world classification and regression tasks.
Our findings indicate that these methods enable the construction of large, powerful models even on relatively small quantum devices.
arXiv Detail & Related papers (2023-03-20T17:19:45Z) - Multi-User Entanglement Distribution in Quantum Networks Using Multipath
Routing [55.2480439325792]
We propose three protocols that increase the entanglement rate of multi-user applications by leveraging multipath routing.
The protocols are evaluated on quantum networks with NISQ constraints, including limited quantum memories and probabilistic entanglement generation.
arXiv Detail & Related papers (2023-03-06T18:06:00Z) - DQC$^2$O: Distributed Quantum Computing for Collaborative Optimization
in Future Networks [54.03701670739067]
We propose an adaptive distributed quantum computing approach to manage quantum computers and quantum channels for solving optimization tasks in future networks.
Based on the proposed approach, we discuss the potential applications for collaborative optimization in future networks, such as smart grid management, IoT cooperation, and UAV trajectory planning.
arXiv Detail & Related papers (2022-09-16T02:44:52Z) - Tools for quantum network design [0.0]
We review the state of the art of tools for evaluating the performance of quantum networks.
We present them from three different angles: information-theoretic benchmarks, analytical tools, and simulation.
arXiv Detail & Related papers (2020-12-12T09:19:25Z) - Experimental Quantum Generative Adversarial Networks for Image
Generation [93.06926114985761]
We experimentally achieve the learning and generation of real-world hand-written digit images on a superconducting quantum processor.
Our work provides guidance for developing advanced quantum generative models on near-term quantum devices.
arXiv Detail & Related papers (2020-10-13T06:57:17Z) - SeQUeNCe: A Customizable Discrete-Event Simulator of Quantum Networks [53.56179714852967]
This work develops SeQUeNCe, a comprehensive, customizable quantum network simulator.
We implement a comprehensive suite of network protocols and demonstrate the use of SeQUeNCe by simulating a photonic quantum network with nine routers equipped with quantum memories.
We are releasing SeQUeNCe as an open source tool and aim to generate community interest in extending it.
arXiv Detail & Related papers (2020-09-25T01:52:15Z)
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.