Resource Estimation for Delayed Choice Quantum Entanglement Based Sneakernet Networks Using Neutral Atom qLDPC Memories

• URL: http://arxiv.org/abs/2410.01211v1
• Date: Wed, 2 Oct 2024 03:39:45 GMT
• Title: Resource Estimation for Delayed Choice Quantum Entanglement Based Sneakernet Networks Using Neutral Atom qLDPC Memories
• Authors: S. Srikara, Andrew D. Greentree, Simon J. Devitt,
• Abstract summary: We design a quantum communication network with a central party connecting the users through delayed-choice quantum entanglement swapping. Our analysis compares this approach with traditional surface codes, demonstrating that qLDPC codes offer superior scaling in terms of resource efficiency and logical qubit count. We show that with near-term attainable patch sizes, one can attain medium-to-high fidelity correlations, paving the way towards large-scale commercial quantum networks.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum Entanglement is a vital phenomenon required for realizing secure quantum networks, so much that distributed entanglement can be re-imagined as a commodity which can be traded to enable and maintain these networks. We explore the idea of commercializing entanglement-based cryptography and future applications where advanced quantum memory systems support less advanced users. We design a sneakernet-based quantum communication network with a central party connecting the users through delayed-choice quantum entanglement swapping, using quantum Low-Density-Parity-Check (qLDPC) encoded qubits on neutral atoms. Our analysis compares this approach with traditional surface codes, demonstrating that qLDPC codes offer superior scaling in terms of resource efficiency and logical qubit count. We show that with near-term attainable patch sizes, one can attain medium-to-high fidelity correlations, paving the way towards large-scale commercial quantum networks.

Related papers

• Quantum Random Access Codes Implementation for Resource Allocation and Coexistence with Classical Telecommunication [32.73124984242397]
  Modern quantum networks have limited capacity to distribute resources among different users. We experimentally test our encoding and decoding strategy from the resource allocation perspective. By emulating a coexistent classical communication, we test the resilience of our implementation in presence of noise.
  arXiv  Detail & Related papers  (2024-03-27T20:46:50Z)
• 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)
• The Quantum Internet: an Efficient Stabilizer states Distribution Scheme [0.0]
  Quantum networks constitute a major part of quantum technologies. They will boost quantum computing drastically by providing a scalable modular architecture of quantum chips. They will provide the backbone of the future quantum internet, allowing for high margins of security.
  arXiv  Detail & Related papers  (2023-05-04T08:53:38Z)
• Quantum Internet: The Future of Internetworking [16.313110394211154]
  The purpose of a quantum Internet is to enable applications that are fundamentally out of reach for the classical Internet. This chapter aims to present the main concepts, challenges, and opportunities for research in quantum information, quantum computing and quantum networking.
  arXiv  Detail & Related papers  (2023-04-30T23:17:47Z)
• Demonstration of teleportation across a quantum network code [0.0]
  We study measurement-based quantum network coding (MQNC), which is a protocol particularly suitable for noisy intermediate-scale quantum devices. In particular, we develop techniques to adapt MQNC to state-of-the-art superconducting processors and subsequently demonstrate successful teleportation of quantum information. The teleportation in our demonstration is shown to occur with fidelity higher than could be achieved via classical means, made possible by considering qubits from a polar cap of the Bloch Sphere.
  arXiv  Detail & Related papers  (2022-10-06T12:59:48Z)
• 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)
• An Evolutionary Pathway for the Quantum Internet Relying on Secure Classical Repeaters [64.48099252278821]
  We conceive quantum networks using secure classical repeaters combined with the quantum secure direct communication principle. In these networks, the ciphertext gleaned from a quantum-resistant algorithm is transmitted using QSDC along the nodes. We have presented the first experimental demonstration of a secure classical repeater based hybrid quantum network.
  arXiv  Detail & Related papers  (2022-02-08T03:24:06Z)
• The Computational and Latency Advantage of Quantum Communication Networks [70.01340727637825]
  This article summarises the current status of classical communication networks. It identifies some critical open research challenges that can only be solved by leveraging quantum technologies.
  arXiv  Detail & Related papers  (2021-06-07T06:31:02Z)
• Quantum Federated Learning with Quantum Data [87.49715898878858]
  Quantum machine learning (QML) has emerged as a promising field that leans on the developments in quantum computing to explore large complex machine learning problems. This paper proposes the first fully quantum federated learning framework that can operate over quantum data and, thus, share the learning of quantum circuit parameters in a decentralized manner.
  arXiv  Detail & Related papers  (2021-05-30T12:19:27Z)
• Entanglement Classification via Neural Network Quantum States [58.720142291102135]
  In this paper we combine machine-learning tools and the theory of quantum entanglement to perform entanglement classification for multipartite qubit systems in pure states. We use a parameterisation of quantum systems using artificial neural networks in a restricted Boltzmann machine (RBM) architecture, known as Neural Network Quantum States (NNS)
  arXiv  Detail & Related papers  (2019-12-31T07:40:23Z)

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.