InterQnet: A Heterogeneous Full-Stack Approach to Co-designing Scalable Quantum Networks

• URL: http://arxiv.org/abs/2509.19503v1
• Date: Tue, 23 Sep 2025 19:22:45 GMT
• Title: InterQnet: A Heterogeneous Full-Stack Approach to Co-designing Scalable Quantum Networks
• Authors: Joaquin Chung, Daniel Dilley, Ely Eastman, Alvin Gonzales, Kara Hokenstad, Md Shariful Islam, Varun Jorapur, Joseph Petrullo, Andy C. Y. Li, Bikun Li, Vasileios Niaouris, Anirudh Ramesh, Ansh Singal, Caitao Zhan, Michael Bishof, Eric Chitambar, Jacob P. Covey, Alan Dibos, Xu Han, Liang Jiang, Prem Kumar, Jeffrey Larson, Zain H. Saleem, Rajkumar Kettimuthu,
• Abstract summary: InterQnet-Achieve focuses on practical realizations of heterogeneous quantum networks.<n>InterQnet-Scale focuses on a systems study of architectural choices for scalable quantum networks.
• Score: 6.4884341485131545
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Quantum communications have progressed significantly, moving from a theoretical concept to small-scale experiments to recent metropolitan-scale demonstrations. As the technology matures, it is expected to revolutionize quantum computing in much the same way that classical networks revolutionized classical computing. Quantum communications will also enable breakthroughs in quantum sensing, metrology, and other areas. However, scalability has emerged as a major challenge, particularly in terms of the number and heterogeneity of nodes, the distances between nodes, the diversity of applications, and the scale of user demand. This paper describes InterQnet, a multidisciplinary project that advances scalable quantum communications through a comprehensive approach that improves devices, error handling, and network architecture. InterQnet has a two-pronged strategy to address scalability challenges: InterQnet-Achieve focuses on practical realizations of heterogeneous quantum networks by building and then integrating first-generation quantum repeaters with error mitigation schemes and centralized automated network control systems. The resulting system will enable quantum communications between two heterogeneous quantum platforms through a third type of platform operating as a repeater node. InterQnet-Scale focuses on a systems study of architectural choices for scalable quantum networks by developing forward-looking models of quantum network devices, advanced error correction schemes, and entanglement protocols. Here we report our current progress toward achieving our scalability goals.

Related papers

• Quantum-Accelerated Wireless Communications: Concepts, Connections, and Implications [59.0413662882849]
  Quantum computing is poised to redefine the algorithmic foundations of communication systems.<n>This article outlines the fundamentals of quantum computing in a style familiar to the communications society.<n>We highlight a mathematical harmony between quantum and wireless systems, which makes the topic more enticing to wireless researchers.
  arXiv  Detail & Related papers  (2025-06-25T22:25:47Z)
• Quantum Data Centers: Why Entanglement Changes Everything [6.310092608526967]
  The Quantum Internet is key for distributed quantum computing, by interconnecting multiple quantum processors into a virtual quantum computation system.<n>We analyze the physical and topological constraints of Quantum Data Centers, by emphasizing the role of entanglement orchestrators in dynamically reconfiguring network topologies.
  arXiv  Detail & Related papers  (2025-06-03T14:22:55Z)
• 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)
• 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)
• 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)
• 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)
• Cavity-enhanced quantum network nodes [0.0]
  A future quantum network will consist of quantum processors that are connected by quantum channels. I will describe how optical resonators facilitate quantum network nodes.
  arXiv  Detail & Related papers  (2022-05-30T18:50:35Z)
• 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)
• 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)
• 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.