This paper presents the design of scalable quantum networks that utilize optical switches to interconnect multiple quantum processors, facilitating large-scale quantum computing. By leveraging these novel architectures, we aim to address the limitations of current quantum processors and explore the potential of quantum data centers. We provide an in-depth analysis of these architectures through the development of simulation tools and performance metrics, offering a detailed comparison of their advantages and trade-offs. We hope this work serves as a foundation for the development of efficient and resilient quantum networks, designed to meet the evolving demands of future quantum computing applications.
This paper presents the design of scalable quantum networks that utilize optical switches to interconnect multiple quantum processors, facilitating large-scale quantum computing. By leveraging these novel architectures, we aim to address the limitations of current quantum processors and explore the potential of quantum data centers. We provide an in-depth analysis of these architectures through the development of simulation tools and performance metrics, offering a detailed comparison of their advantages and trade-offs. We hope this work serves as a foundation for the development of efficient and resilient quantum networks, designed to meet the evolving demands of future quantum computing applications.
The Quantum Internet is key for distributed quantum computing, by interconnecting multiple quantum processors into a virtual quantum computation system. This allows for scaling the number of qubits by overcoming the inherent limitations of noisy intermediate-scale quantum devices. Thus, the Quantum Internet is the foundation for large-scale, fault-tolerant quantum computation. Among the distributed architectures, quantum data centres emerge as the most viable in the medium term, since they integrate multiple quantum processors within a localized network infrastructure, by allowing modular design of quantum networking. We analyse the physical and topological constraints of quantum data centres, by emphasizing the role of entanglement orchestrators in dynamically reconfiguring network topologies through local operations. We examine the major hardware challenge of quantum transduction, essential for interfacing heterogeneous quantum systems. Furthermore, we explore how interconnecting multiple Quantum Data Centres could enable large-scale quantum networks. We discuss the topological constraints of such a scaling and identify open challenges, including entanglement routing and synchronization. The analysis positions quantum data centres as both a practical implementation platform and strategic framework for the future quantum internet. This article is part of the discussion meeting issue 'Bits, neurons and qubits for sustainable AI'.
Quantum entanglement generation and distribution is key to the vision for a Quantum Internet. Existing research has focused on entanglement routing schemes and QR performance in a general network setting with strong physical layer assumptions. In reality, the required quantum memory and quantum repeater devices along with the control protocols for general quantum networks remain grand challenges in the foreseeable future. Main performance concerns at the networking layer include entanglement distribution rate and fidelity. We thereafter propose to focus more research efforts on the quantum data center network due to its structured topology and potential to support emerging distributed quantum computing applications. This paper presents a quantum data center (QDC) network architecture with novel switch architecture and protocols that feature locally buffered entanglement qubits and centralized on-demand entanglement generation and distribution. Queueing models for the switches and large-scale network simulation with the NetSquid quantum simulator demonstrate the high network throughput, scalability, and fidelity performance for the proposed QDC network architecture and protocol.
This paper presents a comprehensive review of quantum computing and the technological foundations of quantum processors. Quantum computing represents a transformative computational paradigm that leverages the fundamental principles of quantum mechanics—such as superposition, entanglement, and quantum interference—to solve complex problems that are intractable for classical computers. At the core of this paradigm lies the quantum processor, a specialized hardware system designed to initialize, control, and measure quantum bits (qubits) through precise gate operations and coherent interactions. The survey examines the essential theoretical concepts underlying quantum computation and provides a structured comparison of leading quantum processor platforms. Prominent architectures, including superconducting circuits, trapped-ion systems, and photonic implementations, are analyzed in terms of their physical mechanisms, scalability, coherence properties, and engineering challenges. Each platform offers distinct advantages and faces specific technical limitations related to noise, error correction, and fabrication complexity. In addition to reviewing hardware developments, this study highlights key obstacles in advancing quantum processors toward large-scale, fault-tolerant systems. Issues such as qubit stability, error mitigation, thermal management, and system integration are discussed to present a realistic perspective on current progress. Performance indicators including gate fidelity, coherence time, connectivity, and scalability are used to compare architectural approaches. The objective of this paper is to provide a clear and organized synthesis of recent advancements in quantum computing hardware, thereby offering researchers and practitioners a foundational reference to support continued innovation and development in this rapidly evolving field.
There is a growing research interest in quantum computing because of its promise to provide significant performance speedups over classical computers at specialized tasks. While there have been many advances in building more capable, robust, and useful quantum algorithms and software, it is not clear how a scalable, high-performance, and area-efficient quantum architecture should be designed for efficient execution of various quantum workloads. This paper attempts to fill this gap by performing a detailed characterization of many real-world quantum algorithms on SIMDstyle quantum architectures. Specifically, we characterize the effect of size and the number of SIMD regions of a quantum SIMD architecture on various metrics such as performance, utilization, qubit (data) movement etc. We hope that the presented insights on the trade-offs and relationships between aforementioned evaluation metrics will be useful towards designing an efficient and scalable quantum architecture.
Scalable distributed quantum computing (DQC) has motivated the design of multiple quantum data-center (QDC) architectures that overcome the limitations of single quantum processors through modular interconnection. While these architectures adopt fundamentally different design philosophies, their relative performance under realistic quantum hardware constraints remains poorly understood.
In this paper, we present a systematic benchmarking study of four representative QDC architectures-QFly, BCube, Clos, and Fat-Tree-quantifying their impact on distributed quantum circuit execution latency, resource contention, and scalability. Focusing on quantum-specific effects absent from classical data-center evaluations, we analyze how optical-loss-induced Einstein-Podolsky-Rosen (EPR) pair generation delays, coherence-limited entanglement retry windows, and contention from teleportation-based non-local gates shape end-to-end execution performance. Across diverse circuit workloads, we evaluate how architectural properties such as path diversity and path length, and shared BSM (Bell State Measurement) resources interact with optical-switch insertion loss and reconfiguration delay. Our results show that distributed quantum performance is jointly shaped by topology, scheduling policies, and physical-layer parameters, and that these factors interact in nontrivial ways. Together, these insights provide quantitative guidance for the design of scalable and high-performance quantum data-center architectures for DQC.
Quantum Data Centers (QDCs) are needed to support large-scale quantum processing for both academic and commercial applications. While large-scale quantum computers are constrained by technological and financial barriers, a modular approach that clusters small quantum computers offers an alternative. This approach, however, introduces new challenges in network scalability, entanglement generation, and quantum memory management. In this paper, we propose a three-layer fat-tree network architecture for QDCs, designed to address these challenges. Our architecture features a unique leaf switch and an advanced swapping spine switch design, optimized to handle high volumes of entanglement requests as well as a queue scheduling mechanism that efficiently manages quantum memory to prevent decoherence. Through queuing-theoretical models and simulations in NetSquid, we demonstrate the proposed architecture's scalability and effectiveness in maintaining high entanglement fidelity, offering a practical path forward for modular QDC networks.