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.
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.
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.
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-center (QDC) architectures aim to scale distributed quantum computing (DQC) by interconnecting multiple quantum processing units (QPUs), but their performance depends strongly on how algorithmic communication patterns interact with entanglement generation, switch reconfiguration, and network topology. This paper studies the Quantum Approximate Optimization Algorithm (QAOA) as a graph-structured optimization workload for QDC-based distributed quantum computing. We adapt QAOA to SwitchQNet, a distributed quantum compiler framework that schedules communication and entanglement generation over switch-based QDC networks, by adding a routing generator that converts graph-dependent two-qubit cost interactions into remote-CX communication requests across QPUs. Using this extension, we evaluate QAOA instances across Clos, fat-tree, and spine-leaf topologies, measuring communication latency, EPR-pair overhead, EPR wait time, retry overhead, and sensitivity to buffer size, look-ahead depth, communication-qubit count, EPR latency, and EPR fidelity assumptions. The results show that QAOA obtains modest but consistent latency reductions, highlighting its value as a diagnostic benchmark for studying the interaction between algorithm structure, entanglement management, and quantum-network architecture.
As practical quantum networks prepare to serve an ever-expanding number of nodes, there has grown a need for advanced auxiliary classical systems that support the quantum protocols and maintain compatibility with the existing fiber-optic infrastructure. We propose and demonstrate a quantum local area network design that addresses current deployment limitations in timing and security in a scalable fashion using commercial off-the-shelf components. First, we employ White Rabbit switches to synchronize three remote nodes with ultra-low timing jitter, significantly increasing the fidelities of the distributed entangled states over previous work with Global Positioning System clocks. Second, using a parallel quantum key distribution channel, we secure the classical communications needed for instrument control and data management. In this way, the conventional network that manages our entanglement network is secured using keys generated via an underlying quantum key distribution layer, preserving the integrity of the supporting systems and the relevant data in a future-proof fashion.
Modular quantum computing scales quantum systems by connecting Quantum Processing Units (QPUs) through a quantum network. A key challenge in such architectures is efficiently scheduling entanglement generation to enable distributed circuit execution. This work investigates how architectural factors—such as network topology, switch placement, and communication qubit allocation—impact entanglement scheduling and resource utilization. Through simulation, we evaluate static and dynamic scheduling strategies under realistic constraints including probabilistic entanglement generation, limited communication qubits, reconfiguration delays, and qubit coherence time. Our results show that dynamic scheduling performs better in highly connected architectures, while sparse topologies lead to contention and entanglement loss. We also profile Bell State Measurement (BSM) demand to identify architectural bottlenecks and inform provisioning. These insights highlight the critical role of architecture in enabling scalable, efficient distributed quantum computing.
Server-centric quantum data-center architectures offer scalability by distributing communication tasks across QPUs rather than concentrating complexity in a centralized switching core. However, scaling such architectures increases the path length, the number of Bell-state measurements, and the loss of end-to-end fidelity. We ask whether the path diversity of a server-centric topology can be converted into a mechanism for preserving not only rate, but also fidelity. We study this through end-to-end purification as a fidelity-restoration mechanism. First, in a black-box model, we determine the minimum number of raw end-to-end Werner-state copies, each carrying the degraded Werner parameter of a distance-ell path, that purification must consume to recover a single copy matching an elementary link, comparing recursive 2-to-1 and optimized nested r-to-1 purification. Second, we instantiate these requirements in a probabilistic BCube architecture, whose edge-disjoint path diversity supplies the raw copies. Because purification imposes a lower bound on input fidelity, no path redundancy can raise the output below this threshold, which limits scaling. To address it we present the Hop-Independent Quantum Data Center (HI-QDC), an isometric, modular, scalable architecture in which purification transforms end-to-end entanglement across a module into an effective link-level resource for the inter-module topology. Our results identify the regimes in which a BCube module, under end-to-end purification, preserves both the fidelity and the yield of an elementary link. The module then hides its internal hop count and acts as an effective elementary link for a higher-level network. Thus topology supplies the path multiplicity purification requires, while purification converts it into fidelity recovery, enabling recursively scalable quantum data-center networks.