Quantum computing offers the potential to solve certain complex problems, yet, scaling monolithic processors remains a major challenge. Modular and distributed architectures are proposed to build large-scale quantum systems while bringing the security advantages of quantum communication. At present, this requires accurate and computationally efficient models of quantum links across different scales to advance system design and guide experimental prototyping. In this work, we review protocols and models for estimating latency, losses, and fidelity in quantum communication primitives relying on quantum state distribution via microwave photons. We also propose a scalable simulation framework to support the design and evaluation of future distributed quantum computing systems.
Quantum computing offers the potential to solve certain complex problems, yet, scaling monolithic processors remains a major challenge. Modular and distributed architectures are proposed to build large-scale quantum systems while bringing the security advantages of quantum communication. At present, this requires accurate and computationally efficient models of quantum links across different scales to advance system design and guide experimental prototyping. In this work, we review protocols and models for estimating latency, losses, and fidelity in quantum communication primitives relying on quantum state distribution via microwave photons. We also propose a scalable simulation framework to support the design and evaluation of future distributed quantum computing systems.
Quantum simulation is a promising pathway toward practical quantum advantage by simulating large-scale quantum systems. In this Letter, we propose communication-efficient distributed quantum simulation protocols by exploring three quantum simulation algorithms, including the product formula, the truncated Taylor series, and quantum signal processing over a quantum network. Crucially, our protocols significantly reduce the local hardware requirements of individual quantum processing units while ensuring the overall gate complexity does not exceed that of standard monolithic architectures. Our protocols are further shown to be optimal by deriving a lower bound on the quantum communication complexity for distributed quantum simulations with respect to evolution time and the number of distributed quantum processing units. Additionally, our distributed techniques go beyond quantum simulation and are applied to distributed versions of Grover's algorithm and quantum phase estimation. Our work not only paves the way for achieving a practical quantum advantage by scalable quantum simulation but also enlightens the design of more general distributed architectures across various physical systems for quantum computation.
This paper explores the potential of utilizing quantum simulation algorithms to achieve distributed simulation of complex physical systems. The core concept involves breaking down computationally intensive simulations—such as fluid dynamics or molecular interactions—into smaller, manageable subproblems solvable on multiple quantum processors. These subproblem solutions are then integrated through quantum communication protocols. The research investigates the theoretical framework for such an approach, focusing on algorithm design, communication strategies, and the challenges associated with achieving efficient distributed simulation. This work demonstrates a practical application of quantum computing for large-scale simulation tasks, offering a novel methodology for tackling problems currently intractable for classical computers. We detail the key considerations for designing a robust and scalable distributed simulation system, including error mitigation techniques and the impact of quantum communication fidelity on overall simulation accuracy.
A core challenge for superconducting quantum computers is to scale up the number of qubits in each processor without increasing noise or cross-talk. Distributed quantum computing across small qubit arrays, known as chiplets, can address these challenges in a scalable manner. We propose a chiplet architecture over microwave links with potential to exceed monolithic performance on near-term hardware. Our methods of modeling and evaluating the chiplet architecture bridge the physical and network layers in these processors. We find evidence that distributing computation across chiplets may reduce the overall error rates associated with moving data across the device, despite higher error figures for transfers across links. Preliminary analyses suggest that latency is not substantially impacted, and that at least some applications and architectures may avoid bottlenecks around chiplet boundaries. In the long-term, short-range networks may underlie quantum computers just as local area networks underlie classical datacenters and supercomputers today.
Scalable quantum computing requires architectural solutions beyond monolithic processors. Distributed quantum computing (DQC) addresses this challenge by interconnecting smaller quantum nodes through quantum communication protocols, enabling collaborative computation. While several experimental and theoretical proposals for DQC exist, emulator platforms are essential tools for exploring their feasibility under realistic conditions. In this work, we introduce a benchmarking framework to evaluate DQC emulators using a distributed implementation of the inverse Quantum Fourier Transform (QFT†) as a representative test case, which enables efficient phase recovery from pre-encoded Fourier states. The QFT is partitioned across nodes using teleportation-based protocols, and performance is analyzed in terms of execution time, memory usage, and fidelity with respect to a monolithic baseline.
As part of this work, we review a broad range of emulators, identifying their capabilities and limitations for programming distributed quantum algorithms. Many platforms either lacked support for teleportation protocols or required complex workarounds. Consequently, we select and benchmark four representative emulators: Qiskit Aer, SquidASM, Interlin-q, and SQUANCH. They differ significantly in their support for discrete-event simulation, quantum networking, noise modeling, and parallel execution. Our results highlight the trade-offs between architectural fidelity and simulation scalability, providing a foundation for future emulator development and the validation of distributed quantum protocols. This framework can be extended to support additional algorithms and emulators.
Abstract: This study investigates photonic-interconnected quantum chiplets as a modular hardware pathway for scalable and networked quantum computing. The central problem is that monolithic quantum processors face compounding constraints in yield, wiring density, cryogenic routing, interconnect loss, calibration complexity and non-local connectivity. Photonic interconnection offers a technically plausible route to divide a large quantum computer into smaller processors while preserving quantum communication across modules through fibre links, photonic switches, optical transduction or integrated photonic interposers. The paper develops an academically rigorous framework that connects quantum-chiplet architecture, photonic integration, quantum error correction, control latency and manufacturability. It uses secondary real-data anchors from recent public demonstrations and a transparent engineering analysis to evaluate whether modular photonic networking can satisfy requirements for distributed logical qubits, entanglement generation and fault-tolerant operation. Results indicate that photonic chiplets can reduce scaling penalties relative to a monolithic wiring strategy when interconnect loss, feed-forward latency and module yield are jointly optimized. The study concludes that photonic-interconnected chiplets are not a minor packaging improvement but a possible architectural transition comparable to the movement from single-die classical processors to heterogeneous chiplet systems. The strongest contribution is a system-level evaluation model that links physical photonic performance with computer-architecture metrics and identifies the practical thresholds that must be met for Nature-level experimental validation. Keywords quantum computing chips, photonic chiplets, modular quantum computing, quantum interconnects, distributed quantum processors, silicon photonics, quantum networking, fault-tolerant quantum computing, optical interposers, quantum error correction, entanglement routing, wafer-scale quantum manufacturing, cryogenic control, quantum architecture, quantum hardware scalability
Quantum computers in the noisy intermediate-scale quantum (NISQ) era are constrained by limited qubit counts, imperfect gate fidelities, and short coherence times. NISQ-era computers often have too few qubits to run many algorithms, and those that do run often have limited quantum advantage. Distributed quantum computing (DQC) is a promising approach to overcome this, where multiple quantum processors are interconnected through shared entanglement. This work serves as a system overview of an entanglement distribution system. We achieve this by examining a zero-added loss multiplexing (ZALM) entanglement generation source, simulating multi-hop, repeater-less networks, and various routing algorithms to distribute entanglement, and real-hardware quantum experiments that reconstruct entanglement links of degraded fidelity and simulate classical-communication delay. Network simulations evaluate routing and spectrum-allocation algorithms under entanglement-generation-imposed rate constraints, by evaluating both fairness and throughput across network sizes and topologies. We identify two polynomial-time approximation algorithms that perform well, or better than others under these metrics. Using both simulations and quantum hardware, we evaluate how degraded entanglement and communication latency affect teleportation-based distributed multipartite-entanglement-state construction. The results reveal the coupled influence of source rate, routing efficiency, fidelity, and classical delay on networked entanglement distribution and DQC performance, providing a reproducible framework for both experimental and simulated studies of near-term DQC.