Quantum computers promise exponential speedups over classical computers for a specific set of problems, yet scaling quantum systems to the sizes required for practical applications remains a major challenge. Multi-chip architectures promise improved scalability and reduced per-chip complexity by interconnecting quantum processors via quantum links. The performance of these interconnects is a key factor determining overall system performance and, ultimately, the feasibility of modular quantum computing. This master's thesis investigates the modeling and analysis of link-layer protocols for multi-chip quantum computers. In this work, various protocols for communication and interaction between chips are modeled, including Teledata, Telegate, and entanglement swapping. The impact of different architectural decisions like the number of qubits per chip and the speed of the classical network on overall performance is analyzed using detailed timing models. The results show that the choice of architecture, network speed, and selected communication protocols have a significant impact on execution time. These findings provide important insights into the scalability of future quantum computing architectures.
Quantum computers promise exponential speedups over classical computers for a specific set of problems, yet scaling quantum systems to the sizes required for practical applications remains a major challenge. Multi-chip architectures promise improved scalability and reduced per-chip complexity by interconnecting quantum processors via quantum links. The performance of these interconnects is a key factor determining overall system performance and, ultimately, the feasibility of modular quantum computing. This master's thesis investigates the modeling and analysis of link-layer protocols for multi-chip quantum computers. In this work, various protocols for communication and interaction between chips are modeled, including Teledata, Telegate, and entanglement swapping. The impact of different architectural decisions like the number of qubits per chip and the speed of the classical network on overall performance is analyzed using detailed timing models. The results show that the choice of architecture, network speed, and selected communication protocols have a significant impact on execution time. These findings provide important insights into the scalability of future quantum computing architectures.
Modular architectures are a promising approach to scaling quantum computers beyond the limits of monolithic designs. However, non-local communications between different quantum processors might significantly impact overall system performance. In this work, we investigate the role of the network infrastructure in modular quantum computing architectures, focusing on coherence loss due to communication constraints. We analyze the impact of classical network latency on quantum teleportation and identify conditions under which it becomes a bottleneck. Additionally, we study different network topologies and assess how communication resources affect the number and parallelization of inter-core communications. Finally, we conduct a full-stack evaluation of the architecture under varying communication parameters, demonstrating how these factors influence the overall system performance. The results show that classical communication does not become a bottleneck for systems exceeding one million qubits, given current technology assumptions, even with modest clock frequencies and parallel wired interconnects. Additionally, increasing quantum communication resources generally shortens execution time, although it may introduce additional communication overhead. The optimal number of quantum links between QCores depends on both the algorithm being executed and the chosen inter-core topology. Our findings offer valuable guidance for designing modular architectures, enabling scalable quantum computing.
Modular quantum processor architectures are envisioned as a promising solution for the scalability of quantum computing systems beyond the Noisy Intermediate Scale Quantum (NISQ) era. Based upon interconnecting tens to hundreds of quantum processors (i.e cores) via quantum coherent and classical links, this approach unravels the pressing limitations of densely qubit-packed monolithic processors, mainly by mitigating the requirements of qubit control and enhancing qubit isolation. Therefore, this new architectural design enables executing large-scale algorithms in a distributed manner. In order to assess the performance and optimize such architectures, it is crucial to analyze the quantum state transfers occurring via inter-core communication networks, referred to as inter-core qubit traffic. This would provide insights to improve the software and hardware stack for multi-core quantum computers. To this aim, we present a characterization of the spatio-temporal inter-core qubit traffic for different large-scale quantum algorithms. The programs are compiled on an all-to-all connected multi-core architecture that supports up to around 1000 qubits. We characterize the qubit traffic based on multiple performance metrics to assess the computational process and the communication overhead. Based on the showcased results, we conclude on the parallelization and scalability of presented algorithms, qualitatively evaluate the resource requirements as we scale circuit sizes, and lay the foundations of application-oriented benchmarking of large-scale multi-core architectures.
Current monolithic quantum computer architectures have limited scalability. One promising approach for scaling them up is to use a modular or multi-core architecture, in which different quantum processors (cores) are connected via quantum and classical links. This new architectural design poses new challenges such as the expensive inter-core communication. To reduce these movements when executing a quantum algorithm, an efficient mapping technique is required. In this paper, a detailed critical discussion of the quantum circuit mapping problem for multi-core quantum computing architectures is provided. In addition, we further explore the performance of a mapping method, which is formulated as a partitioning over time graph problem, by performing an architectural scalability analysis.
The scalability of quantum computing is constrained by the physical and architectural limitations of monolithic quantum processors. Modular multi-core quantum architectures, which interconnect multiple quantum cores (QCs) via classical and quantum-coherent links, offer a promising alternative to address these challenges. However, transitioning to a modular architecture introduces communication overhead, where classical communication plays a crucial role in executing quantum algorithms by transmitting measurement outcomes and synchronizing operations across QCs. Understanding the impact of classical communication on execution time is therefore essential for optimizing system performance. In this work, we introduce qcomm , an open-source simulator designed to evaluate the role of classical communication in modular quantum computing architectures. qcomm provides a high-level execution and timing model that captures the interplay between quantum gate execution, entanglement distribution, teleportation protocols, and classical communication latency. We conduct an extensive experimental analysis to quantify the impact of classical communication bandwidth, interconnect types, and quantum circuit mapping strategies on overall execution time. Furthermore, we assess classical communication overhead when executing real quantum benchmarks mapped onto a cryogenically-controlled multi-core quantum system. Our results show that, while classical communication is generally not the dominant contributor to execution time, its impact becomes increasingly relevant in optimized scenarios—such as improved quantum technology, large-scale interconnects, or communication-aware circuit mappings. These findings provide useful insights for the design of scalable modular quantum architectures and highlight the importance of evaluating classical communication as a performance-limiting factor in future systems.
This thesis treats networks providing quantum computation based on distributed paradigms. Compared to architectures relying on one processor, a network promises to be more scalable and less fault-prone. Developing a distributed system able to provide practical quantum computation comes with many challenges, each of which need to be faced with careful analysis in order to create a massive integration of several components properly engineered. In accordance with hardware technologies, currently under construction around the globe, telegates represent the fundamental inter-processor operations. Each telegate consists of several tasks: i) entanglement generation and distribution, ii) local operations, and iii) classical communications. Entanglement generation and distribution is an expensive resource, as it is time-consuming. The main contribution of this thesis is on the definition of compilers that minimize the impact of telegates on the overall fidelity. Specifically, we give rigorous formulations of the subject problem, allowing us to identify the inter-dependence between computation and communication. With the support of some of the best tools for reasoning -- i.e. network optimization, circuit manipulation, group theory and ZX-calculus -- we found new perspectives on the way a distributed quantum computing system should evolve.
Practical fault-tolerant quantum computation requires a large number of physical qubits, posing a major challenge for scaling up individual quantum processors. Distributed architectures offer a promising solution by interconnecting multiple processors through quantum networks. However, remote Bell-pair generation remains technically demanding, making it essential to assess computational performance under limited communication resources. In this work, we present a comprehensive resource analysis of distributed fault-tolerant quantum computation using superconducting processors connected by microwave or optical links. We show that even a single physical communication channel per node can substantially reduce the physical-qubit requirements per node under experimentally motivated, forward-looking microwave-link assumptions of a 1 MHz physical Bell-pair generation rate and 90% fidelity, although at the cost of a roughly tenfold increase in execution time. Conversely, reducing the execution-time overhead requires substantially greater communication resources, including higher Bell-pair fidelities and extensive multiplexing. These results demonstrate the potential feasibility of distributed fault-tolerant quantum computation with limited communication resources and provide a quantitative basis for balancing quantum-link performance, processor size, and execution time.