Abstract Quantum computing is a rapidly evolving field, with almost every aspect open to change or improvement. This includes moving from using a single quantum processing unit to interconnecting multiple quantum processing units (or several of them), establishing a new paradigm called distributed quantum computing and increasing the overall computing capability. Some research is already underway in this area to prepare the ground for an eventual architecture with these characteristics. This is the case of InQuIR (Nishio and Wakizaka in arXiv:2302.00267 2023) and NetQASM (Dahlberg et al in QST 7:035023 2022), two languages developed for distributed quantum computing. This paper presents the development of the InQASM compiler with the aim of translating code from the InQuIR language to NetQASM, establishing a compilation stack for the new distributed paradigm. An example of this compilation and a simulation of the compiled code are shown to showcase it.
Abstract Quantum computing is a rapidly evolving field, with almost every aspect open to change or improvement. This includes moving from using a single quantum processing unit to interconnecting multiple quantum processing units (or several of them), establishing a new paradigm called distributed quantum computing and increasing the overall computing capability. Some research is already underway in this area to prepare the ground for an eventual architecture with these characteristics. This is the case of InQuIR (Nishio and Wakizaka in arXiv:2302.00267 2023) and NetQASM (Dahlberg et al in QST 7:035023 2022), two languages developed for distributed quantum computing. This paper presents the development of the InQASM compiler with the aim of translating code from the InQuIR language to NetQASM, establishing a compilation stack for the new distributed paradigm. An example of this compilation and a simulation of the compiled code are shown to showcase it.
Various physical constraints limit the number of qubits that can be implemented in a single quantum processor, and thus it is necessary to connect multiple quantum processors via quantum interconnects. While several compiler implementations for interconnected quantum computers have been proposed, there is no suitable representation as their compilation target. The lack of such representation impairs the reusability of compiled programs and makes it difficult to reason formally about the complicated behavior of distributed quantum programs. We propose InQuIR, an intermediate representation that can express communication and computation on distributed quantum systems. InQuIR has formal semantics that allows us to describe precisely the behaviors of distributed quantum programs. We give examples written in InQuIR to illustrate the problems arising in distributed programs, such as deadlock. We present a roadmap for static verification using type systems to deal with such a problem. We also provide software tools for InQuIR and evaluate the computational costs of quantum circuits under various conditions. Our tools are available at https://github.com/team-InQuIR/InQuIR.
Abstract Intermediate representations (IRs) are fundamental to classical and quantum computing, bridging high-level quantum programming languages and the hardware-specific instructions required for execution. This paper reviews the development of quantum IRs, focusing on their evolution and the need for abstraction layers that facilitate portability and optimization. Monolithic quantum IRs, such as QIR (Lubinski et al. in Front Phys 10:940293, 2022. https://doi.org/10.3389/fphy.2022.940293), QSSA (Peduri et al. in Proceedings of the 31st ACM SIGPLAN international conference on compiler construction. CC 2022. Association for Computing Machinery, New York, 2022), or Q-MLIR (McCaskey and Nguyen in Proceedings-2021 IEEE International Conference on Quantum Computing and Engineering, QCE, 2021), their effectiveness in handling abstractions, and their hybrid support between quantum-classical operations are evaluated. However, a key limitation is their inability to address qubit locality, an essential feature for distributed quantum computing (DQC). To overcome this, InQuIR (Nishio and Wakizaka in InQuIR: Intermediate Representation for Interconnected Quantum Computers, 2023. https://arxiv.org/abs/2302.00267) was introduced as an IR specifically designed for distributed systems, providing explicit control over qubit locality and inter-node communication. While effective in managing qubit distribution, InQuIR’s dependence on manual manipulation of communication protocols increases complexity for developers. NetQIR (Vázquez-Pérez et al. in NetQIR: An Extension of QIR for Distributed Quantum Computing, 2024. https://arxiv.org/abs/2408.03712), an extension of QIR for DQC, emerges as a solution to achieve the abstraction of quantum communications protocols. This review emphasizes the need for further advancements in IRs for distributed quantum systems, which will play a crucial role in the scalability and usability of future quantum networks.
The rapid advancement of quantum computing has highlighted the need for scalable and efficient software infrastructures to fully exploit its potential. Current quantum processors face significant scalability constraints due to the limited number of qubits per chip. In response, distributed quantum computing (DQC) —achieved by networking multiple quantum processor units (QPUs)— is emerging as a promising solution. To support this paradigm, robust intermediate representations (IRs) are needed to translate high-level quantum algorithms into executable instructions suitable for distributed systems. This paper presents NetQIR, an extension of Microsoft’s Quantum Intermediate Representation (QIR), specifically designed to facilitate DQC by incorporating new instruction specifications. NetQIR was developed in response to the lack of abstraction at the network and hardware layers identified in the existing literature as a significant obstacle to effectively implementing distributed quantum algorithms. Based on this analysis, NetQIR introduces new essential abstraction features to support compilers in DQC contexts. It defines network communication instructions independent of specific hardware, abstracting the complexities of inter-QPU communication. Although the proposed work allows abstraction of the underlying network, it is important to note that it is intended for the development of high-performance code on future modular quantum architectures. Leveraging the QIR framework, NetQIR aims to bridge the gap between high-level quantum algorithm design and low-level hardware execution, thus promoting modular and scalable approaches to quantum software infrastructures for distributed applications. Furthermore, its design may serve as a foundational component for future implementations of distributed quantum standards such as the Quantum Message Passing Interface (QMPI).
Distributed quantum computing (DQC) is emerging as a practical solution to overcome the scalability limits of individual quantum processors by interconnecting them via quantum networks. However, programming such systems remains a significant challenge due to the need to coordinate quantum operations, manage entanglement, and synchronize classical communication. This paper proposes NetQMPI as a Python library that enables high-level programming of distributed quantum applications by building on top of two key foundations: NetQASM, which abstracts the physical network layer to interface with quantum nodes and simulators such as NetSquid and SimulaQron; and NetQIR, which proposes a layered abstraction model suitable for defining a quantum version of the classical Message Passing Interface (MPI). NetQMPI provides an MPI-style programming model tailored to quantum systems. It introduces primitives such as qsend and qrecv that abstract quantum communication details like entanglement generation, and protocols. Collective operations such as qscatter or qgather are also included. This allows developers to focus on distributed algorithm design while relying on NetQMPI to handle low-level operations efficiently.
Quantum computing is a promising paradigm for problems that are challenging for classical machines, but realizing that promise requires far more qubits than a single processor can offer. Distributed quantum computing (DQC) scales out by connecting multiple quantum processing units (QPUs), at the cost of making entanglement the scarce resource: every remote gate consumes a Bell pair, and inter-QPU links generate Bell pairs at finite rates orders of magnitude slower than local gates. Since quantum programs are executed repeatedly, this rate bounds how fast shots complete and thus how fast results are obtained. Existing DQC compilers emit a single implementation per circuit, so throughput is capped by its busiest link while other links stay idle. We observe that alternative compilations of the same circuit are logically equivalent yet stress different links; executing them concurrently and pooling their samples converts idle Bell pairs into additional shots. We formulate the joint selection of compilations and allocation of shots under per-link Bell-pair capacities as Candidate-Constrained Max-Shot Allocation (CMA), prove it NP-hard, and solve it with a dynamic program and its approximate variant AppDP, a compact MILP, and a greedy heuristic Effi. In simulation on six-QPU networks, multi-compilation raises throughput by 2-4.5* over the single compilation and correspondingly improves output fidelity under equal Bell-pair budgets. On hardware, it increases measured fidelity by up to 93% and reaches the single-compilation fidelity in up to 10* less time. Scaling to 36 QPUs and 144-qubit circuits, MILP improves throughput over the single compilation by 76.8% on average across 48 configurations while Effi allocates in milliseconds.
In distributed quantum computing architectures, with the network and communications functionalities provided by the Quantum Internet, remote quantum processing units can communicate and cooperate for executing computational tasks that single, noisy, intermediate-scale quantum devices cannot handle by themselves. To this aim, distributed quantum computing requires a new generation of quantum compilers, for mapping any quantum algorithm to any distributed quantum computing architecture. With this perspective, in this article, we first discuss the main challenges arising with compiler design for distributed quantum computing. Then, we analytically derive an upper bound of the overhead induced by quantum compilation for distributed quantum computing. The derived bound accounts for the overhead induced by the underlying computing architecture as well as the additional overhead induced by the suboptimal quantum compiler-expressly designed in this article to achieve three key features, namely, general-purpose, efficient, and effective. Finally, we validate the analytical results, and we confirm the validity of the compiler design through an extensive performance analysis.