In this survey, there is a systematic assessment of the existing plans of manufacturing Quantum.Their ability to make Intermediate Representations (QIRs) sell optimization solutions to problems, plasticity in the both hardware and verification.We survey the existent methodologies and identify them in four waves, i.e. language-derived paradigm, multi-level paradigm, classically-quantum and hybrid classicalquantum paradigm and hybrid formally verified and verify their performance in some major parameters, i.e., circuit depth reduction, compilation transversal and cross-operating system portability.We find that the optimal compromise of performance and reliability is realised on hybrid systems that combine classical Compiler with extensions supporting quantum, in which current tools (note that we are not exist and future designs, which implement quantum provide technology at the center of the research significant enhancement of optimization ability and black box testing of the verification suite.Nevertheless, essential there are problems within the development of the new quantum paradigms supporter, temporal optimization and error correction incorporation.An outlook is provided at the end of the paper on the creation of next generation QIR with a special emphasis on the need to have verifiable, quantifiable frameworks that maintain optimization at the various levels transparent.This paper can be used as are source on both the technical community designing quantum compilers in addition to a roadmap that researchers should pursue in this various area of QIR.
In this survey, there is a systematic assessment of the existing plans of manufacturing Quantum.Their ability to make Intermediate Representations (QIRs) sell optimization solutions to problems, plasticity in the both hardware and verification.We survey the existent methodologies and identify them in four waves, i.e. language-derived paradigm, multi-level paradigm, classically-quantum and hybrid classicalquantum paradigm and hybrid formally verified and verify their performance in some major parameters, i.e., circuit depth reduction, compilation transversal and cross-operating system portability.We find that the optimal compromise of performance and reliability is realised on hybrid systems that combine classical Compiler with extensions supporting quantum, in which current tools (note that we are not exist and future designs, which implement quantum provide technology at the center of the research significant enhancement of optimization ability and black box testing of the verification suite.Nevertheless, essential there are problems within the development of the new quantum paradigms supporter, temporal optimization and error correction incorporation.An outlook is provided at the end of the paper on the creation of next generation QIR with a special emphasis on the need to have verifiable, quantifiable frameworks that maintain optimization at the various levels transparent.This paper can be used as are source on both the technical community designing quantum compilers in addition to a roadmap that researchers should pursue in this various area of QIR.
Quantum Intermediate Representation (QIR) is a Microsoft-developed, LLVM-based intermediate representation for quantum program compilers. QIR aims to provide a general solution for quantum program compilers independent of front-end languages and back-end hardware, thus avoiding duplicate development of intermediate representations and compilers. Since it is still under development, QIR is described in natural language and lacks a formal definition, leading to ambiguity in its interpretation and a lack of rigor in implementing quantum functions. In this paper, we provide formal definitions for the data types and instruction sets of QIR, aiming to provide correctness and security guarantees for operations and intermediate code conversions in QIR. To validate our design, we show some samples of unsafe QIR code where errors can be detected by our formal approach.
Quantum Intermediate Representation (QIR) is an LLVM-based intermediate representation developed by Microsoft for quantum program compilers. QIR is designed to offer a universal solution for quantum program compilers, decoupled from both front-end languages and back-end hardware, thereby eliminating the need for redundant development of intermediate representations and compilers. However, the lack of a formal definition and reliance on natural language descriptions in the current state of QIR result in interpretational ambiguity and a dearth of rigor in implementing quantum functions. In this paper, we present formal definitions for QIR's data types and instruction sets to establish correctness and safety assurances for operations and intermediate code conversions within QIR. To demonstrate the effectiveness of our approach, we provide examples of unsafe QIR codes where errors can be identified with our method.
Intermediate representations (IRs) play a crucial role in the software stack of a quantum computer to facilitate efficient optimizations for executing an application on hardware. One of those IRs is the Quantum Intermediate Representation (QIR), which builds on the classical LLVM compiler infrastructure. In this article, we outline different approaches to how QIR can be adopted. This exploration culminates in a demonstration of what it takes to turn an existing quantum circuit simulator into a QIR runtime and that such a transition is less daunting than it might seem at first. We further show that switching to QIR does not entail any performance deficits compared to the original simulator. On the contrary, the presented steps effortlessly allow adding support for arbitrary classical control flow to any classical simulator. We conclude with an outlook on future directions using QIR. The implemented QIR runtime is available under https://github.com/munich-quantum-toolkit/core.
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.
Quantum computing holds transformative potential, but its adoption is hindered by the complexity of generating efficient, hardware-specific code. This work presents a modular, extensible compiler framework that bridges high-level quantum languages with diverse hardware architectures. The framework consists of three modules: a front-end for parsing quantum code into a hardware-agnostic intermediate representation (IR), an optimization module for enhancing quantum circuits through gate synthesis, qubit routing, and error mitigation, and a back-end for generating hardware-specific instructions. Major contributions include a hardware-agnostic IR for cross-platform compatibility, optimization techniques to reduce gate complexity and noise, and hardware-specific adaptations to improve execution fidelity. A practical demonstration optimizes quantum circuits, highlighting the impact of hardware constraints. Comparative analysis of IBM Quantum and IonQ platforms underscores the role of qubit connectivity and noise resilience in algorithmic performance. This scalable framework enhances quantum software development and efficient hardware utilization.
This research paper provides an in-depth examination of verification and testing approaches for quantum circuits, focusing on methodologies essential for ensuring the correctness, reliability and operational efficiency of quantum computing systems. Since quantum circuits function on the fundamental principles of superposition and entanglement, they present verification challenges that cannot be effectively addressed using conventional classical testing techniques. As a result, the development of specialized quantum-specific verification strategies has become critically important. The study highlights simulation-based verification as a foundational technique, wherein the outcomes of quantum circuit simulations are systematically compared with results obtained from physical quantum hardware. This process enables the identification of functional inconsistencies and supports iterative refinement of circuit designs. In addition, randomized benchmarking is examined as a key evaluation method for estimating circuit fidelity and quantifying error rates through the application of random gate sequences and performance comparisons against established benchmarks. To further improve system robustness, the research investigates fault-tolerant mechanisms, particularly quantum error correction codes, which play a vital role in minimizing the effects of noise, decoherence and hardware imperfections. The integration of advanced quantum metrology and characterization techniques is also explored, enabling precise measurement and detailed analysis of quantum system behavior. These techniques provide deeper insights into circuit performance and contribute significantly to validation processes. By combining simulation-based verification, randomized benchmarking, fault-tolerant protocols and quantum metrology, this study proposes a comprehensive and reliable framework for quantum circuit verification and testing. The findings contribute to the advancement of dependable quantum technologies and support their growing applications in areas such as cryptography, materials science and other emerging domains.