With the increasing capabilities of quantum systems, the efficient, practical execution of quantum programs is becoming more critical. Each execution includes compilation time, which accounts for substantial overhead of the overall program runtime. To address this challenge, proposals that leverage precompilation techniques have emerged, whereby entire circuits or select components are precompiled to mitigate the compilation time spent during execution. Considering the impact of compilation time on quantum program execution, identifying the contribution of each individual compilation task to the execution time is necessary in directing the community’s research efforts towards the development of an efficient compilation and execution pipeline. In this work, we perform a preliminary analysis of the quantum circuit compilation process in Qiskit, examining the cumulative runtime of each individual compilation task and identifying the tasks that most strongly impact the overall compilation time. Our results indicate that, as the desired level of optimization increases, circuit optimization and gate synthesis passes become the dominant tasks in compiling a Quantum Fourier Transform, with individual passes consuming up to 87% of the total compilation time. Mapping passes require the most compilation time for a GHZ state preparation circuit, accounting for over 99% of total compilation time.
With the increasing capabilities of quantum systems, the efficient, practical execution of quantum programs is becoming more critical. Each execution includes compilation time, which accounts for substantial overhead of the overall program runtime. To address this challenge, proposals that leverage precompilation techniques have emerged, whereby entire circuits or select components are precompiled to mitigate the compilation time spent during execution. Considering the impact of compilation time on quantum program execution, identifying the contribution of each individual compilation task to the execution time is necessary in directing the community’s research efforts towards the development of an efficient compilation and execution pipeline. In this work, we perform a preliminary analysis of the quantum circuit compilation process in Qiskit, examining the cumulative runtime of each individual compilation task and identifying the tasks that most strongly impact the overall compilation time. Our results indicate that, as the desired level of optimization increases, circuit optimization and gate synthesis passes become the dominant tasks in compiling a Quantum Fourier Transform, with individual passes consuming up to 87% of the total compilation time. Mapping passes require the most compilation time for a GHZ state preparation circuit, accounting for over 99% of total compilation time.
The recent times of fast development of quantum computers has been followed by many researchers who want to run the larger and more difficult quantum algorithms on it and they have promised such speedup several times. Notwithstanding this, commercial quantum computers are currently fraught with instability and errors. This paper is centered on development of the customized compiler for quantum computing with aid of Qiskit Terra, a QIS framework. We target central classes such as circuit representation structures, programming techniques based on OpenQASM, challenges in the QC architecture, high-level routing optimization, and the structure of the Qiskit Terra compiler. In every circuit, the optimization is provided by methods of Qiskit Terra, including Trivial Layout, Noise Adaptive Layout, Dense Layout, and Custom Layout. These optimization levels address many problems that emerge when circuits are being compiled and executed, and thus, the optimization levels seek to boost circuit efficiency, reduce the count of gates, and enhance the overall performance. The introduction of numerous optimization passes starting from unroller passes that translate gates, the layout passes that map virtual to physical qubits, and the optimization algorithm aimed at the runtime reduction. Modern quantum compilation technologies are being currently developed based on economic (and theoretical) analyses to underpin the investigation and development of optimal quantum computation procedures.
Quantum computing has the potential to outperform classical computing in specific problem domains, but current systems rely heavily on classical resources for tasks such as quantum circuit compilation. As quantum hardware scales, the energy consumption of these supporting classical processes becomes increasingly important. This thesis investigates the energy consumption of quantum circuit compilation by analyzing existing literature and benchmarking results for different quantum software frameworks. The study focuses on comparing the performance of widely used quantum compilers. Energy consumption is estimated based on processor power models and execution time. Benchmark data from multiplier and quantum Fourier transform circuits are used to evaluate how compiler performance scales with increasing qubit counts and different hardware connectivity constraints. The results show that no single compiler is optimal for all tasks, but significant differences exist in runtime and energy efficiency. Compilers with better scalability, such as Qiskit in many cases, tend to consume less energy for larger circuits, while others exhibit rapidly increasing costs. Additionally, restricted hardware connectivity increases compilation time and energy consumption across most frameworks. The thesis concludes that energy consumption is an important, but unexplored aspect of quantum circuit compilation. As quantum systems grow in size, the classical overhead of compilation may become a limiting factor. Future work should focus on direct measurement of energy consumption and the development of energy-aware compilation techniques.
Similar to classical programming, high-level quantum programming languages generate code that cannot be executed directly by quantum hardware and must be compiled. However, unlike classical code, quantum programs must be compiled before each execution, making the trade-off between compilation time and execution time particularly significant. In this paper, we address the first step of quantum compilation: multi-qubit gate decomposition. We analyze the trade-offs of state-of-the-art decomposition algorithms by implementing them in the Ket quantum programming platform and collecting numerical performance data. This is the first study to both implement and analyze the current state-of-the-art decomposition methods within a single platform. Based on our findings, we propose two compilation profiles: one optimized for minimizing compilation time and another for minimizing quantum execution time. Our results provide valuable insights for both quantum compiler developers and quantum programmers, helping them make informed decisions about gate decomposition strategies and their impact on overall performance.
Quantum circuit optimization is critical for mitigating the noise inherent in current quantum hardware. Quantum compilers typically sequentially apply multiple optimizations (also called ``optimization passes'') to improve the circuit. The impact of the order in which these passes are executed has yet been largely unexplored. This paper investigates the significance of the order of optimization passes within quantum circuit compilation, specifically analyzing interactions between different optimization methods and quantifying their mutual influences. Using Qiskit's compiler, we systematically evaluate pairwise combinations of 16 selected optimization passes, measuring circuit depth and gate count across various benchmark circuits. Our findings indicate dependencies between certain optimization passes, demonstrating that the order of the passes affects the optimization quality. In some cases, the worse performing sequence can be corrected through repeated pass application. %such that they are as good as the best performing one by extending the sequence. Experiments on multi-pass sequences show that more than two optimization passes may have an impact on each other but that this always links to the previously found pairwise effects. We observe that it is important to initially choose the best order of optimization passes to get the best possible optimization for the given circuit. The experiments reveal some factors which are important to choose the best, or at least a good, order; among those, the resulting optimization sequence depends the most on the native gate set.
Quantum compilation is a multi-pass process that translates a high-level circuit into an equivalent one executable on quantum hardware. A critical stage in this process is mapping, where additional gates are inserted to satisfy hardware constraints. Current mapping techniques often suffer from significant performance degradation—in terms of added gate count, increased circuit depth, and longer compilation times that scale with circuit size. In this work, we propose a novel methodology that enhances quantum compilation by leveraging concepts from Electronic Design Automation. Our approach partitions a quantum circuit into sub-circuits that can be compiled independently, and reformulates the mapping problem as a temporal floorplanning instance—a well-established technique in classical circuit design. We validate our method on widely used quantum circuit benchmark suites, achieving an average depth reduction of 22.05 % compared to traditional monolithic compilation chains using IBM Qiskit. Moreover, our approach reduces overall compilation time to that required for compiling the largest partition, while our partitioning-floorplanning algorithm runs, on average, two orders of magnitude faster than compiling the full circuit.
Realizing a conceptual quantum algorithm on an actual physical device necessitates the algorithm's quantum circuit description to undergo certain transformations in order to adhere to all constraints imposed by the hardware. In this regard, the individual high-level circuit components are first synthesized to the supported low-level gate-set of the quantum computer, before being mapped to the target's architecture-utilizing several optimizations in order to improve the compilation result. Specialized tools for this complex task exist, e.g., IBM's Qiskit, Google's Cirq, Microsoft's QDK, or Rigetti's Forest. However, to date, the circuits resulting from these tools are hardly verified, which is mainly due to the immense complexity of checking if two quantum circuits indeed realize the same functionality. In this paper, we propose an efficient scheme for quantum circuit equivalence checking-specialized for verifying results of the IBM Qiskit quantum circuit compilation flow. To this end, we combine characteristics unique to quantum computing, e.g., its inherent reversibility, and certain knowledge about the compilation flow into a dedicated equivalence checking strategy. Experimental evaluations confirm that the proposed scheme allows to verify even large circuit instances with tens of thousands of operations within seconds or even less, whereas state-of-the-art techniques frequently time-out or require substantially more runtime. A corresponding open source implementation of the proposed method is publicly available at https://github.com/iic-jku/qcec.