OpenQL : A Portable Quantum Programming Framework for Quantum Accelerators
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Abstract (arXiv)
With the potential of quantum algorithms to solve intractable classical problems, quantum computing is rapidly evolving and more algorithms are being developed and optimized. Expressing these quantum algorithms using a high-level language and making them executable on a quantum processor while abstracting away hardware details is a challenging task. Firstly, a quantum programming language should provide an intuitive programming interface to describe those algorithms. Then a compiler has to transform the program into a quantum circuit, optimize it and map it to the target quantum processor respecting the hardware constraints such as the supported quantum operations, the qubit connectivity, and the control electronics limitations. In this paper, we propose a quantum programming framework named OpenQL, which includes a high-level quantum programming language and its associated quantum compiler. We present the programming interface of OpenQL, we describe the different layers of the compiler and how we can provide portability over different qubit technologies. Our experiments show that OpenQL allows the execution of the same high-level algorithm on two different qubit technologies, namely superconducting qubits and Si-Spin qubits. Besides the executable code, OpenQL also produces an intermediate quantum assembly code (cQASM), which is technology-independent and can be simulated using the QX simulator.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 27 May 2020.
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Citing papers per year: 2023: 1; 2024: 2; 2025: 1.
4 papers.
- 2025QAgent: An LLM-based Multi-Agent System for Autonomous OpenQASM programmingcited by 11
- 2023qgym: A Gym for Training and Benchmarking RL-Based Quantum Compilationcited by 5
- 2024Surrogate-guided optimization in quantum networkscited by 1
- 2024Profiling quantum circuits for their efficient execution on single- and multi-core architecturescited by 0
- 2025QAgent: An LLM-based Multi-Agent System for Autonomous OpenQASM programming26 Aug 2025
- 2024Surrogate-guided optimization in quantum networks24 Jul 2024
- 2024Profiling quantum circuits for their efficient execution on single- and multi-core architectures17 Jul 2024
- 2023qgym: A Gym for Training and Benchmarking RL-Based Quantum Compilation1 Aug 2023