A Software Methodology for Compiling Quantum Programs
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Abstract (arXiv)
Quantum computers promise to transform our notions of computation by offering a completely new paradigm. To achieve scalable quantum computation, optimizing compilers and a corresponding software design flow will be essential. We present a software architecture for compiling quantum programs from a high-level language program to hardware-specific instructions. We describe the necessary layers of abstraction and their differences and similarities to classical layers of a computer-aided design flow. For each layer of the stack, we discuss the underlying methods for compilation and optimization. Our software methodology facilitates more rapid innovation among quantum algorithm designers, quantum hardware engineers, and experimentalists. It enables scalable compilation of complex quantum algorithms and can be targeted to any specific quantum hardware implementation.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Apr 2016.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 1.
5 papers.
- 2021Theory of overparametrization in quantum neural networkscited by 100
- 2022Theory for Equivariant Quantum Neural Networkscited by 60
- 2021Variational quantum compiling with double Q-learningcited by 13
- 2022Quantum compiling with a variational instruction set for accurate and fast quantum computingcited by 3
- 2023Q-fid: Quantum Circuit Fidelity Improvement with LSTM Networkscited by 1
- 2023Q-fid: Quantum Circuit Fidelity Improvement with LSTM Networks30 Mar 2023
- 2022Theory for Equivariant Quantum Neural Networks16 Oct 2022
- 2022Quantum compiling with a variational instruction set for accurate and fast quantum computing29 Mar 2022
- 2021Theory of overparametrization in quantum neural networks23 Sep 2021
- 2021Variational quantum compiling with double Q-learning22 Mar 2021