Towards High-Level Synthesis of Quantum Circuits

In recent years, there has been a proliferation of quantum algorithms, primarily due to their exponential speedup over their classical counterparts. Quantum algorithms find applications in various domains, including machine learning, molecular simulation, and cryptography. However, extensive knowledge of linear algebra and quantum mechanics are required to program a quantum computer, which might not be feasible for traditional software programmers. Moreover, current quantum programming paradigm is difficult to scale and integrate quantum circuits to achieve complex functionality. To this end, in this paper, we introduce QHLS, a quantum high-level synthesis (HLS) framework. To the best of our knowledge, this is the first HLS framework for quantum circuits. The proposed QHLS allows quantum programmers to start with high-level behavioral descriptions (e.g., C, C++) and automatically generate the corresponding quantum circuit; thus, reducing the complexity of programming a quantum computer. Our experimental results demonstrate the success of QHLS in translating high-level behavioral software programs containing arithmetic, logical, and conditional statements.

Automated summary

In recent years, there has been a rise in the number of quantum algorithms, which offer exponential speedup compared to classical algorithms. Quantum algorithms have applications in machine learning, molecular simulation, and cryptography. However, programming a quantum computer requires extensive knowledge of linear algebra and quantum mechanics, which may be challenging for traditional software programmers. Additionally, the current quantum programming paradigm lacks scalability and integration of quantum circuits for complex functionality. This paper introduces QHLS, the first quantum high-level synthesis (HLS) framework, which allows quantum programmers to start with high-level behavioral descriptions and automatically generate corresponding quantum circuits, reducing the complexity of quantum computer programming. Experimental results demonstrate the success of QHLS in translating high-level behavioral software programs containing arithmetic, logical, and conditional statements.