Constant-time hybrid compilation of Shor's algorithm with quantum just-in-time compilation

• URL: http://arxiv.org/abs/2504.12449v1
• Date: Wed, 16 Apr 2025 19:30:10 GMT
• Title: Constant-time hybrid compilation of Shor's algorithm with quantum just-in-time compilation
• Authors: David Ittah, Jackson Fraser, Josh Izaac, Olivia Di Matteo,
• Abstract summary: This work provides an implementation of Shor's factoring algorithm, compiled to elementary quantum gates using PennyLane and Catalyst.<n>We demonstrate that with QJIT compilation, the algorithm is compiled once per bit width of $N$, even when $N$-specific optimizations are applied to circuit generation.<n>The implementation is benchmarked up to 32-bit $N$, and both the size of the compiled program and the pure compilation time are found to be constant.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Continuous improvements in quantum computing hardware are exposing the need for simultaneous advances in software. Large-scale implementation of quantum algorithms requires rapid and automated compilation routines such as circuit synthesis and optimization. As systems move towards fault-tolerance, programming frameworks and compilers must also be capable of compiling and optimizing programs comprising both classical and quantum code. This work takes a step in that direction by providing an implementation of Shor's factoring algorithm, compiled to elementary quantum gates using PennyLane and Catalyst, a library for quantum just-in-time (QJIT) compilation of hybrid workflows. We demonstrate that with QJIT compilation, the algorithm is compiled once per bit width of $N$, the integer being factored, even when $N$-specific optimizations are applied to circuit generation based on values determined at runtime. The implementation is benchmarked up to 32-bit $N$, and both the size of the compiled program and the pure compilation time are found to be constant (under 3 seconds on a laptop computer), meaning code generation becomes tractable even for realistic problem sizes.

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