MorphQPV: Exploiting Isomorphism in Quantum Programs to Facilitate Confident Verification

Abstract

Unlike classical computing, quantum program verification (QPV) is much more challenging due to the non-duplicability of quantum states that collapse after measurement. Prior approaches rely on deductive verification that shows poor scalability. Or they require exhaustive assertions that cannot ensure the program is correct for all inputs. In this paper, we propose MorphQPV, a confident assertion-based verification methodology. Our key insight is to leverage the isomorphism in quantum programs, which implies a structure-preserve relation between the program runtime states. In the assertion statement, we define a tracepoint pragma to label the verified quantum state and an assume-guarantee primitive to specify the expected relation between states. Then, we characterize the ground-truth relation between states using an isomorphism-based approximation, which can effectively obtain the program states under various inputs while avoiding repeated executions. Finally, the verification is formulated as a constraint optimization problem with a confidence estimation model to enable rigorous analysis. Experiments suggest that MorphQPV reduces the number of program executions by $107.9\times$ when verifying the 27-qubit quantum lock algorithm and improves the probability of success by $3.3\times$-$9.9\times$ when debugging five benchmarks.

Publication
In ASPLOS 2024
Mingshuai Chen
Mingshuai Chen
ZJU100 Young Professor

My research interests include formal verification, programming theory, and logical aspects of computer science.