Analyzing Quantum Programs with LintQ: A Static Analysis Framework for Qiskit

As quantum computing is rising in popularity, the amount of quantum programsand the number of developers writing them are increasing rapidly.Unfortunately, writing correct quantum programs is challenging due to varioussubtle rules developers need to be aware of. Empirical studies show that 40-82of all bugs in quantum software are specific to the quantum domain. Yet,existing static bug detection frameworks are mostly unaware of quantum-specificconcepts, such as circuits, gates, and qubits, and hence miss many bugs. Thispaper presents LintQ, a comprehensive static analysis framework for detectingbugs in quantum programs. Our approach is enabled by a set of abstractionsdesigned to reason about common concepts in quantum computing without referringto the details of the underlying quantum computing platform. Built on top ofthese abstractions, LintQ offers an extensible set of ten analyses that detectlikely bugs, such as operating on corrupted quantum states, redundantmeasurements, and incorrect compositions of sub-circuits. We apply the approachto a newly collected dataset of 7,568 real-world Qiskit-based quantum programs,showing that LintQ effectively identifies various programming problems, with aprecision of 91.0analyses. Comparing to a general-purpose linter and two existing quantum-awaretechniques shows that almost all problems (92.1evaluation are missed by prior work. LintQ hence takes an important step towardreliable software in the growing field of quantum computing.