Shaking Up Quantum Simulators with Fuzzing and Rigour
This program is tentative and subject to change.
Quantum computing platforms rely on simulators for modelling circuit behaviour prior to hardware execution, where inconsistencies can lead to costly errors. While existing formal validation methods typically target specific compiler components to manage state explosion, they often miss critical bugs. Meanwhile, conventional testing lacks systematic exploration of corner cases and realistic execution scenarios, resulting in both false positives and negatives.
We present \toolname, a novel framework that bridges this gap by combining formal methods with structured test generation and fuzzing for quantum simulators. Our approach employs differential benchmarking complemented by mutation testing and invariant checking. At its core, \toolname{} utilises our Alloy-based formal model of QASM 3.0, which encodes the semantics of quantum circuits to enable automated analysis and to generate structurally diverse, constraint-guided quantum circuits with guaranteed properties. We introduce several test oracles to assess both Alloy’s modelling of QASM 3.0 and simulator correctness, including invariant-based checks, statistical distribution tests, and a novel cross-simulator unitary consistency check that verifies functional equivalence modulo global phase, revealing discrepancies that standard statevector comparisons fail to detect in cross-platform differential testing.
We evaluate \toolname{} on both Qiskit and Cirq, demonstrating its platform-agnostic effectiveness. By executing over 800,000 quantum circuits to completion, we assess throughput, code and circuit coverage, and simulator performance metrics, including sensitivity, correctness, and memory overhead. Our analysis revealed eight simulator bugs, six previously undocumented. We also outline a path for extending the framework to support mixed-state simulations under realistic noise models.
This program is tentative and subject to change.
Sat 18 OctDisplayed time zone: Perth change
10:30 - 12:15 | |||
10:30 15mTalk | AccelerQ: Accelerating Quantum Eigensolvers With Machine Learning on Quantum Simulators OOPSLA Avner Bensoussan King's College London, Elena Chachkarova Kings College London, Karine Even-Mendoza King’s College London, Sophie Fortz King's College London, Connor Lenihan King's College London | ||
10:45 15mTalk | A Language for Quantifying Quantum Network Behavior OOPSLA Anita Buckley USI Lugano, Pavel Chuprikov Télécom Paris, Institut Polytechnique de Paris, Rodrigo Otoni USI Lugano, Robert Soulé Yale University, Robert Rand University of Chicago, Patrick Eugster USI Lugano, Switzerland | ||
11:00 15mTalk | Compositional Quantum Control Flow with Efficient Compilation in Qunity OOPSLA Mikhail Mints California Institute of Technology, Finn Voichick University of Maryland, Leonidas Lampropoulos University of Maryland, College Park, Robert Rand University of Chicago | ||
11:15 15mTalk | Dependency-Aware Compilation for Surface Code Quantum Architectures OOPSLA Abtin Molavi University of Wisconsin-Madison, Amanda Xu University of Wisconsin-Madison, Swamit Tannu University of Wisconsin-Madison, Aws Albarghouthi University of Wisconsin-Madison | ||
11:30 15mTalk | QbC: Quantum Correctness by Construction OOPSLA | ||
11:45 15mTalk | qblaze: An Efficient and Scalable Sparse Quantum Simulator OOPSLA Hristo Venev INSAIT, Sofia University "St. Kliment Ohridski", Thien Udomsrirungruang University of Oxford, Dimitar Dimitrov INSAIT, Sofia University "St. Kliment Ohridski", Timon Gehr ETH Zurich, Martin Vechev ETH Zurich | ||
12:00 15mTalk | Shaking Up Quantum Simulators with Fuzzing and Rigour OOPSLA Vasileios Klimis Queen Mary University of London, Karine Even-Mendoza King’s College London, Avner Bensoussan King's College London, Elena Chachkarova Kings College London, Sophie Fortz King's College London, Connor Lenihan King's College London |