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Quantum Machine Learning
QReach: A Reachability Analysis Tool for Quantum Markov Chains
arXiv
Authors: Aochu Dai, Mingsheng Ying
Year
2025
Paper ID
16212
Status
Preprint
Abstract Read
~2 min
Abstract Words
64
Citations
N/A
Abstract
We present QReach, the first reachability analysis tool for quantum Markov chains based on decision diagrams CFLOBDD (presented at CAV 2023). QReach provides a novel framework for finding reachable subspaces, as well as a series of model-checking subprocedures like image computation. Experiments indicate its practicality in verification of quantum circuits and algorithms. QReach is expected to play a central role in future quantum model checkers.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2025 reference point for readers tracking recent quantum research.
- We present QReach, the first reachability analysis tool for quantum Markov chains based on decision diagrams CFLOBDD (presented at CAV 2023).
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