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Manjushri: A Tool for Equivalence Checking of Quantum Circuits

arXiv Quantum Physics
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⚡ Quantum Brief
Researchers introduced a new tool for verifying quantum-circuit equivalence using local projections and weighted binary decision diagrams (WBDDs), enabling compact symbolic representation of quantum behavior. The tool outperforms existing solutions like ECMC by 8–10× in speed for circuits up to depth 30, with performance gains varying by qubit count and equivalence status. Experimental tests on random 1D Clifford+T circuits show near-uniform success for depths up to 38, though accuracy drops to 75% at depth 50 and 0% at depth 48 for 128-qubit equivalent circuits. ECMC excels on 32- and 64-qubit circuits up to depth 50 but struggles with 128-qubit cases, highlighting scalability limitations compared to the new framework. This advancement positions the tool as a preferred choice for large-scale quantum-circuit verification unless circuits exceed depth 38.
Manjushri: A Tool for Equivalence Checking of Quantum Circuits

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Quantum Physics arXiv:2601.22372 (quant-ph) [Submitted on 29 Jan 2026] Title:Manjushri: A Tool for Equivalence Checking of Quantum Circuits Authors:Xuan Du Trinh, Meghana Sistla, Nengkun Yu, Thomas Reps View a PDF of the paper titled Manjushri: A Tool for Equivalence Checking of Quantum Circuits, by Xuan Du Trinh and 3 other authors View PDF HTML (experimental) Abstract:Verifying whether two quantum circuits are equivalent is a central challenge in the compilation and optimization of quantum programs. We introduce \textsc{Manjushri}, a new automated framework for scalable quantum-circuit equivalence checking. \textsc{Manjushri} uses local projections as discriminative circuit fingerprints, implemented with weighted binary decision diagrams (WBDDs), yielding a compact and efficient symbolic representation of quantum behavior. We present an extensive experimental evaluation that, for random 1D Clifford+$T$ circuits, explores the trade-off between \textsc{Manjushri} and \textsc{ECMC}, a tool for equivalence checking based on a much different approach. \textsc{Manjushri} is much faster up to depth 30 (with the crossover point varying from 39--49, depending on the number of qubits and whether the input circuits are equivalent or inequivalent): when inputs are equivalent, \textsc{Manjushri} is about 10$\times$ faster (or more); when inputs are inequivalent, \textsc{Manjushri} is about 8$\times$ faster (or more). For both kinds of equivalence-checking outcomes, \textsc{ECMC}'s success rate out to depth 50 is impressive on 32- and 64-qubit circuits: on such circuits, \textsc{ECMC} is almost uniformly successful. However, \textsc{ECMC} struggled on 128-qubit circuits for some depths. \textsc{Manjushri} is almost uniformly successful out to about depth 38, before tailing off to about 75\% at depth 50 (falling to 0\% at depth 48 for 128-qubit circuits that are equivalent). These results establish that \textsc{Manjushri} is a practical and scalable solution for large-scale quantum-circuit verification, and would be the preferred choice unless clients need to check equivalence of circuits of depth $>$38. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2601.22372 [quant-ph] (or arXiv:2601.22372v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2601.22372 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Xuan Du Trinh [view email] [v1] Thu, 29 Jan 2026 22:30:35 UTC (1,776 KB) Full-text links: Access Paper: View a PDF of the paper titled Manjushri: A Tool for Equivalence Checking of Quantum Circuits, by Xuan Du Trinh and 3 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-01 References & Citations INSPIRE HEP NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) Links to Code Toggle Papers with Code (What is Papers with Code?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)

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Source: arXiv Quantum Physics