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Multi-Outcome Circuit Optimization for Enhanced Non-Gaussian State Generation

arXiv Quantum Archived Mar 20, 2026 ✓ Full text saved

arXiv:2603.18303v1 Announce Type: new Abstract: Photonic quantum computing has gained significant interest in recent years due to its potential for scaling to large numbers of qubits. A critical requirement for fault-tolerant quantum computation is the reliable generation of non-Gaussian quantum states, typically achieved using Gaussian operations and photon-number-resolving detectors. However, the probabilistic nature of quantum measurement typically results in low success rates for state prepa

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    Quantum Physics [Submitted on 18 Mar 2026] Multi-Outcome Circuit Optimization for Enhanced Non-Gaussian State Generation S. Ismailzadeh, B. Abedi Ravan Photonic quantum computing has gained significant interest in recent years due to its potential for scaling to large numbers of qubits. A critical requirement for fault-tolerant quantum computation is the reliable generation of non-Gaussian quantum states, typically achieved using Gaussian operations and photon-number-resolving detectors. However, the probabilistic nature of quantum measurement typically results in low success rates for state preparation. Conventionally, these circuits are optimized to herald a single specific target outcome, thereby disregarding the potential utility of alternative measurement patterns generated by the same physical setup. In this work, we propose and demonstrate a multi-outcome optimization strategy that increases the overall acceptance probability by allowing a single circuit to produce useful quantum states across several measurement patterns. To evaluate this approach, we apply the framework to the generation of Gottesman-Kitaev-Preskill core states, Schrodinger cat states, binomial codes, and cubic phase states using both two-mode and three-mode Gaussian circuits. We demonstrate that the success probability can be enhanced through two distinct mechanisms: first, by simultaneously targeting a diverse set of useful resource states, and second, by aggregating degenerate outcomes to maximize the production rate of a single target state. Subjects: Quantum Physics (quant-ph); Computational Physics (physics.comp-ph) Cite as: arXiv:2603.18303 [quant-ph]   (or arXiv:2603.18303v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2603.18303 Focus to learn more Submission history From: Sadeq Ismailzadeh [view email] [v1] Wed, 18 Mar 2026 21:40:34 UTC (910 KB) Access Paper: HTML (experimental) view license Current browse context: quant-ph < prev   |   next > new | recent | 2026-03 Change to browse by: physics physics.comp-ph References & Citations INSPIRE HEP NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation 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 Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Quantum
    Category
    ◌ Quantum Computing
    Published
    Mar 20, 2026
    Archived
    Mar 20, 2026
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