Multi-Outcome Circuit Optimization for Enhanced Non-Gaussian State Generation
arXiv QuantumArchived 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
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Submission history
From: Sadeq Ismailzadeh [view email]
[v1] Wed, 18 Mar 2026 21:40:34 UTC (910 KB)
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