Non-Gaussian quantum states of bosons are a key resource in quantum information science with applications ranging from quantum metrology to fault-tolerant quantum computation. Generation of photonic non-Gaussian resource states, such as Schrödinger's cat and Gottesman-Kitaev-Preskill states, is challenging. In this work, we go beyond existing passive architectures and explore a broad set of adaptive schemes. Our numerical results demonstrate a consistent improvement in the probability of success and fidelity of generating these non-Gaussian quantum states with equivalent resources. We also explore the effect of loss as the primary limiting factor and observe that adaptive schemes lead to more desirable outcomes in terms of overall probability of success and loss tolerance. Our work offers a versatile framework for non-Gaussian resource state generation with the potential to guide future experimental implementations.
Non-Gaussian quantum states of bosons are a key resource in quantum information science with applications ranging from quantum metrology to fault-tolerant quantum computation. Generation of photonic non-Gaussian resource states, such as Schrödinger's cat and Gottesman-Kitaev-Preskill states, is challenging. In this work, we go beyond existing passive architectures and explore a broad set of adaptive schemes. Our numerical results demonstrate a consistent improvement in the probability of success and fidelity of generating these non-Gaussian quantum states with equivalent resources. We also explore the effect of loss as the primary limiting factor and observe that adaptive schemes lead to more desirable outcomes in terms of overall probability of success and loss tolerance. Our work offers a versatile framework for non-Gaussian resource state generation with the potential to guide future experimental implementations.
Non-Gaussian quantum states are crucial to fault-tolerant quantum computation with continuous-variable systems. Usually, generation of such states involves trade-offs between success probability and quality of the resultant state. For example, injecting squeezed light into a multimode interferometer and postselecting on certain patterns of photon-number outputs in all but one mode, a fundamentally probabilistic task, can herald the creation of cat states, Gottesman-Kitaev-Preskill (GKP) states, and more. We consider the addition of a non-Gaussian resource state, particularly single photons, to this configuration and show how it improves the qualities and generation probabilities of desired states. With only two modes, adding a single-photon source improves GKP-state fidelity from 0.68 to 0.95 and adding a second then increases the success probability eightfold; for cat states with a fixed target fidelity, the probability of success can be improved by factors of up to four by adding single-photon sources. These demonstrate the usefulness of additional commonplace non-Gaussian resources for generating desirable states of light.
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.
Abstract The practical value of non-Gaussian states for quantum computation, metrology, and networking is currently limited by the intrinsically low success rates of conventional generation methods like photon addition and subtraction. We introduce a scalable protocol that overcomes this bottleneck using postselected von Neumann measurements beyond the weak-coupling regime. Applied to standard Gaussian inputs, our method efficiently generates a suite of critical resources—including large-amplitude Schrödinger cat states, Gottesman–Kitaev–Preskill-like states, and two-mode entangled states—with considerably higher success probabilities. Quantitative analysis of Wigner negativity and entanglement confirms their high quality. This work establishes postselected von Neumann measurement as a general and scalable principle for quantum resource generation, moving beyond a fundamental limitation in quantum state engineering.
The effects of optical loss and photon distinguishability on the heralded generation of entangled states based on Gaussian resources are quantitatively investigated. By incorporating mode-dependent loss and the statistical characteristics of partially distinguishable photons into a phase-space representation, an efficient numerical framework is established to optimize target-state fidelity and success probability, with a specific focus on the enhancement triggered by non-Gaussian operations such as photon addition and subtraction. The numerical optimization results indicate that a non-vacuum post-selection strategy within a dual-rail encoding framework, combined with the simultaneous tuning of squeezing parameters and the interferometer network, effectively suppresses vacuum noise, enabling the generation of high-fidelity Bell, GHZ, and W states under realistic experimental constraints. The results show that introducing non-Gaussian operations can successfully enhance the state generation performance under realistic imperfections analogous to the enhancements observed under ideal conditions. This study demonstrates that experimental imperfections primarily scale down the success probability rather than fundamentally compromising the state fidelity, providing practical design guidelines for scalable state engineering on integrated photonic platforms.
Advanced quantum technologies rely on non-Gaussian states of light, essential for universal quantum computation, fault-tolerant error correction, and quantum sensing. Their practical realization, however, faces hurdles: Simulating large multimode generators is computationally demanding, and benchmarks such as the do not capture how effectively photon detections yield useful non-Gaussianity. We address these challenges by introducing the ( s 0 , δ 0 ) , a continuous and operational measure that goes beyond stellar rank. Leveraging these parameters, we develop a universal optimization method that reduces photon-number requirements and greatly enhances success probabilities while preserving state quality. Applied to the Gottesman-Kitaev-Preskill state generation, for example, our method cuts the required photon detections by a factor of 3 and raises the preparation probability by nearly 10 8 . Demonstrations across cat states, cubic phase states, Gottesman-Kitaev-Preskill states, and even random states confirm broad gains in experimental feasibility. Our results provide a unifying principle for resource-efficient non-Gaussian state generation, charting a practical route toward scalable optical quantum technologies and fault-tolerant quantum computation.
Quantum technologies, encompassing communication, computation, and metrology, rely on the generation and control of non-Gaussian states of light. These states enable secure quantum communication, fault-tolerant quantum computation, and precision sensing beyond classical limits, yet their practical realisation remains a major challenge due to reliance on high-photon-number Fock states or strong non-linearities. Here we introduce a unified optical framework that removes this constraint, using only Gaussian inputs, optical parametric amplification, and heralded photon detection. Within a single architecture, we demonstrate the generation of photon-added squeezed states with near unit fidelity, cubic-phase-like states with strong non-linearities and fidelities above 98.5%, and squeezed-cat states exceeding 99% fidelity that can be iteratively bred into GKP grid states surpassing the 9.75 dB fault-tolerance threshold. Operating entirely below 3 dB of input squeezing, the approach provides a scalable, experimentally accessible platform that unites the state resources required for quantum communication, metrology, and computation within one coherent optical framework.