Quantum Science and Technology最新文献

{"title":"Programmable optical parametric amplifier synthesizer for cubic phase states and amplified Schrödinger cat states","authors":"Yusuf Turek,Ming-Yan Sun,Xiao-Xi Yao","doi":"10.1088/2058-9565/aeb092","DOIUrl":"https://doi.org/10.1088/2058-9565/aeb092","url":null,"abstract":"Abstract We introduce a programmable optical parametric amplifier (OPA) synthesizer that, under a heralded photon-number-resolving framework, generates high-fidelity cubic phase states and amplifies Schrödinger cat states. By systematically exploring both the catalytic configuration, where the idler input and output contain the same number of photons (m = n ), and non-catalytic configurations ( m = n), we discover two qualitatively different functionalities. First, with a coherent-state signal input, our protocol generates cubic phase states with fidelity exceeding 0.99 across a broad range of (m, n) configurations. Second, using a Schrödinger cat state as the signal input, the same framework amplifies the cat state: an input cat with amplitude αin ≤ 1 is transformed into an output squeezed cat with αout ≥ 2 while maintaining fidelity above 0.99. The catalytic configuration preserves the input parity and restores the idler state, whereas non-catalytic configurations enable parity-flipping amplification with higher success rates. Moreover, the amplified output can serve as a seed for subsequent amplification rounds, offering a self-seeding pathway to progressively larger cat states. Our protocol requires only moderate-gain OPA operation and low-order photon-number-resolving detection, providing a flexible and experimentally accessible platform for cubic phase state preparation and amplified squeezed cat state generation.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"20 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149089752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measurement circuit ansatz: Naimark versus quantum neural-network measurements","authors":"Sung Won Yun,Thi Ha Kyaw,Joonwoo Bae","doi":"10.1088/2058-9565/aeb048","DOIUrl":"https://doi.org/10.1088/2058-9565/aeb048","url":null,"abstract":"Abstract In this work, we present constructions of quantum circuits to implement general measurements on quantum hardware. Firstly, we investigate a quantum circuit ansatz by following the Naimark extension with a universal set of gates, such as controlled-NOT and single-qubit gates; we call it a {it Naimark measurement}. We present a circuit ansatz framed by the Naimark extension, leaving single-qubit gates with parameters, and apply a classical optimizer to determine their parameters to approximate a desired quantum measurement. Secondly, we relax the Naimark measurement with quantum neural-network (QNN) circuits, employing parameterized quantum circuits. We present hybrid Naimark-QNN measurements by incorporating QNN circuits into Naimark measurements. Thirdly, we also consider fully QNN measurements with shallow parameterized circuits. Then, we compare the constructed measurement circuits, Naimark, hybrid Naimark-QNN, and fully QNN measurements, for strategies of state discrimination, such as minimum-error and maximum-confidence measurements. We demonstrate that QNN circuits can efficiently and effectively achieve near-optimal quantum measurements with fewer training iterations.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"16 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149089755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Finite-Frequency Fluctuation-Response Bounds for Open Quantum Systems","authors":"Jie Gu,Kangqiao Liu","doi":"10.1088/2058-9565/aeaf7f","DOIUrl":"https://doi.org/10.1088/2058-9565/aeaf7f","url":null,"abstract":"Abstract We derive a finite-frequency fluctuation-response inequality for Markovian open quantum systems in an input-output setting. For any downstream measurement of the emitted field, the measured lock-in response-to-noise matrix is bounded by the output-field quantum Fisher information rate. For dissipative amplitude modulation with vacuum inputs, this information rate is further bounded by a frequency-independent signal-channel activity, which reduces for kinetic modulation to the stationary channel fluxes. For a faithful stationary state, complete access to the Markov output, and horizontal dissipative tangents, we also evaluate the intermediate output-field quantum Fisher information rate explicitly and show that it equals the activity matrix. The result is detector-facing but unraveling-independent: it applies after choosing a measurement record, while the information ceiling is set by the quantum field before any detection scheme or trajectory representation is selected. We formulate the bound for multiple signal channels and real finite-frequency quadratures, and illustrate it with a single-sided cavity, resonance fluorescence, and a two-port truncated Kerr-parametric cat resonator exhibiting appreciable channel mixing and off-diagonal matrix effects.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"166 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149089756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optomagnonic generation of entangled travelling fields with different polarizations","authors":"Zi-Xu Lu,Huai-Bing Zhu,Xuan Zuo,Jie Li","doi":"10.1088/2058-9565/aeaf7c","DOIUrl":"https://doi.org/10.1088/2058-9565/aeaf7c","url":null,"abstract":"Abstract The optomagnonic coupling between magnons and optical photons is an essential component for building remote quantum networks based on magnonics. Here we show that such a coupling, manifested as the magnoninduced Brillouin light scattering, can be exploited to entangle two propagating optical fields. The protocol employs two pairs of the whispering gallery modes coupled to the same magnon mode in a YIG microsphere or microdisk. In each pair a strong pump field is applied to activate either Stokes or anti-Stokes scattering. Due to the magnon mode involving in the two scattering processes and as a mediation, Stokes and anti-Stokes photons of different polarizations get entangled. The entanglement can be extracted by filtering the travelling output fields centered at the Stokes and anti-Stokes sidebands. Optimal conditions are identified under which strong output entanglement can be achieved.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"25 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149089759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantum lock-in detection via successive adiabatic evolution","authors":"Kangze Li,Siqi Chen,Hao Zhang,Jiazhao Tian,Liantuan Xiao,Gerardo Adesso","doi":"10.1088/2058-9565/aeaf80","DOIUrl":"https://doi.org/10.1088/2058-9565/aeaf80","url":null,"abstract":"Abstract In recent years, quantum lock-in detection has emerged as a promising technique to accurately detect weak signals submerged in background noise. However, the signal-to-noise ratio of existing protocols is severely limited by spectral leakage resulting from control operations implemented in pulse form. Here, we propose a general protocol for realizing quantum lock-in detection by employing successive quantum adiabatic evolution. In our protocol, the signal modulation is achieved by adiabatically controlling the time evolution of the quantum probe, which enables the implementation of triangular modulation functions. The realization of triangular-wave modulation fundamentally solves the problem of spectral leakage and facilitates the extraction of the complete characteristics of the target signals. We present a practical implementation scheme of adiabatic quantum lock-in detection based on nitrogen-vacancy centers in diamond, and demonstrate that the proposed protocol possesses strong resilience against experimental imperfections. Our results establish adiabatic quantum lock-in detection as a robust and experimentally accessible approach to detection of weak alternating signals in noisy environments, thus promoting the advance of real-world quantum sensing technologies.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"37 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149089758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resource-efficient quantum simulation of transport phenomena via Hamiltonian embedding","authors":"Joseph Li,Gengzhi Yang,Jiaqi Leng,Xiaodi Wu","doi":"10.1088/2058-9565/aeaf7d","DOIUrl":"https://doi.org/10.1088/2058-9565/aeaf7d","url":null,"abstract":"Abstract Transport phenomena play a key role in a variety of application domains, and efficient simulation of these dynamics remains an outstanding challenge. While quantum computers offer potential for significant speedups, existing algorithms either lack rigorous theoretical guarantees or demand substantial quantum resources, preventing scalable and efficient validation on realistic quantum hardware. To address this gap, we develop a comprehensive framework for simulating classes of transport equations, offering both rigorous theoretical guarantees---including exponential speedups in specific cases---and a systematic, hardware-efficient implementation. Central to our approach is the Hamiltonian embedding technique, a white-box approach for end-to-end simulation of sparse Hamiltonians that avoids abstract query models and retains near-optimal asymptotic complexity. Empirical resource estimates indicate that our approach can yield an order-of-magnitude (e.g., 42x) reduction in circuit depth given favorable problem structures. We then apply our framework to solve linear and nonlinear transport PDEs, including the first experimental demonstration of a 2D advection equation on a trapped-ion quantum computer.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"29 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149089773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Encoding Numerical Data for Generative Quantum Machine Learning","authors":"Michael Krebsbach,Florentin Reiter,Thomas Wellens,Hagen-Henrik Kowalski,Ali Abedi","doi":"10.1088/2058-9565/aeaf7e","DOIUrl":"https://doi.org/10.1088/2058-9565/aeaf7e","url":null,"abstract":"Abstract Generative quantum machine learning models are trained to deduce the probability distribution underlying a given dataset, and to produce new, synthetic samples from it. The majority of such models proposed in the literature, like the Quantum Circuit Born Machine (QCBM), fundamentally work on a binary level. Real-world data, however, is often numeric, requiring the models to translate between binary and continuous representations. We analyze how this transition influences the performance of quantum models and show that it requires the models to learn correlations that are solely an artifact of the way the data is encoded, and not related to the data itself. At the same time, structure of the original data, like continuity, can be obscured in the binary representation, hindering generalization. To mitigate these effects, we propose a strategy based on Gray-codes that can be implemented with essentially no overhead, conserves structures in the data, and avoids artificial correlations in situations in which the standard approach creates them. Considering datasets drawn from various low-dimensional probability distributions, we verify that, in most cases, QCBMs using the reflected Gray code learn faster and more accurately than those with standard binary code. This shows that, as complement to specifically tailored circuit ansätze or data pre-processing, binary encodings can be used to introduce inductive biases into generative machine learning models.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"52 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149089775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Half the Interference, Most of the Answer: Approximate Quantum Simulation via Path-Sum Pruning","authors":"Sinan Pehlivanoglu,Srinivasan Iyengar,Amr Sabry","doi":"10.1088/2058-9565/aeaf7a","DOIUrl":"https://doi.org/10.1088/2058-9565/aeaf7a","url":null,"abstract":"Abstract Classical simulation of quantum circuits is expensive for two distinct reasons. The obvious one is state-space size: an n-qubit system requires exponentially many amplitudes. The less obvious one is interference: useful output distributions emerge only after many computational histories have been coherently combined at common endpoints, and this aggregation step is itself a substantial source of cost. We introduce statistical interference sampling, a framework that makes this second bottleneck explicit by treating endpoint interference as a separately schedulable computation. Using the Chemical Abstract Machine (ChAM) as our model, weighted path contributions evolve as concurrent molecular species, and interference reactions combine contributions that share a common output state. A threshold rule terminates the process once an endpoint accumulates sufficient amplitude, discarding the remaining reactions. The method does not improve worst-case complexity and is not intended as a general-purpose simulator. Its purpose is to ask a more targeted question: how much of the interference calculation can be skipped while still recovering a useful output distribution? On benchmark circuits for Deutsch-Jozsa, Grover search, Simon's problem, and Shor period-finding instances, we find that nearly 50% of endpoint interference reactions can be omitted while maintaining over 90% output accuracy for most algorithms tested. Circuits with strong amplitude separation, where a large gap exists between the amplitude accumulated at the correct endpoint and the maximum amplitude attainable at any incorrect endpoint, benefit most from early termination; circuits with flatter output distributions, where valid outputs share comparable amplitudes across many endpoints rather than concentrating probability on a single marked state, are less amenable to this strategy. These results suggest that interference arithmetic is a structured resource that admits meaningful approximation, and that exposing it explicitly opens new opportunities for pruning strategies across path-sum, Pauli-path, and tensor-network simulation methods.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"7 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149089774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Compositional Quantum Heuristics for Max-Clique Detection","authors":"Tiffany Duneau,Colin Krawchuk,Anna Naomi Pearson","doi":"10.1088/2058-9565/aeaf7b","DOIUrl":"https://doi.org/10.1088/2058-9565/aeaf7b","url":null,"abstract":"Abstract Quantum machine learning holds the promise of combining the success of classical machine learning methods with the power of quantum computing, however one of the largest obstacles facing the field is the problem of barren plateaus. Parameterised quantum circuits offer a flexible framework for developing quantum machine learning models, but their practicality is constrained by a trade-off between trainability and classical simulability. In general, circuits that are sufficiently expressive to model complex behaviour often exhibit barren plateaus, where gradients vanish and optimisation fails.

In this work we investigate a compositional approach to mitigate this trade-off. We exploit the recursive structure of Max-Clique by reusing a model trained on small graph instances to guide a sequence of induced-subgraph problems whose outputs are composed into a clique of the original graph. To ensure trainability of these subcomponents, we describe a framework for constructing group-invariant loss functions, which introduce symmetry-induced inductive bias and lead to improved gradient behaviour and generalisation. In particular, we use this framework to design permutation-equivariant quantum graph neural networks for identifying maximum cliques in graphs. The models we construct exhibit superior training trajectories through symmetry-induced bias, reaching accuracies up to 30% better than the un-symmetrised counterparts. Our experiments demonstrate that the trained models generalise to larger, more complex problem instances, which we demonstrate on 8 to
16 node graphs.

Finally, inspired by Quantum-Informed Recursive Optimisation Algorithms [FKS+24], we implement a recursive hybrid quantum-classical heuristic using the learned quantum models to guide a classical search procedure, demonstrating improved inference accuracy and scalability. Together, these results suggest that compositional circuits could be a viable pathway towards scalable quantum learning models that remain challenging to reproduce classically.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"21 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149089776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Entangling Distant Qubits via Flying Photons Under Thermal Noise Protected by Multi-Time-Bin Encoding","authors":"Jing Wu,Changqing Wang,Andrew R Cameron,Yao Lu,Silvia Zorzetti","doi":"10.1088/2058-9565/aeaf81","DOIUrl":"https://doi.org/10.1088/2058-9565/aeaf81","url":null,"abstract":"Abstract Entangling distant stationary qubits—such as superconducting qubits, color centers, trapped ions, and phononic modes—commonly relies on flying photons transmitted through noisy channels. 
The fidelity of remote entanglement is severely degraded by channel noise. While entanglement purification can theoretically mitigate this effect, its practical implementation in quantum networks is limited by the overhead of local operations and classical communication. We propose a multi-time-bin encoding scheme that improves the fidelity of remote entangled stationary qubits without relying on entanglement purification. Our results show that, compared to single-rail (vacuum–one-photon) encoding, the fidelity in thermal-loss Gaussian channels is improved from 0.66 to 0.89. Taking superconducting qubits connected through microwave-to-optical transduction as a representative implementation, the fidelity is increased from 0.75 to 0.98. Finally, we discuss the prospects for extending the protocol to other stationary-qubit platforms.
","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"7 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149089757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}