EPJ Quantum Technology最新文献

Efficient bidirectional microwave-optical photon conversion is a key capability for scaling superconducting quantum processors into distributed networks. Achieving the necessary conversion efficiency requires filling a critical knowledge gap in understanding the loss mechanisms of electro-optic materials. Here, we characterize the microwave properties of single-crystal bulk LiNbO₃ and AlN over a broad range of powers, down to single-photon levels, and spanning from millikelvin temperatures to above 1 K. We demonstrate that both materials exhibit two-level systems (TLS) behavior, while piezoelectric-related losses are excluded. We show that TLS-induced dissipation is predominantly localized on the surface rather than being an intrinsic bulk property, a result further corroborated by room-temperature 3D XPS and time-of-flight SIMS analyses. These findings provide useful insights to engineer hybrid architectures that integrate bulk electro-optic crystals within superconducting cavities, proving that microwave quality factors compatible with high-efficiency microwave–optical transduction are within reach.

We analyze a concrete local quantum-optical measurement architecture for polarization-entangled photon pairs in which Bob coherently maps polarization onto an additional path degree of freedom that functions as a local quantum label. Within an explicit loss-inclusive POVM model that includes no-detection events, and without coincidence matching, event-by-event pairing, or any side information from Alice, we compare three regimes: direct label readout, symmetric label-interference networks, and an asymmetric 2 + 3-aperture architecture. Direct readout and a broad symmetric class yield setting-independent local POVM outcome probabilities and linear unconditional count rates, in agreement with standard no-signaling expectations for ordinary local statistics. In contrast, for the asymmetric architecture we identify a separately defined normalized, block-averaged spatial morphology constructed from Bob’s unconditional detection records that becomes setting-distinguishable as Alice’s polarization setting is varied. Numerical simulations for contrasted settings show distinct block-averaged spatial structure and spatial-frequency content, and a complementary phase-shift/path-sum analysis independently confirms asymmetric multipath interference as the underlying mechanism. The result is an explicit, implementable distinction within standard quantum mechanics between setting-independent ordinary local statistics and setting-distinguishable structure in a derived block-averaged observable generated by asymmetric local label interference. These results delineate within the explicit measurement model, where quantum-label interference leaves ordinary local statistics unchanged and where it generates setting-distinguishable structure in a derived block-averaged local observable.

Wireless Sensor Network plays a crucial role in IoT applications, but they face numerous challenges such as limited energy, insecure routing, and inefficient cluster head selection, which lower the network lifetime and reliability. To overcome these challenges, this paper proposes a quantum K-means assisted trust-aware energy-efficient routing framework. The proposed method deploys a multi-dimensional trust model which integrates the direct, indirect, behavioural and energy trust to ensure the node is trustworthy. Moreover, Quantum K-means clustering has been employed to balance the clusters, while hybrid SSO-PSO optimization algorithm elects optimal cluster heads based on trust, residual energy, and distance to the base station. Additionally, trust-aware multi-hop routing strategy is employed in the proposed framework to assure secure and energy-efficient data transmission in the network. The proposed framework is evaluated through the MATLAB simulations, using PDR, throughput, energy consumption, end-to-end delay and network lifetime as the key performance evaluation metrics. The proposed approach improves the packet delivery ratio and throughput by 6.6% and 10.33% respectively, reduces the energy consumption and end-to-end delay by 14.53% and 15.05% respectively, enhances the network lifetime by 24.88%, and provides secure communication, making it suitable for the IoT-based wireless sensor network applications.

A major challenge for quantum workforce development is the need to both understand and reliably assess student learning of quantum information science (QIS) fundamentals. Yet student thinking is notoriously difficult to probe, even for seasoned education researchers. This article presents the story of Item 15 on the Quantum Computing Conceptual Survey (QCCS). This assessment item underwent more revision and discussion within the team than the remaining 19 assessment questions combined. This paper provides a behind-the-scenes look at the development of this assessment question: a story that both reveals interesting findings about student reasoning in quantum computing and illustrates why quantum education researchers insist on triangulating diverse quantitative and qualitative data sources when developing and refining assessment items, with implications for any researcher looking to understand and measure student conceptual reasoning in quantum computing, as well as for QIS curriculum and workforce development more broadly.

We present a quantum reservoir computing (QRC) framework based on a small-scale quantum system comprising at most six interacting qubits, designed for nonlinear financial time-series forecasting. We apply the model to predict future daily closing trading prices of 20 quantum-sector publicly traded companies over the period from April 11, 2020, to April 11, 2025 (exclusive), as well as minute-by-minute trading prices during out-of-market hours on July 7, 2025. Our analysis identifies optimal reservoir parameters that yield stock trend (up/down) classification accuracies exceeding 86%. Importantly, the QRC model is platform-agnostic and can be realized across diverse physical implementations of qubits, including superconducting circuits and trapped ions. These results demonstrate the expressive power and robustness of small-scale quantum reservoirs for modeling complex temporal correlations in financial data, highlighting their potential applicability to real-world forecasting tasks on near-term quantum hardware.

The ground state of the negatively charged NV center forms a spin–1 manifold providing a versatile platform for sensing and information processing. Here we present a scheme for implementing fast arbitrary qutrit gates in the low–field regime using monochromatic microwave pulses of constant intensity tuned to the zero–field transition. By concatenating pulses with appropriate phases and durations, the NV-ERC scheme is extended from SU(2) operations in the double-quantum subspace to the full three–level structure. We show that arbitrary SU(3) operations can be decomposed into rotations in the double-quantum subspace together with effective implementations of the generators related to (hat{lambda }_{5}) and (hat{lambda }_{8}). We further analyze the nontrivial (hat{lambda }_{5}) operation under pure dephasing, finding low average gate infidelities throughout the regime studied. We illustrate the SU(3) decomposition with a use case: performing quantum state tomography of the complete three-level density matrix.

Quantum annealing is a promising heuristic for combinatorial optimization, but on current hardware its solution quality degrades for larger and more complex problems due to noise and small energy gaps. Reverse annealing has been established as a refinement strategy, yet it remains unclear how problem characteristics, particularly the implemented quadratic unconstrained binary optimization (QUBO) matrix structure, influence refinement success and the optimal parameter regime. We find that combining forward and reverse annealing improves solution quality, with the magnitude of the improvement depending strongly on the problem class and corresponding QUBO size, while efficiency gains are tied to both annealing and problem-instance parameters. The benefits of reverse annealing increase with problem complexity and are strongest in regimes where forward annealing is increasingly limited. In these settings, reverse annealing yields larger efficiency gains than simply extending forward annealing times. We establish these results through a systematic experimental study on a D-Wave Advantage system, benchmarking reverse annealing across Max-Cut, Number Partitioning, and sparse clustering problems while varying reverse distance, pause duration, and annealing time. We identify optimal reverse annealing parameter regimes that depend on QUBO characteristics and are consistent with expected freeze-out behavior and with the energy-level-crossing structure observed for small representative instances. These findings demonstrate that reverse annealing is most valuable for large, high-complexity optimization problems and is likely to gain importance as quantum annealing hardware scales toward more realistic applications.

Quantum technologies serve civilian and military purposes at once, a fact usually captured by the contested term “dual-use”. Introducing a topical collection on dual-use quantum technologies, this editorial provides a proposed guidance on the term’s applicability in view of an emerging quantum economy. Quantum technology was dual-use from its origins, in foundational experiments funded and in some cases performed by defence and intelligence agencies; but that history is largely Anglo-American, which is part of why the connection between quantum research and defence is accepted so differently, and so much more recently, in continental Europe. As a concept, “dual-use” describes a status rather than settling any moral question, a point that three of the collected papers reach independently using different lenses. The collection’s ten contributions are a reflection of a wide and diverse sector; they span technology development, strategy, governance, and the ethics of dual-use research.

Engaging a larger, non-specialist audience with quantum technology poses challenges as the theory underlying quantum technology is very different to what we experience in our everyday lives. Quantum technology is predicted to have a significant impact on society once it matures. This study ((n = 637) adults representative of the Dutch population) examined the effect of different frames on engagement – specifically, information seeking, internal efficacy, general interest and perceived knowledge – with quantum technology. The different frames were: enigmatic, explaining quantum physics, benefit, risk and balanced. Results indicated that framing quantum as enigmatic does not affect engagement, while explaining quantum physics positively influences general interest. Furthermore, emphasising a benefit of quantum technology increases participants’ internal efficacy, whereas highlighting both a benefit and a risk of quantum technology decreases perceived knowledge. Based on these findings, we offer practical advice for science communicators in the field and suggest further research.

Scalable quantum networks require quantum interfaces that coherently connect stationary matter qubits with flying photonic qubits. In solid-state defect platforms, such interfaces require coordinated optical excitation, microwave spin control, photon detection, and feedback with nanosecond-level timing, while conventional instrument-based control systems become increasingly difficult to scale as experimental protocols grow in complexity. Here we present an open-source FPGA control architecture for solid-state spin–photon interface experiments. Built on the Quantum Instrumentation Control Kit (QICK), the platform extends the existing FPGA overlay by integrating a programmable multi-channel single-photon counter, enabling photon-count–centric experiment execution while preserving compatibility with the QICK software ecosystem. This architecture integrates time-gated single-photon detection with synchronized RF, microwave, and digital control within a unified hardware environment. Using single nitrogen-vacancy (NV) centers in diamond, we experimentally validate the platform through microwave spin manipulation, resonant optical control, automated measurement routines, and time-bin–encoded spin–photon correlation protocols relevant to quantum networking. These results establish an extensible and experimentally validated control framework for solid-state spin–photon interfaces, with clear potential to accelerate the development of scalable quantum-network nodes.