Quantum radar has emerged as a promising sensing paradigm that exploits quantum resources, including entanglement and quantum correlations, to enhance target detection in noisy and lossy environments. Although entanglement generated by superconducting devices such as Josephson parametric amplifiers, Josephson parametric converters, and Josephson traveling-wave parametric amplifiers is rapidly degraded under realistic propagation conditions, the remaining quantum correlations can still provide a measurable detection advantage through the principles of quantum illumination. This review presents a comprehensive engineering perspective on quantum radar, covering the theoretical foundations of quantum illumination, microwave entanglement generation, electro-optomechanical quantum transducers, atmospheric channel effects, cryogenic receiver architectures, and digital signal-processing techniques. Recent microwave experimental demonstrations are also reviewed, highlighting the transition from theoretical concepts to laboratory-scale implementations. Collectively, these developments demonstrate that microwave quantum radar is evolving toward practical sensing architectures while emphasizing the engineering challenges that must be addressed before real-world deployment.
An Elitzur–Vaidman bomb tester demonstrates interaction-free sensing: detecting an object without absorbing a photon. The original protocol, however, has a success probability capped at 25%. We present a scalable quantum circuit that harnesses the quantum Zeno effect to overcome this limit. A single probe qubit undergoes repeated cycles of a small rotation followed by a controlled-NOT (CNOT) with an ancilla qubit representing the obstacle. The circuit requires only two qubits, regardless of the number of cycles N and has depth linear in N, compatible with near-term processors that support mid-circuit measurement and conditional reset. We simulate the circuit under ideal conditions and under a depolarizing noise model with gate errors typical of superconducting qubits (CNOT error 2% and single-qubit gate error rate 0.1%). Under noise, the success probability peaks around N=14 (reaching 72.0%), outperforming the original 25% limit by nearly a factor of three, with a well-defined optimal region. The protocol requires approximately 4.4 times fewer photons than the original Elitzur–Vaidman scheme to achieve 99.9% confidence. Its simple repetitive structure and well-defined optimal regime make it a practical benchmark for quantifying gate errors and decoherence on noisy intermediate-scale quantum hardware for quantum sensing applications.
Single-photon lidar possesses significant advantages in underwater weak-signal target detection. However, the complex underwater light propagation environment leads to highly random and non-uniform observation noise. Furthermore, the limited scale of real data, constrained by experimental conditions and acquisition costs, makes it difficult to meet the training requirements of deep learning detection models. To address these issues, this paper proposes a physics-driven method for single-photon lidar observation modeling and high-fidelity data generation. First, a noise physics model is established based on the water photon detection mechanism to achieve parameterized characterization of the underwater observation degradation process. Then, virtual data matching the distribution of real observation data are synthesized through domain-adaptive physics optimization. Simultaneously, a simplified data synthesis method based on statistical feature constraints is proposed, enabling rapid construction of large-scale samples—generating over 14 000 images within 0.2 h. Experimental results demonstrate that the relative alignment index exceeds 90% across all evaluated scenarios, validating that both methods effectively balance data fidelity and generation efficiency to provide a robust data foundation for spectral power distribution target detection.
Measurements of plasma electric fields are essential to the advancement of plasma science and applications. Performing non-invasive in situ measurements of plasma fields on sub-millimeter length scales with high sensitivity over a large range of field magnitude remains an outstanding challenge. We introduce and demonstrate a method for plasma electric field measurement that employs electromagnetically induced transparency as a high-resolution quantum-optical probe for the Stark energy level shifts of Rydberg atoms embedded in a plasma and serving as highly sensitive field sensors. The method is applied in diagnostics of plasmas generated by photo-excitation of a cesium vapor. The plasma electric fields are extracted from spatially resolved measurements of field-induced lineshape changes and shifts of Rydberg resonances in rubidium tracer atoms. Measurement capabilities over a range of plasma densities and temperatures are exploited to characterize plasmas in applied magnetic fields and to image electric-field distributions in cyclotron-heated plasmas. Our results pave the way toward further applications of Rydberg-atom-based field sensors to diagnostics and monitoring of electric fields due to plasmas.
Side-channel imperfections in quantum key distribution (QKD) are often treated within the GLLP and Koashi framework, which typically produces overly conservative key-rate estimates. Conditional-entropy approaches based on the Holevo bound provide a less pessimistic alternative but must correctly account for post-selective measurements, such as unambiguous state discrimination. We show that general post-selective soft-filtering transformations of side-channel states can be consistently incorporated into this framework. By relating the distinguishability of filtered Trojan-horse-attack states to observable parameters, namely, the reflected mean photon number and the single-photon yield, we derive a Holevo-based upper bound on the eavesdropper's information for decoy-state BB84. Numerical comparison demonstrates that this method yields significantly higher key rates than the GLLP and Koashi approach when the side-channel intensity is large, extending the secure distance by tens of kilometers. This provides a practical and tighter tool for leakage estimation in modern QKD systems.
