We report on a high-level squeezed vacuum state with maximum quantum noise reduction of 13.2 dB directly detected at the pump power of 180 mW. The pump power dependence of the squeezing factor is experimentally exhibited. When considering only loss and phase fluctuation, the fitting results have a large deviation from the measurement value near the threshold. By integrating green-light-induced infrared absorption (GLIIRA) loss, the squeezing factor can be perfectly fitted in the whole pump power range. The result indicates that GLIIRA loss should be thoroughly considered and quantified in the generation of high-level squeezed states.

The use of optical sensing for in vivo applications is compelling, since it offers the advantages of non-invasiveness, non-ionizing radiation, and real-time monitoring. However, the signal-to-noise ratio (SNR) of the optical signal deteriorates dramatically as the biological tissue increases. Although increasing laser power can improve the SNR, intense lasers can severely disturb biological processes and viability. Quantum sensing with bright squeezed light can make the measurement sensitivity break through the quantum noise limit under weak laser conditions. A bright squeezed light source is demonstrated to avoid the deterioration of SNR and biological damage, which integrates an external cavity frequency-doubled laser, a semi-monolithic standing cavity with periodically poled titanyl phosphate (PPKTP), and a balanced homodyne detector (BHD) assembled on a dedicated breadboard. With the rational design of the mechanical elements, the optical layout, and the feedback control equipment, a maximum non-classical noise reduction of −10.7 ± 0.2 dB is observed. The average squeeze of −10 ± 0.2 dB in continuous operation for 60 min is demonstrated. Finally, the intracavity loss of degenerate optical parametric amplifier (DOPA) and the initial bright squeezed light can be calculated to be 0.0021 and −15.5 ± 0.2 dB, respectively. Through the above experimental and theoretical analysis, the direction of improving bright squeeze level is pointed out.

Signal detection and classification tasks, especially in the realm of audio, suffer from difficulties in capturing long short-term dependencies and effectively utilizing samples. Firstly, audio signal detection and classification need to classify audio signals and detect their onset and offset times; therefore, obtaining long short-term dependencies is necessary. The methods based on RNNs have high time complexity and dilated convolution-based methods suffer from the “gridding issue” challenge; thus, the HDC-Inception module is proposed to efficiently extract long short-term dependencies. Combining the advantages of the Inception module and a hybrid dilated convolution (HDC) framework, the HDC-Inception module can both alleviate the “gridding issue” and obtain long short-term dependencies. Secondly, datasets have large numbers of silent segments and too many samples for some signal types, which are redundant and less difficult to detect, and, therefore, should not be overly prioritized. Thus, selecting effective samples and guiding the training based on them is of great importance. Inspired by support vector machine (SVM), combining soft margin SVM and cross-entropy loss (CE loss), the soft margin CE loss is proposed. Soft margin CE loss can adaptively select support vectors (effective samples) in datasets and guide training based on the selected samples. To utilize datasets more sufficiently, a hybrid CE loss is proposed. Using the benefits of soft margin CE loss and CE loss, hybrid CE loss guides the training with all samples and gives weight to support vectors. Soft margin CE loss and hybrid CE loss can be extended to most classification tasks and offer a wide range of applications and great potential.

The inseparability criterion provides a straightforward and efficient method for identifying and quantifying two-mode Gaussian quantum entanglement, making it a crucial tool in quantum optics experiments. However, it is crucial to recognize that the inseparability criterion serves only as a sufficient condition for entanglement assessment, thereby posing a risk of missed detection during evaluation. This paper investigates the use of the inseparability criterion in assessing two-mode squeezed states, with a particular focus on examining missed entanglement detection due to entanglement asymmetry. The results show that when decoherence symmetrically affects both modes, the inseparability criterion effectively detects entanglement. In contrast, when this symmetry is broken, the criterion may fail to identify entanglement, with the likelihood of missed detection increasing with increasing asymmetry. By comparing these results with the positive partial transpose criterion, which serves as a necessary and sufficient condition, the occurrence of missed detections by the inseparability criterion is confirmed. Our research not only provides valuable insights into the application of the inseparability criterion in quantum information tasks but also deepens the understanding of its operational principles and limitations.

In this study, a method for the active shape control for carbon fiber-reinforced polymer (CFRC) reflectors using piezoelectric lead zirconate titanate (PZT) actuators is proposed. According to this method, a finite element model considering higher transverse shear deformation with independent voltage degrees of freedom is formulated by the Hamilton principle. An optimal shape controller that minimizes the discrete root mean square (RMS) error of a reflecting surface is applied. Then, the optimal arrangements of the PZT actuators are determined by numerical optimization methods, which are developed by modifying the classical Genetic Algorithm, with both single and multi-objective optimizations being studied. In the single optimization formulation, the number of actuators is considered as a constraint, and the RMS error of the reflector is regarded as the optimizing target. A hybrid method that combines the gradient projection method with an adaptive Genetic Algorithm is proposed to solve this problem. In the multi-objective optimization, the residual RMS errors and power consumption of the actuators are considered as the optimization targets. Pareto optimal solutions are obtained by an improved multi-objective Genetic Algorithm. Numerical examples are provided to show the effectiveness of the proposed methods.

The inseparability criterion provides a straightforward and efficient method for identifying and quantifying two-mode Gaussian quantum entanglement, making it a crucial tool in quantum optics experiments. However, it is crucial to recognize that the inseparability criterion serves only as a sufficient condition for entanglement assessment, thereby posing a risk of missed detection during evaluation. This paper investigates the use of the inseparability criterion in assessing two-mode squeezed states, with a particular focus on examining missed entanglement detection due to entanglement asymmetry. The results show that when decoherence symmetrically affects both modes, the inseparability criterion effectively detects entanglement. In contrast, when this symmetry is broken, the criterion may fail to identify entanglement, with the likelihood of missed detection increasing alongside rising asymmetry. By comparing these results with the positive partial transpose criterion, which serves as a necessary and sufficient condition, the occurrence of missed detections by the inseparability criterion is confirmed. Our research not only provide valuable insights into the application of the inseparability criterion in quantum information tasks but also deepens the understanding of its operational principles and limitations.