Applied Physics B最新文献

We report a sensitive laser absorption diagnostic method for shock tube experiments using a multipass configuration with a single-line spot pattern. The multipass setup consists of two silver-coated concave mirrors, which are placed outside the optical windows of the shock tube. The multipass configuration increases the effective path length by a factor of 31. All the reflected beams are aligned within a single plane that is perpendicular to the propagation direction of the shock wave, mitigating the Schlieren and beam steering effects. We validated the approach by measuring shock-heated gases behind reflected shock waves using tunable laser absorption spectroscopy of water vapor at 7447.48 cm^− 1. Our approach enables sensitive species detection for high-temperature shock tube/laser absorption experiments.

In discrete variable quantum key distribution (DV-QKD), the homodyne detection method is frequently employed for its simplicity in use, effectiveness in terms of error correction, and suitability with contemporary optical communication systems. Being a coherent detection method, it relies on a local oscillator whose frequency is matched to that of the transmitted carrier’s signal. In this paper, we evaluate a free space optical (FSO) DV-QKD system based on the KMB09 protocol using Homodyne detection under random phase fluctuation and depolarizing noise error. We present simulation results for system efficiency and quantum bit error rate (QBER) for the proposed model. An obtained efficiency ((25%)) for our proposed DV-QKD system model shows that under atmospheric turbulence and noise effect and it is in line with the available analytical results. However, the inclusion of random phase fluctuation and noise led to higher-than-normal QBER which is anticipated in a real-world scenario.

This study investigates the influence of amplified spontaneous emission (ASE) on the output characteristics of a Master Oscillator Power Amplifier (MOPA) system, with particular attention to the temporal dependence of the signal-to-noise ratio (SNR). The time delay between the ASE generated in the power amplifier and the laser pulse emitted by the master oscillator was varied over a wide range, from − 36 to + 24 ns. A positive delay corresponds to the input signal entering the amplifier before the onset of ASE. Temporal profiles of the ASE, the input pulse, and the amplified output signal were recorded and analyzed. The results demonstrate that the temporal alignment of the input signal with the leading edge of the ASE critically affects the output power and the efficiency of population inversion utilization. The maximum output power of 3.87 watts was achieved at a time delay of plus 4.7 ns, when the peak of the input pulse coincided with the ASE front. Quantitative estimates of the ASE contribution to the output signal were obtained, enabling an assessment of the SNR under various timing conditions. These findings provide practical recommendations for optimizing synchronization in MOPA-based laser systems to maximize output contrast and minimize noise.

The present work demonstrates shot-to-shot calibrated imaging thermometry in a spray-flame-synthesis (SFS) process by utilizing two-line atomic fluorescence (TLAF) of indium atoms. Measurements in this highly turbulent, particle-laden flame were accomplished by implementing two optical parametric oscillators (OPOs) designed for pulsed operation in order to generate radiation with the required excitation wavelengths. The OPOs were optimized towards a narrow-band spectral output while maintaining high tunability. A linear OPO design was realized, which is capable to produce laser radiation with a bandwidth as narrow as 148 pm. These laser sources were employed to excite the ({5}^{2}{P}_{1/2}to {6}^{2}{S}_{1/2}) transition at 410.13 nm and the ({5}^{2}{P}_{3/2}to {6}^{2}{S}_{1/2}) transition at 451.13 nm using to two coplanar light sheets formed, one from each OPO. As this TLAF-method requires calibration, the light sheets were split by a 50:50 beam splitter and guided through two burners simultaneously, one being a calibration flame with a known temperature profile and the other one being the flame of a spray-flame-synthesis burner. By recording the fluorescence signals from both flames in the same camera frame, calibration could be conducted for each single shot, which allows to compensate for shot-to-shot spatial irradiance fluctuations of the OPOs. The shown TLAF-measurement set-up thus enables highly reliable and accurate single-shot measurements of flame temperatures in SFS.

We report on the efficient delivery of sub-picosecond laser pulses with high peak and high average powers through a home-made 7.5 m long tubular inhibited-coupling guiding hollow-core photonic-crystal fiber (IC-HCPCF). The experiments were performed using an ultrafast laser generating pulses with durations between 430 fs and 560 fs at a central wavelength of 1030 nm. Pulses with an energy of either 263 µJ or 150 µJ were coupled into the fiber at average powers of either 48 W or 95 W, respectively. In both cases, the transmittance through the fiber was measured to exceed 85% without detectable distortion of the temporal pulse shapes or damage to the fiber.

The paper is devoted to an original method of time-domain fluorescence molecular lifetime tomography (FMLT) based on asymptotic approximation to the fluorescence source function. Such an approximation helps to simplify the expressions that describe the FMLT reconstruction model in the time domain and to formulate the linear inverse problem for a generalized fluorescence parameter distribution function. The method firstly solves this problem and then separates distributions of the fluorophore absorption coefficient and the fluorescence lifetime from the generalized function. The paper analyzes results the authors have obtained during last 5 years in their testing the method in numerical and physical experiments. The method is inferred to be quite promising and directions of further research for its verification as a sub-millimeter resolution method are outlined.

In this work, we present a precise mathematical solution that explains how two two-level atoms interact with a multiphoton electromagnetic field inside a single-mode cavity, while specifically considering the Stark shift effect. The system is initialized with the field in a coherent state and both atoms in their excited states. The resulting model incorporates the changes in atomic energy levels induced by the Stark shift and serves as a transmission channel for the quantum teleportation of a bipartite state. Our study focuses on the combined influence of the Stark shift and photon number on teleportation fidelity and the preservation of quantum resources such as entanglement and coherence. The results reveal the existence of critical thresholds for these two parameters, below which the quality of teleportation degrades significantly. Additionally, we analyze the impact of these parameters on the Quantum Fisher Information (QFI), a key quantity for assessing the accuracy of parameter estimation after teleportation. A direct comparison between QFI and the Hilbert-Schmidt speed is also conducted to better understand the latter’s role in quantum estimation tasks.

Here, we introduce an optical interferometric microfiber sensor for in situ measurement of flow velocity in a microfluidic chip. The interferometric sensor is fabricated by fusing and tapering a standard single-mode optical fiber, and then embedded into a microfluidic chip, where the sensor element intersects vertically with the liquid flow channel. As the liquid flows through the channel, it applies pressure to the sensor’s sensitive surface, causing a wavelength shift in the transmission spectrum proportional to the flow velocity. Real-time monitoring and analysis of this wavelength shift enable precise flow velocity measurement. Results show that the proposed sensor chip exhibits excellent measurement performance within a average flow velocity range of 0–30.391 cm/s, with a average sensitivity of 0.094 nm/(cm/s). The resolution of average flow velocity measurement can reach 1.2 cm/s and the accuracy exceeds 90%.

Uranium polymetallic ores (UPOs) are strategic emerging mineral resources that possess both significant economic value and strategic importance. In this study, femtosecond laser-induced breakdown spectroscopy (LIBS) was combined with four machine learning algorithms—partial least squares regression (PLSR), principal component analysis (PCA), support vector machine (SVM), and linear discriminant analysis (LDA)—to perform quantitative analysis of uranium (U) concentration and classification of UPO samples. The concentrations of U in six UPO samples were determined using a high-purity germanium gamma ray spectrometer, which served as reference values. Three spectral normalization methods were applied to preprocess the raw spectra and assess the impact of preprocessing on model performance. Due to the significant matrix effect, the intensities of U characteristic emission lines did not exhibit a clear linear correlation with U concentration, making the univariate analysis impossible. However, the multivariate regression model based on PLSR algorithm was employed to mitigate the matrix effect, enabling accurate U quantification in UPOs. The leave-one-out cross-validation results showed that, with the exception of sample 1#, the combination of femtosecond LIBS and PLSR reliably predicted U concentration in the other samples, with relative standard deviation and mean relative error maintained below 9.48% and 7.30%, respectively. Furthermore, PCA was applied to the whole LIBS spectral dataset for dimensionality reduction and feature vector reconstruction. The resulting principal components were used as inputs for SVM and LDA classification algorithms to distinguish among the six ore types. The SVM model achieved a classification accuracy of 91.67%, while LDA demonstrated a superior classification performance with 100% accuracy. Overall, this study demonstrates that the combination of femtosecond LIBS with machine learning algorithms enables effective quantitative analysis of U and accurate classification of UPOs.

The rapid proliferation of commercial unmanned aerial vehicles (UAVs) poses growing security, safety, and privacy challenges. This paper presents a novel frequency-domain analysis methodology to extract mechanical signatures of UAVs using backscattered optical signals from drone propellers. Through both simulations and experimental validation, the feasibility of retrieving key mechanical signatures, including the propeller's rotational speed (RPM) and the number of blades, was demonstrated. These signatures are a first step towards the real-time identification of drone models and provide insights into drone’s flight behavior. The methodology, tested here with small toy drones, offers promise for real-world deployment of drone monitoring systems, complementing traditional detection techniques by operating in various atmospheric conditions. Additionally, harmonic and frequency peak analysis may allow for future improvements in trajectory tracking and payload detection. This work opens new possibilities for integrating lidar-based UAV characterization into both civilian and military airspace security frameworks.