Photoelectric Detection System and Machine Learning Recognition Method of Its Detection Images

In the photoelectric detection system, the photoelectric detector can convert the optical signal to be measured into a current signal, and the current amplifier transforms the current signal output by the detector into a voltage signal for amplification. In this study, the photo-multiplier tube (PMT) is selected as the photoelectric detector. Compared with other photoelectric detectors, it can obtain higher internal gain, higher sensitivity, and better response performance. The current amplifier is prepared by pre-amplifier and voltage amplifier. In order to capture photoelectric signals well, a large-format scanning system is set up to design each component module, control module, and host computer module of the system. Besides, a machine learning-based algorithm is proposed, namely semi-supervised manifold image recognition algorithm, which is used for identify photoelectric detection images. In the test process, the printed circuit board (PCB) and sapphire material are firstly used as the substrate of the current amplifier, and their influences in the circuit are compared. The peak value of the output noise of each substrate circuit is around 2.8 mV when the input of the current amplifier is short-circuited. Then, the signal gain and signal bandwidth of the photoelectric detection system remain stable when there is no optical signal input. During the process of changing the system signal gain ratio, the noise output of the system is the lowest when the voltage of PMT is 0.50 V and the current amplifier gain is set to 2.2 × 105 V/A. The proposed recognition algorithm can identify different types of targets well. After the image is projected into a two-dimensional space by the algorithm, the distance between classes increases, and the targets in the class promote aggregation, thereby enhancing the identify-ability between samples.

Design of Quantum Communication Broadband Amplifier Based on Photoelectric Diode

according to the special requirements of quantum optics experiments, through the optimum design of broadband low noise amplifier circuit, this paper developed a broadband low noise photoelectric detector. We focus on the analysis of the factors affecting the photoelectric detector gain, bandwidth and noise, by a suitable choice of the photodiode, a sampling resistor, feedback resistor and capacitor, the broadband low noise photoelectric detector. Experiments show that, this circuit can be used for broadband low noise quantum communication circuit.

Simulation Analysis of Excess Noise Factors for Photomultiplier Tube

Noise is one of the most significant indicators to measure the performance of the PMT, which is regarded as a photoelectric detector. Moreover, the excess noise factor F is an important parameter to describe the noise. Excess noise factor expressions for PMT in different situations are derived and analyzed by simulation in this paper. Some numerical simulations are made to obtain the maximum and minimum excess noise factor F and the changing trend of F with each parameter. From the analysis, we can minimize the noise for PMT to increase the detection precision as a photoelectric detector.