Measuring the Gain of a Micro-Channel Plate/Phosphor Assembly Using a Convolutional Neural Network

This article presents a technique to measure the gain of a single-plate microchannel plate (MCP)/phosphor assembly by using a convolutional neural network to analyze the images of the phosphor screen, which are recorded by a charge-coupled device. The neural network reduces the background noise in the images sufficiently that individual electron events can be identified. From the denoised images, an algorithm determines the average intensity recorded on the phosphor associated with a single electron hitting the MCP. From this average single-particle intensity, along with the measurements of the charge of bunches after amplification by the MCP, we were able to deduce the gain curve of the MCP.