Measuring the Gain of a Microchannel Plate/Phosphor Assembly Using a Convolutional Neural Network

Michael Jones, Matthew Harvey, William Bertsche, Andrew James Murray, Robert B. Appleby

Research output: Contribution to journalArticle

Abstract

This paper presents a technique to measure the gain of a single-plate micro-channel plate (MCP)/phosphor assembly by using a convolutional neural network to analyse images of the phosphor screen, 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 measurements of the charge of bunches after amplification by the MCP, we were able to deduce the gain curve of the MCP.
Original languageEnglish
Article number8886588
Pages (from-to)2430-2434
Number of pages5
JournalIEEE Transactions on Nuclear Science
Volume66
Issue number12
DOIs
Publication statusPublished - 29 Oct 2019
Externally publishedYes

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microchannel plates
Microchannels
Phosphors
phosphors
assembly
Neural networks
Electrons
particle intensity
Charge coupled devices
Amplification
background noise
charge coupled devices
electrons
curves

Cite this

Jones, Michael ; Harvey, Matthew ; Bertsche, William ; Murray, Andrew James ; Appleby, Robert B. / Measuring the Gain of a Microchannel Plate/Phosphor Assembly Using a Convolutional Neural Network. In: IEEE Transactions on Nuclear Science. 2019 ; Vol. 66, No. 12. pp. 2430-2434.
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Measuring the Gain of a Microchannel Plate/Phosphor Assembly Using a Convolutional Neural Network. / Jones, Michael; Harvey, Matthew; Bertsche, William; Murray, Andrew James; Appleby, Robert B.

In: IEEE Transactions on Nuclear Science, Vol. 66, No. 12, 8886588, 29.10.2019, p. 2430-2434.

Research output: Contribution to journalArticle

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