Neural network applications to improve drift chamber track position measurements-Reference-Cited by-同舟云学术

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Neural network applications to improve drift chamber track position measurements

Published:2024-07 Issue: Volume:1064 Page:169404
ISSN:0168-9002
Container-title:Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
language:en
Short-container-title:Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

Author:

Palo D.^ORCID,Molzon W.^ORCID

Funder

US Department of Energy

Publisher

Elsevier BV

Reference15 articles.

1. Track fitting with multiple scattering: A new method;Billoir;Nucl. Instrm. Meth. A,1984

2. Garfield++ — simulation of ionisation based tracking detectors;Schindler,2018

3. Performances of the MEG II cylindrical drift chamber;Afanaciev,2023

4. Particle Detection with Drift Chambers;Blum,1993

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A search for $$\upmu ^+ \rightarrow \textrm{e}^+ \upgamma $$ with the first dataset of the MEG II experiment;The European Physical Journal C;2024-03-01

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