Cyclotron radiation emission spectroscopy signal classification with machine learning in project 8
Cyclotron radiation emission spectroscopy signal classification with machine learning in project 8
复制标题
项目 8 中使用机器学习的回旋辐射发射光谱信号分类
DOI:
10.1088/1367-2630/ab71bd
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发表时间:
2020
影响因子:
3.3
通讯作者:
Guigue, M
中科院分区:
文献类型:
--
作者:
Esfahani, A Ashtari;Böser, S;Buzinsky, N;Cervantes, R;Claessens, C;Viveiros, L de;Fertl, M;Formaggio, J A;Gladstone, L;Guigue, M
The cyclotron radiation emission spectroscopy (CRES) technique pioneered by Project 8 measures electromagnetic radiation from individual electrons gyrating in a background magnetic field to construct a highly precise energy spectrum for beta decay studies and other applications. The detector, magnetic trap geometry and electron dynamics give rise to a multitude of complex electron signal structures which carry information about distinguishing physical traits. With machine learning models, we develop a scheme based on these traits to analyze and classify CRES signals. Proper understanding and use of these traits will be instrumental to improve cyclotron frequency reconstruction and boost the potential of Project 8 to achieve world-leading sensitivity on the tritium endpoint measurement in the future.
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DOI:
10.1007/bf01294491
发表时间:
1992
期刊:
Zeitschrift für Physik A Hadrons and Nuclei
影响因子:
--
作者:
A. Picard;H. Backe;J. Bonn;B. Degen;R. Haid;A. Hermanni;P. Leiderer;A. Osipowicz;E. Otten;M. Przyrembel;M. Schrader;M. Steininger;C. Weinheimer
通讯作者:
C. Weinheimer
DOI:
--
发表时间:
2015
期刊:
影响因子:
--
作者:
J. Kofron
通讯作者:
J. Kofron
影响因子:
3.1
作者:
Esfahani, A. Ashtari;Bansal, V.;Böser, S.;Buzinsky, N.;Cervantes, R.;Claessens, C.;de Viveiros, L.;Doe, P. J.;Fertl, M.;Formaggio, J. A.
通讯作者:
Formaggio, J. A.
影响因子:
5.8
作者:
Carpenter, Bob;Gelman, Andrew;Riddell, Allen
通讯作者:
Riddell, Allen
DOI:
--
发表时间:
2017
期刊:
影响因子:
--
作者:
Benjamin LaRoque
通讯作者:
Benjamin LaRoque