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arXiv · 2407.00926

Applying Deep Learning Technique to Chiral Magnetic Wave Search

Yuan-Sheng Zhao·Xu-Guang Huang
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Abstract

The chiral magnetic wave (CMW) is a collective mode in quark-gluon plasma originated from the chiral magnetic effect (CME) and chiral separation effect. Its detection in heavy-ion collisions is challenging due to significant background contamination. In Ref.[1], we have constructed a neural network which can accurately identify the CME-related signal from the final-state pion spectra. In this paper, we generalize such a neural network to the case of CMW search. We show that, after a updated training, the neural network can effectively recognize the CMW-related signal. Additionally, we assess the performance of the neural network compared to other known methods for CMW search.

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Yuan-Sheng Zhao, Xu-Guang Huang. 2024-07-01. Applying Deep Learning Technique to Chiral Magnetic Wave Search. https://doi.org/10.1088/1674-1137%2Fad4c5d

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