Applying Deep Learning Technique to Chiral Magnetic Wave Search

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.

6 pages, 6 figures. Published in Chin.Phys.C

References in corpus (9)

• The Chiral Magnetic Effect
• Gravitational Anomaly and Transport
• Chiral Magnetic Wave
• Quantum Anomalies in Dense Matter
• Novel quantum phenomena induced by strong magnetic fields in heavy-ion collisions
• Observation of charge asymmetry dependence of pion elliptic flow and the possible chiral magnetic wave in heavy-ion collisions
• Chiral magnetic effect reveals the topology of gauge fields in heavy-ion collisions
• Chiral electric separation effect in the quark-gluon plasma
• New developments in relativistic magnetohydrodynamics