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9–12 Sept 2025
Fudan University, Shanghai, China
Europe/Vienna timezone

Overcoming Plasma-Induced Noise: Statistical Optimization of α-Particle Detection in EXL-50U p-B Reactions

10 Sept 2025, 15:30
45m
Auditorium Hall HGX 102 (Guanghua Twin Tower) (Fudan University, Shanghai, China)

Auditorium Hall HGX 102 (Guanghua Twin Tower)

Fudan University, Shanghai, China

220 Handan Road, Yangpu District, Shanghai, China 邯郸路 220 号 复旦大学
Oral (Short) Signal Processing and Anomaly Detection Poster session with tea

Speaker

zhi li (ENN Science and Technology Development Co., Ltd.)

Description

Accurate measurement of charged fusion products in magnetically confined plasmas faces significant challenges due to plasma radiation exposure, electromagnetic interference, thermal loads, and background bombardment by electrons/ions, which generate substantial noise while yielding sparse signals. To address these issues, advanced solutions are required beyond conventional detector design and calibration, including signal discrimination techniques, machine learning-based noise suppression for enhanced signal-to-noise ratios, and statistical analysis to improve signal significance. This study focuses on the detection simulation of α-particles generated by proton-boron (p-B) fusion reactions in the ENN-operated ST-type device EXL-50U. By employing Monte Carlo simulations, we systematically evaluate the expected α-particle signals, reducible backgrounds (e.g., electromagnetic interference, plasma fluctuations, and energetic protons/electrons/photons), and irreducible backgrounds (e.g., high-energy proton pileup events and fortuitously energized helium impurities). The signal significance of measurable fusion products is quantified using statistical metrics, providing critical insights for optimizing α-particle diagnostics in p-B fusion experiments under high-background conditions.

Speaker's email address lizhiz@enn.cn
Speaker's Affiliation ENN Science and Technology Development Co., Ltd.
Member State or International Organizations China

Author

zhi li (ENN Science and Technology Development Co., Ltd.)

Presentation materials