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Automatic spectrum recognition system for charge state analysis in electron cyclotron resonance ion sources

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Abstract

The Electron Cyclotron Resonance (ECR) ion source is a critical device for producing highly charged ion beams in various applications. Analyzing the charge-state distribution of the ion beams is essential, but the manual analysis is labor-intensive and prone to inaccuracies due to impurity ions. An automatic spectrum recognition system based on intelligent algorithms was proposed for rapid and accurate chargestate analysis of ECR ion sources. The system employs an adaptive window-length Savitzky–Golay (SG) filtering algorithm, an improved automatic multiscale peak detection (AMPD) algorithm, and a greedy matching algorithm based on the relative distance to accurately match different peaks in the spectra with the corresponding charge-state ion species. Additionally, a user-friendly operator interface was developed for ease of use. Extensive testing on the online ECR ion source platform demonstrates that the system achieves high accuracy, with an average root mean square error of less than 0.1 A for identifying charge-state spectra of ECR ion sources. Moreover, the system minimizes the standard deviation of the first-order derivative of the smoothed signal to 81.1846 A. These results indicate the capability of the designed system to identify ion beam spectra with mass numbers less than Xe, including Xe itself. The proposed automatic spectrum recognition system represents a significant advancement in ECR ion source analysis, offering a rapid and accurate approach for charge-state analysis while enhancing supply efficiency. The exceptional performance and successful implementation of the proposed system on multiple ECR ion source platforms at IMPCAS highlight its potential for widespread adoption in ECR ion source research and applications.

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Availability of Data and Materials

The data that support the findings of this study are openly available in Science Data Bank at https://www.doi.org/10.57760/sciencedb.08240 and https://cstr.cn/31253.11.sciencedb.08240.

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Authors and Affiliations

  1. Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, 730000, China

    Rui Wang, Cheng Qian, Yu-Hui Guo, Peng Zhang & **-Dou Ma

  2. University of Chinese Academy of Sciences, Bei**g, 100049, China

    Rui Wang

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  1. Rui Wang
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  2. Cheng Qian
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  3. Yu-Hui Guo
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Rui Wang and Cheng Qian. Yu-Hui Guo contributed to the key revisions of the manuscript. Peng Zhang and **-Dou Ma guided some physical aspects of the experiments. The first draft of the manuscript was written by Rui Wang and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Yu-Hui Guo.

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Wang, R., Qian, C., Guo, YH. et al. Automatic spectrum recognition system for charge state analysis in electron cyclotron resonance ion sources. NUCL SCI TECH 34, 178 (2023). https://doi.org/10.1007/s41365-023-01326-9

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