Disorder induced phase transition in magnetic higher-order topological insulator: A machine learning study<xref rid="cpb_28_11_117301_fn1" ref-type="fn">*</xref><fn id="cpb_28_11_117301_fn1"><label>*</label><p>Project supported by the National Natural Science Foundation of China (Grant No. 11822407) and the Priority Academic Program Development of Jiangsu Higher Education Institutions, China.</p></fn>

Disorder induced phase transition in magnetic higher-order topological insulator: A machine learning study**

Project supported by the National Natural Science Foundation of China (Grant No. 11822407) and the Priority Academic Program Development of Jiangsu Higher Education Institutions, China.

Su Zixian¹, Kang Yanzhuo², Zhang Bofeng¹, Zhang Zhiqiang^{1, †}, Jiang Hua^{1, 3}

Neural network structure. The input is the real space wave function distribution. There exist two layers of convolution and two layers of full connection to reach the output layer. The size of the convolution kernel and the number of neurons in the full connection layer are marked in the figure.