Improvement of mobility spectrum algorithm based on Hall measurement

Mobility spectrum analysis is a data analysis algorithm based on Hall measurement, which aims to analyze the spectrum of semiconductor carriers. By collecting the semiconductor conductance tensor analysis in the variable magnetic field, the electron and hole transport behavior in the material can be studied. However, the traditional maximum entropy mobility spectrum algorithm has some limitations, such as sensitivity to data noise and uncertainty, and high computational complexity. To solve these problems, this paper proposes two key improvements. Firstly, the entropy information containing probability values is introduced into the change matrix to improve the robustness and accuracy of the algorithm. Secondly, the adaptive step factor is adopted. Through the simulation verification of various situations, the results show that the improved algorithm can not only better deal with noise and uncertainty, but also improve the evaluation indexes such as fitting degree, Gaussian peak parameter and convergence factor under the same number of iterations, which is more meaningful in the material research of semiconductor field.