Python-based Simulation Optimization Method for Superconducting Quantum Interference Devices
The optimization study of superconducting quantum interference devices aims to enhance their performances in detecting minute magnetic flux changes.A Python-based simulation framework is built,the SuperScreen,Numpy,and Matplotlib libraries are used to simulate the devices and optimize their performance.This framework supports the simulation of various superconducting quan-tum interference devices(SQUID)shapes,including an algorithm to simulate polygon modeling.The magnetic response of SQUID superconducting films under non-uniform external magnetic fields is analyzed by the simulation,and the vector magnetic fields inside and outside the films are calculated.Additionally,the continuous physical space is transformed into the computational model through meshing techniques,it perhaps provides the solution of physical equations.Simulation results show that the optimized SQUID meets the requirements for high-precision magnetic field detection,providing a theoretical and technical support for the design of supercon-ducting devices.
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