## 2016 Paper

In Oct 2016 we published a paper in IEEE Transactions on Microwave Theory and Techniques. This paper describes a method of using eigenfunction expansion in vacuum cavity modes to compute the resonance frequencies and field patterns of complex, cylindrically symmetric cavities. In the zip file are found MATLAB scripts that can be used to compute the resonance frequencies and field patterns of modes in two types of cylindrical cavities: one is a simple cavity with two identical dielectrics, and the other is a complex cavity akin to that from the paper. The cavity described in the paper contains multiple dielectrics as well as Rexolite throughout the cavity that made the dielectric constant of the cavity spatially complicated. A readme file is found among the other files that contains a detailed description of how to run the MATLAB scripts.

Download a zip file with all the programs: Supplementary-Codes-2016.zip

The zip file contains these individual files:

- Complex_Cavity.m
- Cplot.m
- D1.m
- Extrapolate_Freq.m
- Field_Patterns.m
- README.txt
- Simple_Cavity.m
- cyl2cartvec.m
- searchr.m

## 2022 Paper

In Jan 2022 we published another paper in IEEE Transactions on Microwave Theory and Techniques on the topic of resonant microwave cavities. This paper describes a method for using machine learning in the form of a neural network to predict the quasi TE_{011} resonant cavity mode of a "double stacked dielectric resonant" cavity. The following are supplementary files needed to run the neural network (in Python) along with the FEniCS program which uses FEniCS (in Python) to solve for the quasi TE_{011} mode using the finite element method (which is slower but more accurate the neural network itself). A readme file is included which contains a detailed description of all the files.

Download a zip file with all the programs: Supplementary-Codes-2022.zip (32 MB, due to the size of the .h5 files)

The zip file contains these individual files:

- coeff.csv
- coefficients.csv
- coeffplot.py
- coefModelAugmented256.h5
- environment_fenics_linux.yml
- freqModelAugmented1234.h5
- ML_eval_and_plot.py
- ML_eval_from_csv.py
- MLenvironment_linux.yml
- Parameter_plots.py
- README.txt
- solveTE011v4.py
- Stacked DRs w rexolite.ipynb
- ultimateTElist.csv