MATLAB Resources

TA Training Material Fall 2017

The training outline describing licensing and overall features of MATLAB can be downloaded below.

Additional information, such as how to create basic column and row vectors and matrices can be downloaded either as a PDF file or as a MATLAB live script below.

A basic tutorial of matlab's functions is also attached.(Basic_Matlab_Stuff.mlx , Basic_Matlab_stuff.pdf)

TA Training Material Fall 2018

The TA training for Fall of 2018 covered some more practical MATLAB concepts; specifically, how to use MATLAB to solve certain fundamental physics problems. The topics covered were Finite-Difference, Ordinary Differential equations, and Eigenvalue problems( Coupled Oscillators and Quantum Well Potentials).

Basic Notes on Data Plotting and Fitting in MATLAB for Physical Science

These notes familiarizes the reader with plotting and data fitting in MATLAB. In the first part, a data set representing a radioactive decay is generated and displayed with plots widely used in data analysis. Next, the data is fitted with a script which plots the fit results, calculates the fit parameters and provides numerical data indicating the quality of the fit. The data will be fit to linear, non-linear and custom models.

Advanced Notes on Data Fitting for Physical Science

These notes outline data fitting in the physical sciences using MATLAB’s versatile and powerful ‘fit’ function which utilizes a least-squares algorithm. The emphasis is on how to use the fit function and interpreting the fit results; explanations on the theory of statistics are kept to a minimum. (Sources on MATLAB and Statistics are listed at the end.) The entire fitting procedure is presented as a MATLAB Live Script, which can be modified to be used for any data as long the input is in the form of column vectors x, y, sig_y. A PDF and HTML version of the Live Script has also been provided on the page listed above.

MATLAB Linear Fitting App

We have integrated the above files into a convenient MATLAB app which allows fitting data to a first order y = p1*x + p2 and second order polynomial, y = p1*x^2 + p2*x + p3. The app displays the fitted results, the goodness of fit and provides plots and histogram of the weighted residues, the weighted residues squared as well as the fit's Chi Squared distribution and its error surfaces. Existing MATLAB variables can be used for the fit or sample data can be generated in the app. A link and a screen shot is shown below.

Download MXP LSQFit MATLAB app.