Algorithms for Solving Inverse Problems in Physics – Training Services

Algorithms for Solving Inverse Problems in Physics – Training Services provides specialized training on computational methods for determining unknown system parameters from measured data. The course covers linear and nonlinear inverse problems, regularization techniques, optimization algorithms, and Bayesian approaches. Participants will use Python and MATLAB to implement algorithms for parameter estimation, model fitting, and reconstruction of physical quantities from indirect measurements. Emphasis is placed on numerical stability, error analysis, and convergence of solutions. Case studies highlight applications in geophysics, medical imaging, optics, and material characterization. Hands-on sessions provide practical experience in coding inverse problem algorithms, analyzing results, and interpreting physical parameters. By the end, participants will be proficient in applying computational algorithms to solve complex inverse problems in physics.