This course bridges classical and quantum frameworks. It begins with central-force problems and oscillatory motion, then transitions from modern physics to quantum mechanics for undergraduate students.
A laboratory course introducing key concepts in optics, modern physics, and mechanics through selected foundational experiments.
This course builds a strong foundation in linear algebra and probability theory, covering vector spaces, eigenvalues, matrix decompositions, random variables, and stochastic processes. Students gain the mathematical tools essential for signal processing, data science, and engineering applications.
This course develops the mathematical foundations essential for modern physics covering linear algebra (vector spaces, eigenvalues, diagonalization, SVD) and probability theory (random variables, stochastic processes, power spectral density). It equips students with the formal tools underlying quantum mechanics, statistical mechanics, and condensed matter physics.
This course introduces core numerical methods for solving linear systems, interpolation, and differential equations, including Gauss elimination, LU decomposition, Jacobi iteration, SVD, cubic spline interpolation, bisection, and Runge-Kutta methods. Students gain practical, computational tools essential for scientific computing and engineering problem-solving.