Day 256: Linear Algebra with NumPy

Learning Objectives

• •**Solve eigenvalue problems** using `np.linalg.eig` and `np.linalg.eigh`
• •**Solve linear systems** with `np.linalg.solve` and understand when to use it
• •**Compute matrix decompositions** (SVD, QR, Cholesky, LU)
• •**Calculate matrix properties** (determinant, trace, rank, condition number)
• •**Find energy levels** of quantum systems numerically
• •**Verify orthonormality** and completeness of eigenstates
• •**Choose appropriate algorithms** for specific problem types

Today's Schedule (7 hours)