Numerical Linear Algebra Toolkit Purpose Provides high-performance numerical linear algebra operations for scientific computing and mathematical analysis. Capabilities - Matrix decompositions (LU, QR, SVD, Cholesky, Schur) - Eigenvalue/eigenvector computation - Sparse matrix operations - Iterative solvers (CG, GMRES, BiCGSTAB) - Condition number estimation - Error analysis and bounds Usage Guidelines 1. Decomposition Selection : Choose appropriate factorization for the problem 2. Sparsity Exploitation : Use sparse formats for large sparse matrices 3. Iterative Methods : Apply iterative solver…