Linear System Solver (Direct Methods)

Project Overview

• Architected a comprehensive linear system solver in Python, implementing core numerical methods: Forward Substitution, Back Substitution, and Gaussian Elimination.
• Engineered algorithm logic to transform general, unstructured matrices into upper/lower triangular forms to minimize computational overhead.
• Optimized for numerical stability, handling pivoting and edge cases in matrix inversion and system solving for engineering applications.
• Performed complexity analysis on solver performance, comparing iterative vs. direct methods for large-scale physical modeling.

Tech Stack

• Language: Python
• Libraries: NumPy, Vectorized Operations