Quantum Algorithms for Sparse Problems
1. Introduction In many real-world applications—from data science and machine learning to physics and engineering—problems are sparse. This means most of the data or matrix elements involved are zero or….
1. Introduction In many real-world applications—from data science and machine learning to physics and engineering—problems are sparse. This means most of the data or matrix elements involved are zero or….
1. Introduction In classical computation, random walks on graphs are a powerful tool used in algorithms, search, and probability theory. They form the backbone of important applications in web page….
1. Introduction to PDEs Partial Differential Equations (PDEs) are foundational in modeling dynamic systems that evolve over time and space. They are used extensively across fields such as physics (wave….
Knowledge graphs are structured representations of real-world entities and their relationships, enabling machines to understand, infer, and reason about data semantically. These graphs are central to search engines, recommendation systems,….