Quantum Algorithms for Sparse Problems
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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….
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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….
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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….
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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….
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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,….