MATH 770 Quantum Inspired Tensor Network Computing
This course explores tensor computing techniques for multi-dimensional data representation and manipulation. It covers tensor decompositions, contractions, and algebra, with applications to solving partial differential equations using tensor networks. Originating in quantum many-body physics, these techniques leverage principles used in quantum mechanics, such as low-rank decompositions and entanglement structure, making them highly efficient for compressing and manipulating high-dimensional data. Hands-on Python implementation emphasizes applications in machine learning and scientific computing.
Distribution
(3,0,3)Offered
Fall