Quantum singular value transformation

Quantum singular value transformation is a framework for designing quantum algorithms. It encompasses a variety of quantum algorithms for problems which can be solved with linear algebra, including Hamiltonian simulation, search problems, and linear system solving. It was introduced in 2018 by András Gilyén, Yuan Su, Guang Hao Low, and Nathan Wiebe, generalizing algorithms for Hamiltonian simulation of Guang Hao Low and Isaac Chuang inspired by signal processing.

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