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Quantum Signal Processing

Lin Lin Professor, University of California-Berkeley, Dept of Mathematics Faculty Scientist, Mathematics Group Lawrence Berkeley National Laboratory Abstract: Quantum Signal Processing (QSP) is a revolutionary technique that uses a product of unitary matrices to represent polynomials, with numerous applications in quantum computing. In this talk, I will introduce QSP in a fashion that does not require prior knowledge of quantum computing. We introduce iterative algorithms that can efficiently find the “phase factors” used to represent a given polynomial. We also identify a surprising connection between the smoothness of the target function and the decay properties of a specific branch of the phase factors. Bio: Lin Lin is a Professor in the Department of Mathematics at UC Berkeley and a Faculty Scientist in the Mathematics Group at Lawrence Berkeley National Laboratory. His research centers on solving quantum many-body problems by employing both classical and contemporary methods. These techniques prove valuable across various domains, including quantum chemistry, quantum physics, materials science, and quantum information theory. He has received the Sloan Research Fellowship (2015), the National Science Foundation CAREER award (2017), the Department of Energy Early Career Award (2017), the (inaugural) SIAM Computational Science and Engineering (CSE) Early Career Award (2017), the Presidential Early Career Awards for Scientists and Engineers (PECASE) (2019), the ACM Gordon Bell Prize (Team, 2020), and the Simons Investigator in Mathematics award (2021).