On nonlinear transformations in quantum computation
ORAL
Abstract
While quantum computers are naturally well-suited to implementing linear operations, it is less clear how to implement nonlinear operations on quantum computers. However, nonlinear subroutines may prove key to a range of applications of quantum computing from solving nonlinear equations to data processing and quantum machine learning. Here we develop algorithms for implementing nonlinear transformations of input quantum states. Our algorithms are framed around the concept of a weighted state, a mathematical entity describing the output of an operational procedure involving both quantum circuits and classical post-processing.
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Publication: https://doi.org/10.48550/arXiv.2112.12307
Presenters
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Yigit Subasi
Los Alamos National Laboratory
Authors
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Yigit Subasi
Los Alamos National Laboratory
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Zoe Holmes
Los Alamos National Laboratory, École polytechnique fédérale de Lausanne
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Nolan Coble
University of Maryland, College Park
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Andrew T Sornborger
Los Alamos National Laboratory