On multivariate polynomials achievable with quantum signal processing
Additional information
Authors
Laneve L.,
Wolf S.
Type
Journal Article
Year
2025
Language
English
Abstract
Quantum signal processing (QSP) is a framework which was proven to unify and simplify a large number of known quantum algorithms, as well as discovering new ones. QSP allows one to transform a signal embedded in a given unitary using polynomials. Characterizing which polynomials can be achieved with QSP protocols is an important part of the power of this technique, and while such a characterization is well-understood in the case of univariate signals, it is unclear which multivariate polynomials can be constructed when the signal is a vector, rather than a scalar. This work uses a slightly different formalism than what is found in the literature, and uses it to find simpler necessary conditions for decomposability, as well as a sufficient condition – the first, to the best of our knowledge, proven for a (generally inhomogeneous) multivariate polynomial in the context of quantum signal processing.
Journal
Quantum
Volume
9
Pages (or article number)
1641
ISSN
2521-327X
Diffusion
License
CC BY
Visibility
Public
Status open access
Gold
