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Multivariable QSP and Bosonic Quantum Simulation using Iterated Quantum Signal Processing
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We provide in this work a form of Modular Quantum Signal Processing that we call iterated quantum signal processing. This method recursively applies quantum signal processing to the outputs of other quantum signal processing steps, allowing polynomials to be easily achieved that would otherwise be difficult to find analytically. We specifically show by using a squaring quantum signal processing routine, that multiplication of phase angles can be approximated and in turn that any bounded degree multi-variate polynomial function of a set of phase angles can be implemented using traditional QSP ideas. We then discuss how these ideas can be used to construct phase functions relevant for quantum simulation such as the Coulomb potential and also discuss how to use these ideas to obviate the need for reversible arithmetic to compute square-root functions needed for simulations of bosonic Hamiltonians.
Forward citations
Cited by 2 Pith papers
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Simulation of Non-Hermitian Hamiltonians with Bivariate Quantum Signal Processing
Claims query-optimal bivariate-QSP simulation of non-Hermitian Hamiltonians, but the constructive angle-finding chain is circular and contradicted by the paper's own benchmarks.
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