Optimal Bounds, Barriers, and Extensions for Non-Hermitian Bivariate Quantum Signal Processing
Abstract
Multivariate quantum signal processing (M-QSP) has recently been shown to be applicable for non-Hermitian Hamiltonian simulation, opening several problems regarding the optimization landscape, angle-finding, and constant-factor analysis. We resolve several of these problems here. We find the anti-Hermitian query complexity to be tight, established via Chebyshev coefficient bounds, modified Bessel function asymptotics, and Lambert~ inversion. Fast-forwarding to is impossible in the bivariate polynomial model, though a linear state-dependent improvement to is achievable. The optimization landscape of M-QSP admits spurious local minima, but a warm-start basin guarantee ensures the two-stage algorithm converges. CRC-exploiting block peeling reduces angle-finding from to classical operations, and optimized error allocation yields a leading constant of approximately~ relative to the information-theoretic lower bound. A constant-ratio condition extends to non-identical signal operators, enabling time-dependent non-Hermitian simulation with query complexity . Block-encoding overhead holds across all function classes within the walk-operator oracle model, and dilational methods (Schr\"odingerization) achieve the walk-operator barrier. A precisely characterized direct-access construction achieves the intrinsic barrier (with for non-commuting Hamiltonians) on a restricted domain, though extension to the full bitorus remains open.
Cite
@article{arxiv.2605.12656,
title = {Optimal Bounds, Barriers, and Extensions for Non-Hermitian Bivariate Quantum Signal Processing},
author = {Joshua M. Courtney},
journal= {arXiv preprint arXiv:2605.12656},
year = {2026}
}
Comments
20 pages, 1 figure, 13 tables