Classical step-size extrapolation reduces the maximum single-run circuit depth of a one-ancilla quantum ODE solver from O(1/ε) to O(polylog(1/ε)) without adding ancillae.
https://arxiv.org/abs/2312.03916
5 Pith papers cite this work. Polarity classification is still indexing.
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A dual Fourier-PSF and contour-PSF framework resolves the smoothness-sparsity trade-off for efficient quantum simulation of singular and holomorphic matrix functions.
Quantum circuit framework for advection-diffusion PDEs with Robin and periodic boundary conditions via LCHS, including LCU error analysis and gate complexity showing potential quantum advantage in high dimensions.
CBMD decomposes non-Hermitian evolution operators into Hermitian LCU terms via a matrix residue theorem, matching known optimal query bounds and offering a route to polynomial matrix functions.
Schrödingerization-based quantum linear systems solver using LCHS and block preconditioning for near-optimal query complexity.
citing papers explorer
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Circuit Depth Reduction of One-Ancilla Quantum Differential Equation Solver via Extrapolation
Classical step-size extrapolation reduces the maximum single-run circuit depth of a one-ancilla quantum ODE solver from O(1/ε) to O(polylog(1/ε)) without adding ancillae.
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A Unified Poisson Summation Framework for Generalized Quantum Matrix Transformations
A dual Fourier-PSF and contour-PSF framework resolves the smoothness-sparsity trade-off for efficient quantum simulation of singular and holomorphic matrix functions.
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Quantum circuits for the advection-diffusion equation with boundary conditions based on LCHS
Quantum circuit framework for advection-diffusion PDEs with Robin and periodic boundary conditions via LCHS, including LCU error analysis and gate complexity showing potential quantum advantage in high dimensions.
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Quantum Simulation of Non-Hermitian Special Functions and Dynamics via Contour-based Matrix Decomposition
CBMD decomposes non-Hermitian evolution operators into Hermitian LCU terms via a matrix residue theorem, matching known optimal query bounds and offering a route to polynomial matrix functions.
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Schr\"odingerization for quantum linear systems problems with near-optimal dependence on matrix queries
Schrödingerization-based quantum linear systems solver using LCHS and block preconditioning for near-optimal query complexity.