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quant-ph2026

Quantum Eigenvalue Transformation via Linear Combination of Hamiltonian Simulation: A Weyl Calculus Approach

Hongkang Ni, Lexing Ying

Linear combination of Hamiltonian simulation (LCHS) provides an efficient method for implementing matrix exponentials on quantum computers. In this paper, we develop LCHS…

quant-ph2025

Inverse nonlinear fast Fourier transform on SU(2) with applications to quantum signal processing

Hongkang Ni, Rahul Sarkar, Lexing Ying +1

The nonlinear Fourier transform (NLFT) extends the classical Fourier transform by replacing addition with matrix multiplication. While the NLFT on has been widel…

quant-ph2024

Fast Phase Factor Finding for Quantum Signal Processing

Hongkang Ni, Lexing Ying

This paper presents two efficient and stable algorithms for recovering phase factors in quantum signal processing (QSP), a crucial component of many quantum algorithms. The first a…

quant-ph2024

Quantum Multiple Eigenvalue Gaussian filtered Search: an efficient and versatile quantum phase estimation method

Zhiyan Ding, Haoya Li, Lin Lin +3

Quantum phase estimation is one of the most powerful quantum primitives. This work proposes a new approach for the problem of multiple eigenvalue estimation: Quantum Multiple Eigen…

quant-ph2024

Quantum wave packet transforms with compact frequency support

Hongkang Ni, Lexing Ying

Different kinds of wave packet transforms are widely used for extracting multi-scale structures in signal processing tasks. This paper introduces the quantum circuit implementation…

quant-ph2024

Quantum Hamiltonian Learning for the Fermi-Hubbard Model

Hongkang Ni, Haoya Li, Lexing Ying

This work proposes a protocol for Fermionic Hamiltonian learning. For the Hubbard model defined on a bounded-degree graph, the Heisenberg-limited scaling is achieved while allowing…