works on

From the 1 of 6 linked papers with an AI index.

collaborators

6 papers

quant-ph2026

From Nonlinear Stochastic Differential Equations to Quantum Channels: The Kolmogorov--Lindblad Mapping

Hsuan-Cheng Wu, Xiantao Li

Nonlinear stochastic differential equations (SDEs) underlie molecular modeling and drug discovery, quantitative finance, stochastic learning, and uncertainty quantification. Their…

quant-ph2026

Structure-Preserving Quantum Simulation of Wave Equations on a Trapped-Ion Processor

Abhishek Shringi, Hsuan-Cheng Wu, Ahmed Shokry +2

The authors design and benchmark Fourier-based quantum circuits that preserve structure for simulating one- and two-dimensional acoustic wave and Dirac equations on a trapped‑ion p…

quant-ph2026

Quantum Simulation of Differential-Algebraic Equations with Applications to Unsteady Stokes Flow

Hsuan-Cheng Wu, Xiantao Li

Differential-algebraic equations (DAEs) arise naturally in constrained dynamical systems, but their algebraic constraints and hidden compatibility conditions make them more subtle…

quant-ph2026

Universal Dilation of Linear Itô SDEs: Quantum Trajectories and Lindblad Simulation of Second Moments

Hsuan-Cheng Wu, Xiantao Li

We present a universal framework for simulating -dimensional linear Itô stochastic differential equations (SDEs) on quantum computers with additive or multiplicative noises. Bu…

quant-ph2025

Structure-preserving quantum algorithms for linear and nonlinear Hamiltonian systems

Hsuan-Cheng Wu, Xiantao Li

Hamiltonian systems of ordinary and partial differential equations are fundamental mathematical models spanning virtually all physical scales. A critical property for the robustnes…

quant-ph2025

Quantum Algorithms for Nonlinear Dynamics: Revisiting Carleman Linearization with No Dissipative Conditions

Hsuan-Cheng Wu, Jingyao Wang, Xiantao Li

In this paper, we explore the embedding of nonlinear dynamical systems into linear ordinary differential equations (ODEs) via the Carleman linearization method. Under dissipative c…