Quantum algorithm for the advection-diffusion equation and the Koopman-von Neumann approach to nonlinear dynamical systems
Ivan Novikau, Ilon Joseph

TL;DR
This paper introduces a quantum algorithm leveraging Hamiltonian simulation techniques to efficiently model both linear and nonlinear differential equations, including advection-diffusion and Koopman-von Neumann systems, with detailed implementation strategies.
Contribution
It presents a novel quantum algorithm that combines QSP and QSVT methods for simulating nonlinear dynamics and includes explicit block-encoding implementations for these models.
Findings
Simulated quantum circuits demonstrate feasibility on fault-tolerant computers.
Algorithm effectively models dissipation and avoids oscillations in advection equations.
Broad applicability to various linear and nonlinear differential equations.
Abstract
We propose an explicit algorithm based on the Linear Combination of Hamiltonian Simulations technique to simulate both the advection-diffusion equation and a nonunitary discretized version of the Koopman-von Neumann formulation of nonlinear dynamics. By including dissipation into the model, through an upwind discretization of the advection operator, we avoid spurious parasitic oscillations which usually accompany standard finite difference discretizations of the advection equation. In contrast to prior works on quantum simulation of nonlinear problems, we explain in detail how different components of the algorithm can be implemented by using the Quantum Signal Processing (QSP) and Quantum Singular Value Transformation (QSVT) methods. In addition, we discuss the general method for implementing the block-encoding (BE) required for QSP and QSVT circuits and provide explicit implementations…
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Taxonomy
Topicsadvanced mathematical theories · Stochastic processes and financial applications · Model Reduction and Neural Networks
