Schr\"odingerization based quantum algorithms for the fractional Poisson equation
Shi Jin, Nana Liu, Yue Yu

TL;DR
This paper introduces a quantum algorithm for efficiently solving high-dimensional fractional Poisson equations by transforming them into Schr"odinger-type systems, achieving exponential speedup over classical methods.
Contribution
The paper develops a novel quantum algorithm using Schr"odingerization for fractional PDEs, enabling high-dimensional problems to be solved more efficiently than classical approaches.
Findings
Quantum algorithm achieves exponential speedup in high dimensions.
Complexity analysis shows independence from dimension in inverse mesh size.
Numerical experiments verify the effectiveness of the proposed method.
Abstract
We develop a quantum algorithm for solving high-dimensional fractional Poisson equations. By applying the Caffarelli-Silvestre extension, the -dimensional fractional equation is reformulated as a local partial differential equation in dimensions. We propose a quantum algorithm for the finite element discretization of this local problem, by capturing the steady-state of the corresponding differential equations using the Schr\"odingerization approach from \cite{JLY22SchrShort, JLY22SchrLong, analogPDE}. The Schr\"odingerization technique transforms general linear partial and ordinary differential equations into Schr\"odinger-type systems, making them suitable for quantum simulation. This is achieved through the warped phase transformation, which maps the equation into a higher-dimensional space. We provide detailed implementations of the method and conduct a comprehensive…
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Taxonomy
TopicsOptical Network Technologies · Advanced Adaptive Filtering Techniques · Neural Networks and Reservoir Computing
