Self-adaptive physics-informed quantum machine learning for solving differential equations

Chebyshev polynomials have shown significant promise as an efficient tool for both classical and quantum neural networks to solve linear and nonlinear differential equations (DEs). In this work, we adapt and generalize this framework in a quantum machine learning setting for a variety of problems, i...

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Bibliographic Details

Published in:	Machine Learning: Science and Technology
Main Authors:	Abhishek Setty, Rasul Abdusalamov, Felix Motzoi
Format:	Article
Language:	English
Published:	IOP Publishing 2025-01-01
Subjects:	quantum machine learning physics-informed neural networks variational quantum algorithms differential equations
Online Access:	https://doi.org/10.1088/2632-2153/ada3ab