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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Hlavní autoři:	Abhishek Setty, Rasul Abdusalamov, Felix Motzoi
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IOP Publishing 2025-01-01
Edice:	Machine Learning: Science and Technology
Témata:	quantum machine learning physics-informed neural networks variational quantum algorithms differential equations
On-line přístup:	https://doi.org/10.1088/2632-2153/ada3ab
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