JOURNAL ARTICLE

The Fresnel equations of classical and extended electrodynamics – a review.

  • Published In: ZAMM -- Journal of Applied Mathematics & Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 2025, v. 105, n. 5. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Ivanova, Elena A.; Müller, Wolfgang H.; Rickert, Wilhelm; Vilchevskaya, Elena N. 3 of 3

Abstract

We study the behavior of electromagnetic waves near the interface between two media: a dielectric medium and a conducting medium leading to the so‐called Fresnel equations. We discuss analytical solutions of the problem in the framework of classical as well as extended electrodynamics. As a didactic add‐on a rational derivation of the classical Fresnel equations in conducting media by using a consistent application of vector representation for the wave vectors is presented for the benefit of the reader. The Fresnel equations obtained in the framework of extended electrodynamics are novel. We also discuss three mechanical models of electrodynamic processes in conducting media. The mathematical description of two of them allows one to obtain classical Maxwell's equations. The third model combines the two first models. Its mathematical description allows one to obtain the equations of extended electrodynamics. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:ZAMM -- Journal of Applied Mathematics & Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik. 2025/05, Vol. 105, Issue 5, p1
  • Document Type:Article
  • Subject Area:History
  • Publication Date:2025
  • ISSN:0044-2267
  • DOI:10.1002/zamm.70016
  • Accession Number:185525037
  • Copyright Statement:Copyright of ZAMM -- Journal of Applied Mathematics & Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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