Efficient Statistical Model for Predicting Electromagnetic Wave Distribution in Coupled Enclosures

Shukai Ma, Sendy Phang, Zachary Drikas, Bisrat Addissie, Ronald Hong, Valon Blakaj, Gabriele Gradoni, Gregor Tanner, Thomas M. Antonsen, Edward Ott, and Steven M. Anlage
Phys. Rev. Applied 14, 014022 – Published 8 July 2020

Abstract

The random coupling model (RCM) has been successfully applied to predicting the statistics of currents and voltages at ports in complex electromagnetic (EM) enclosures operating in the short-wavelength limit. Recent studies have extended the RCM to systems of multimode aperture-coupled enclosures. However, as the size (as measured in wavelengths) of a coupling aperture grows, the coupling matrix used in the RCM increases as well, and the computation becomes more complex and time consuming. A simple power balance (PWB) model can provide fast predictions for the averaged power density of waves inside electrically large systems for a wide range of cavity and coupling scenarios. However, the important interference-induced fluctuations of the wave field retained in the RCM are absent in the PWB model. Here we aim to combine the best aspects of each model to create a hybrid treatment and study the EM fields in coupled enclosure systems. The proposed hybrid approach provides both mean and fluctuation information of the EM fields without the full computational complexity of the coupled-cavity RCM. We compare the hybrid model predictions with experiments on linear cascades of over-moded cavities. We find good agreement over a set of different loss parameters and for different coupling strengths between cavities. The range of validity and applicability of the hybrid method are tested and discussed.

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  • Received 15 March 2020
  • Revised 22 May 2020
  • Accepted 26 May 2020

DOI:https://doi.org/10.1103/PhysRevApplied.14.014022

© 2020 American Physical Society

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied PhysicsNetworksStatistical Physics & Thermodynamics

Authors & Affiliations

Shukai Ma1,*, Sendy Phang2,3, Zachary Drikas4, Bisrat Addissie4, Ronald Hong4, Valon Blakaj2, Gabriele Gradoni2,3, Gregor Tanner2, Thomas M. Antonsen5,6, Edward Ott5,6, and Steven M. Anlage1,6

  • 1Quantum Materials Center, Department of Physics, University of Maryland, College Park, Maryland 20742, USA
  • 2School of Mathematical Sciences, University of Nottingham, Nottingham NG7 2RD, United Kingdom
  • 3George Green Institute for Electromagnetics Research, University of Nottingham, Nottingham NG7 2RD, United Kingdom
  • 4U.S. Naval Research Laboratory, Washington, DC 20375, USA
  • 5Department of Physics, University of Maryland, College Park, Maryland 20742, USA
  • 6Department of Electrical and Computer Engineering, University of Maryland, College Park, Maryland 20742-3285, USA

  • *skma@umd.edu

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Vol. 14, Iss. 1 — July 2020

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