Advertisement

Reducing Microwave Absorption with Chaotic Microwaves

  • Juehang QinEmail author
  • A. Hubler
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 6)

Abstract

We study the response of a two-level quantum system to a chaotic signal using numerical methods and compare it to the response to a sinusoidal signal. We expect the largest response for sinusoidal driving functions, because the Schrödinger equation is linear. The method is based on numerical solutions of the Schrödinger solution of the two-level system, and the chaotic signal used is that of a Chua oscillator. We find that when two-level systems are perturbed by a chaotic signal, the peak population of the initially unpopulated state is much lower than which is produced by a sinusoidal signal of small detuning. This is true even when the peak frequency of the chaotic signal, which is identified via a discrete fourier transform, is close to the resonant frequency. We also find that the response is weaker for a weaker signal, where the resonant peak for a sinusoidal signal would be narrower. We discuss potential applications of this result in the field of microwave power transmission, as it shows applying chaotic forcing functions to transmitted microwaves used for power transmission could decrease unintended absorption of microwaves by organic tissue.

Keywords

Power Transmission Power Transfer Chaotic Signal Peak Population Microwave Transmission 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This work was funded in part by the Office of Naval Research grant N00014-14-1-0381 and grant N00014-15-1-2397 and Air Force Research Laboratory grant AF FA9453-14-1-0247.

References

  1. 1.
    L. Xie, Y. Shi, Y.T. Hou, A. Lou, IEEE Wirel. Commun. 20(4), 140 (2013)Google Scholar
  2. 2.
    A. Sharma, V. Singh, T.L. Bougher, B.A. Cola, Nature Nanotechnol. 10(12), 1027 (2015)CrossRefGoogle Scholar
  3. 3.
    P. Jaffe, J. McSpadden, Proc. IEEE 101(6), 1424 (2013)CrossRefGoogle Scholar
  4. 4.
    H. Takhedmit, L. Cirio, B. Merabet, B. Allard, F. Costa, C. Vollaire, O. Picon, Electron. Lett. 46(12), 811 (2010)CrossRefGoogle Scholar
  5. 5.
    J.A. Tanner, Nature 210(5036), 636 (1966)CrossRefGoogle Scholar
  6. 6.
    K. Huang, X. Zhou, IEEE Commun. Mag. 53(6), 86 (2015)MathSciNetCrossRefGoogle Scholar
  7. 7.
    J.C. Reyes-Guerrero, M. Bokenfohr, T. Ciamulski, in WUWNET’14 Proceedings of the International Conference on Underwater Networks & Systems (ACM Press, New York, New York, USA, 2014), pp. 1–2Google Scholar
  8. 8.
    G. Foster, A.W. Hübler, K. Dahmen, Phys. Rev. E 75(3), 036212 (2007)MathSciNetCrossRefGoogle Scholar
  9. 9.
    C. Wargitsch, A. Hübler, Phys. Rev. E 51(2), 1508 (1995)MathSciNetCrossRefGoogle Scholar
  10. 10.
    V. Gintautas, A.W. Hübler, Chaos: an Interdisciplinary. J. Nonlinear Sci. 18(3), 033118 (2008)Google Scholar
  11. 11.
    V.S. Anishchenko, T.E. Vadivasova, D.E. Postnov, M.A. Safonova, Int. J. Bifurc. Chaos 02(03), 633 (1992)CrossRefGoogle Scholar
  12. 12.
    L. Pivka, C.W. Wu, A. Huang, J. Franklin Inst. 331(6), 705 (1994)MathSciNetCrossRefGoogle Scholar
  13. 13.
    J. Dormand, P. Prince, J. Comput. Appl. Math. 6(1), 19 (1980)MathSciNetCrossRefGoogle Scholar
  14. 14.
    L.F. Shampine, M.W. Reichelt, SIAM J. Sci. Comput. 18(1), 1 (1997)MathSciNetCrossRefGoogle Scholar
  15. 15.
    P. Pracna, V. Špirko, W.P. Kraemer, J. Mol. Spectrosc. 136(2), 317 (1989)CrossRefGoogle Scholar
  16. 16.
    M. Valentin, M. Olivier, J. Phys. D Appl. Phys. 13(2), 127 (1980)CrossRefGoogle Scholar
  17. 17.
    S. Sasaki, K. Tanaka, K.I. Maki, Proc. IEEE 101(6), 1438 (2013)CrossRefGoogle Scholar
  18. 18.
    H.P. Ren, M.S. Baptista, C. Grebogi, Phys. Rev. Lett. 110(18), 184101 (2013)CrossRefGoogle Scholar
  19. 19.
    J.C. Martín, Phys. Rev. E 91(2), 022914 (2015)CrossRefGoogle Scholar
  20. 20.
    L. Zhang, H. Wang, T. Li, IEEE Trans. Wirel. Commun. 12(1), 70 (2013)CrossRefGoogle Scholar
  21. 21.
    M. Frasca, A modern review of the two-level approximation (2003)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Center for Complex Systems Research at the University of Illinois at Urbana-ChampaignChampaignUSA

Personalised recommendations