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SUMMARY:Wave propagation in complex media: Branching\, chimeras and machin
 e learning predictions - Professor G. P. Tsironis - Department of Physics\
 , University of Crete\, Greece
DTSTART:20180530T100000Z
DTEND:20180530T113000Z
UID:TALK106297@talks.cam.ac.uk
CONTACT:Romy Hall
DESCRIPTION:Wave formation and propagation in complex media involves extre
 me phenomena such as branching and rogue-type waves as well as partial syn
 chronization in the form of chimeras.    We present results from disordere
 d media where singular wave events may appear.   We first address wave pro
 pagation in optical metamaterial-type units with disorder and strong scatt
 ering.  We show that theory and experiments agree that coalescing waves du
 e to strong disorder lead to singular waves.  The experimental work is on 
 silica layers where the intensity of the impinging laser light is used to 
 tune from the linear to the nonlinear regimes [1].   The second\, mathemat
 ically related problem\, involves electric current patterns in doped graph
 ene and the onset of branching.  We find theoretically and also numericall
 y a scaling relationship that connects statistically the location of where
  the first branches occur to the disordered properties of  the medium [2].
   We show further that the patterns of the occurrence of branches in graph
 ene may be detected through machine learning.  Specifically we use recurre
 nt neural networks and show that after initial training and while using pa
 rtial information on the electron flow\, the network is able to predict qu
 ite accurately the location and properties of the branches.  We propose th
 at machine learning may be used for experimental data reconstruction in gr
 aphene and related problems [3].    Finally\,  we switch to a medium made 
 of  SQUIDS that form a nonlinear superconducting metamaterial [4].  In thi
 s system a wave pattern with stable yet partially coherent features termed
  “chimeras” has been predicted to form\; we describe their basic prope
 rties and address the issue of chimera predictability through machine lear
 ning algorithms [3]. \n\n[1] M. Mattheakis\, I. J. Pitsios\, G. P. Tsironi
 s and S. Tzortzakis\, Extreme events in complex linear and nonlinear photo
 nic media\, Chaos\, Solitons and Fractals\, 84\, 73 (2016).\n[2] M. Matthe
 akis\, G. P. Tsironis and E. Kaxiras\,  Emergence and dynamical properties
  of stochastic branching in electronic flows in disordered Dirac solids\, 
 arXiv:1801.08217v1.\n[3] G. Neofotistos et al\, in preparation\n[4] N. Laz
 arides and G. P. Tsironis\, Superconducting metamaterials\, arXiv :1712.01
 323v1.\n
LOCATION:Mott Seminar Room (531)\, Cavendish Laboratory\, Department of Ph
 ysics
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