Wavefront shaping techniques in complex media
- Details
- Category: Multimode fibers
- Published on Monday, 25 February 2019 16:20
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[tutorial] pyMMF: Simulating Multimode Fibers in Python
Part 1: Step Index Benchmark
I recently published a two-part tutorial on how to find the modes of an arbitrary multimode fiber without or with bending. Based on this tutorial, I published a (still experimental) version of a Python module to find the modes of multimode fibers and calculate their transmission matrix: pyMMF. The goal of this module is not to compete with commercial solutions in term of precision but to provide a way to easily simulate realistic fiber systems. To validate the approach, I use step-index multimode fibers as a benchmark test as the dispersion relation is analytically known (see my tutorial here) and for which the Linearly Polarized (LP) mode approximation yields good results. I focus my attention here on the precision of the numerically found propagation constants.
- Details
- Category: Events
- Published on Monday, 18 February 2019 16:47
Complex Nanophotonics Science Camp 2019
Aug 11th - Aug 14th 2019
Cumberland Lodge
Windsor, United Kingdom
Organizers: Jacopo Bertolotti (University of Exeter, UK), Paloma Arroyo Huidobro (Imperial College London, UK), Giorgio Volpe (University College London, UK), Kevin Vynck (LP2N , Bordeaux, France)
Link: here
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- Category: Events
- Published on Thursday, 14 February 2019 11:22
PIERS2019 Rome Focus/Special Sessions
Disordered Photonics
June 17th - June 20th 2019
Faculty of Engineering - University of Rome "La Sapienza"
Rome, Italy
Organizers: Dr. Pedro David Garcia Fernandez (Catalan Institute of Nanoscience and Nanotechnology - ICN2) and Dr. Jacopo Bertolotti (University of Exeter)
Link: here
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- Category: Events
- Published on Friday, 08 February 2019 14:17
Summer School
Imaging in Wave Physics: Multi-Wave and Large Sensor Networks
Sep 23rd - Sep 27th 2019
Institut d’Études Scientifiques de Cargèse
Corsica, France
Director: Mathias Fink (Institut Langevin, ESPCI, France)
Organizers: Alexandre Aubry, Romain Pierrat, Sébastien M. Popoff (Institut Langevin, CNRS - ESPCI, France)
Link: here
- Details
- Category: Multimode fibers
- Published on Saturday, 29 December 2018 16:35
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[tutorial] Numerical Estimation of Multimode Fiber Modes and Propagation Constants:
Part 2: Bent Fibers
We saw in the first part of the tutorial that the profiles and the propagation constants of the propagation modes of a straight multimode fiber can easily be avulated for an arbitrary index profile by inverting a large but sparse matrix. Under some approximations [1], a portion of fiber with a fixed radius of curvature satisfies a similar problem that can be solved with the same numerical tools, as we illustrate with the PyMMF Python module [2]. Moreover, when the modes are known for the straight fiber, the modes for a fixed radius can be approximate by inverting a square matrix of size the number of propagating modes [1]. It allows fast computation of the modes for different radii of curvature.
- Details
- Category: Multimode fibers
- Published on Thursday, 13 December 2018 10:29
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[tutorial] Numerical Estimation of Multimode Fiber Modes and Propagation Constants:
Part 1: Straight Fibers
Under the weakly guided approximation, analytical solutions for the mode profiles of step index (SI) and graded index (GRIN) multimode fibers (MMF) can be found [1]. It also gives a semi-analytical solution for the dispersion relation in SI MMFs, and, by adding stronger approximations, an analytical solution for the parabolic profile GRIN MMFs [2] (note that those approximations do fail for lower order modes). An arbitrary index profile requires numerical simulations to estimate the mode profiles and the corresponding propagation constants of the modes. I present in this tutorial how to numerically estimate the scalar solution for the profiles and propagation constants of guides modes in multimode circular waveguide with arbitrary index profile and in presence of bending. I released a beta version of the Python module pyMMF based on such approach [3]. It relies on expressing the transverse Helmholtz equation as an eigenvalue problem. Solutions are found by finding the eigenvectors of a large but spare matrix representing the equation on the discretized space.
