Phase-dependent Supermode Excitation in Photonic Molecules

A photonic molecule (PM) is a miniature diffractive optical structure composed of resonance microcavities called atoms (e.g., cylinders or spheres) supporting a set of high-quality eigenmodes. All atoms in a PM are coupled by the electromagnetic fields of eigenmodes, which form collective supermodes of the whole PM. We consider a particular type of mirror-symmetric PMs being optically excited simultaneously via two light channels (tapered fibers). Based on the numerical simulations, we show that the spectral composition of supermodes in such PM can be effectively manipulated by changing the phase detuning between the optical channels. For a seven-atom silicon microcylinder cyclic-PM is demonstrated the possibility to achieve tenfold intensity amplification/suppression of several supermodes from the Stokes and anti-Stokes bands of PM spectrum

Toward high-speed effective numerical simulation of multiple filamentation of high-power femtosecond laser radiation in transparent medium

High-power femtosecond laser radiation during the propagation in air (and other transparent media) experiences multiple filamentation. Filamentation is a unique nonlinear optical phenomenon, which is accompanied by a wealth of nonlinear optical effects such as formation of extended plasma channels in the beam wake, generation of higher harmonics and supercontinuum, generation of THz radiation. The manifestations of laser filamentation can be useful for solving atmospheric optics problems related to remote sensing of the environment as well as directed transmission of laser power. The classical numerical methods used for simulating the nonlinear long-range atmospheric propagation of high-power radiation with a sufficiently large laser beam aperture have almost reached their limit regarding the acceleration of calculations. To solve this problem and speed-up the numerical simulations of laser filamentation, we propose an improved numerical technique based on a modified method of phase screens constructed on a sparse spatial grid. Within the framework of this technique, we seek for optimal ansatz (substitution function) to the governing equations using the machine learning technology, which provides for the best correspondence to the numerical solution of the test problem using a denser spatial gri