collaborators

7 papers

physics.optics2025

Coherent perfect absorption and lasing in bimodal Fabry-Pérot interferometers

Dmitry A. Bykov, Evgeni A. Bezus, Leonid L. Doskolovich

Bimodal Fabry-Pérot interferometer is a model generalizing the conventional Fabry-Pérot interferometer, in which not one but two kinds of waves propagate between the interfaces.…

physics.optics2025

Optical computation of the divergence of a vector field using a metal-dielectric multilayer

Leonid L. Doskolovich, Artem I. Kashapov, Evgeni A. Bezus +1

We theoretically describe the optical computation of the divergence of a two-dimensional vector field, which is composed by the transverse electric field components of an incident…

physics.optics2024

Topological properties of reflection zeros of optical differentiators based on layered metal-dielectric-metal structures

Artem I. Kashapov, Evgeni A. Bezus, Dmitry A. Bykov +2

We investigate the topological properties of reflection zeros of three-layer structures consisting of a dielectric layer sandwiched between two metal layers, which can be used as o…

physics.optics2024

Design of cascaded diffractive optical elements generating different intensity distributions at several operating wavelengths

Georgy A. Motz, Daniil V. Soshnikov, Leonid L. Doskolovich +3

We consider the design of cascaded diffractive optical elements (DOEs) for generating specified intensity distributions for several incident beams with different wavelengths. For e…

physics.optics2024

Design of diffractive neural networks solving different classification problems at different wavelengths

Georgy A. Motz, Leonid L. Doskolovich, Daniil V. Soshnikov +4

We consider the problem of designing a diffractive neural network (DNN) consisting of a set of sequentially placed phase diffractive optical elements (DOEs) and intended for the op…

physics.optics2024

Designing robust diffractive neural networks with improved transverse shift tolerance

Daniil V. Soshnikov, Leonid L. Doskolovich, Georgy A. Motz +3

A wide range of practically important problems is nowadays efficiently solved using artificial neural networks. This gave momentum to intensive development of their optical impleme…