arXiv subjects

Régis Orobtchouk

Publications and source records attributed to Régis Orobtchouk.

5 recordsLinked to original sources

arXiv2026

Diffusion Schrödinger Bridges with enhanced posterior sampling for metasurface inverse design

Metasurface inverse design is challenged by the intricate relationship between structural parameters and electromagnetic responses, as well as the high dimensionality of the optimization space. Local models, while commonly employed, quickly become infeasible for complex and locally coupled structures. Conventional iterative optimization techniques, on the other hand, are computationally intensive, time-consuming, and susceptible to convergence in local minima. This study explores a versatile generative methodology based on enhanced posterior sampling within the Schrödinger Bridge framework. By decomposing posterior sampling into amplitude and directional contributions, we effectively integrated different kind of posterior sampling. This approach is further supported by refined training strategies to enhance performance and reduce the complexity of hyperparameter optimization. The proposed framework demonstrates exceptional accuracy and robustness, representing a significant advancement in metasurface design. Notably, it enables high-precision inverse design for large-scale configurations of up to $350 \times 350$ pillar arrays, despite being trained on significantly smaller arrays of $23 \times 23$ pillars.

physics.optics↗

arXiv2026

Enhanced posterior sampling via diffusion models for efficient metasurfaces inverse design

The inverse design of metasurfaces faces inherent challenges due to the nonlinear and highly complex relationship between geometric configurations and their electromagnetic behavior. Traditional optimization approaches often suffer from excessive computational demands and a tendency to converge to suboptimal solutions. This study presents a diffusion-based generative framework that incorporates a dedicated consistency constraint and advanced posterior sampling methods to ensure adherence to desired electromagnetic specifications. Through rigorous validation on small-scale metasurface configurations, the proposed approach demonstrates marked enhancements in both accuracy and reliability of the generated designs. Furthermore, we introduce a scalable methodology that extends inverse design capabilities to large-scale metasurfaces, validated for configurations of up to $98 \times 98$ nanopillars. Notably, this approach enables rapid design generation completed in minute by leveraging models trained on substantially smaller arrays ($23 \times 23$). These innovations establish a robust and efficient framework for high-precision metasurface inverse design.

physics.optics↗

arXiv2025

Spatially-Controlled Planar Guided Crystallization of Low-Loss Phase Change Materials for Programmable Photonics

Photonic integrated devices are progressively evolving beyond passive components into fully programmable systems, notably driven by the progress in chalcogenide phase-change materials (PCMs) for non-volatile reconfigurable nanophotonics. However, the stochastic nature of their crystal grain formation results in strong spatial and temporal crystalline inhomogeneities. Here, we propose the concept of spatially-controlled planar guided crystallization, a novel method for programming the growth of optically homogeneous low-loss Sb2S3 PCM, leveraging the seeded directional and progressive crystallization within confined channels. This guided crystallization method is experimentally shown to circumvent the current limitations of conventional PCM-based nanophotonic devices, including a multilevel non-volatile optical phase-shifter exploiting a silicon nitride-based Mach-Zehnder interferometer, and a programmable metasurface with spectrally reconfigurable bound state in the continuum. Precisely controlling the growth of PCMs to ensure optically uniform crystalline properties across devices is the cornerstone for the industrial development of non-volatile reconfigurable photonic integrated circuits.

physics.optics↗

arXiv2024

Invited: Neuromorphic architectures based on augmented silicon photonics platforms

In this work, we discuss our vision for neuromorphic accelerators based on integrated photonics within the framework of the Horizon Europe NEUROPULS project. Augmented integrated photonic architectures that leverage phase-change and III-V materials for optical computing will be presented. A CMOS-compatible platform will be discussed that integrates these materials to fabricate photonic neuromorphic architectures, along with a gem5-based simulation platform to model accelerator operation once it is interfaced with a RISC-V processor. This simulation platform enables accurate system-level accelerator modeling and benchmarking in terms of key metrics such as speed, energy consumption, and footprint.

cs.ET↗

arXiv2019

VO2 Nanocrystals for Designer Phase-Change Metamaterials

Subwavelength nanoparticles can support electromagnetic resonances with distinct features depending on their size, shape and nature. For example, electric and magnetic Mie resonances occur in dielectric particles, while plasmonic resonances appear in metals. Here, we experimentally demonstrate that the multipolar resonances hosted by VO2 nanocrystals can be dynamically tuned and switched thanks to the insulator-to-metal transition of VO2. Using both Mie theory and Maxwell Garnett effective medium theory, we retrieve the complex refractive index of the effective medium composed of a slab of VO2 nanospheres embedded in SiO2 and show that such a resulting metamaterial presents distinct optical tunability compared to unpatterned VO2. We further show that this provides a new degree of freedom to design low-loss phase-change metamaterials with designer optical tunability and actively controlled light scattering.

physics.optics↗