Related papers: Versatile non-diffracting beams generator based on…
A rapid and efficient method for generating laser beams with controlled intensity, phase and coherence distributions is presented. It is based on a degenerate cavity laser in which a digital phase-only spatial light modulator is…
We introduce a paradigm for accurate design of metasurfaces for intricate beam manipulation, implementing functionalities previously considered impossible to achieve with passive lossless elements. The key concept involves self-generation…
Dynamic phase-only beam shaping with a liquid crystal spatial light modulator is a powerful technique for tailoring the beam's intensity profile or wave front. While shaping and controlling the light field is a highly researched topic,…
Mirrors are ubiquitous in optics and are used to control the propagation of optical signals in space. Here we propose and demonstrate frequency domain mirrors that provide reflections of the optical energy in a frequency synthetic…
We introduce DiffRF, a novel approach for 3D radiance field synthesis based on denoising diffusion probabilistic models. While existing diffusion-based methods operate on images, latent codes, or point cloud data, we are the first to…
We manipulate a Bose-Einstein condensate using the optical trap created by the diffraction of a laser beam on a fast ferro-electric liquid crystal spatial light modulator. The modulator acts as a phase grating which can generate arbitrary…
The PhD thesis is devoted to the study of second harmonic generation of narrow beams in photonic crystals. The basic idea is that if both frequencies, the fundamental and second harmonics are in the region of self-collimation, then the…
Hyperuniform structures possess the ability to confine and drive light, although their fabrication is extremely challenging. Here we demonstrate that speckle patters obtained by a superposition of randomly arranged sources of Bessel beams…
Diffusion bridges (DBs) are a class of diffusion models that enable faster sampling by interpolating between two paired image distributions. Training traditional DBs for image reconstruction requires high-quality reference images, which…
Denoising diffusion models have emerged as powerful tools for image manipulation, yet interactive, localized editing workflows remain underdeveloped. We introduce Layered Diffusion Brushes (LDB), a novel training-free framework that enables…
The generation of light beams carrying orbital angular momentum (OAM) from a free-electron laser at short wavelengths has attracted considerable attention as a key resource in several fields and applications. Herein, we present a facile…
Low-refractive-index (LRI) particles play significant roles in physics, drug delivery, biomedical science, and other fields. However, they have not attained sufficient utilization in active manipulation due to the repulsive effect of light.…
All-optical diffractive neural networks (DNNs) offer a promising alternative to electronics-based neural network processing due to their low latency, high throughput, and inherent spatial parallelism. However, the lack of reconfigurability…
Multimode optical fibres are enjoying a renewed attention, boosted by the urgent need to overcome the current capacity crunch of single-mode fibre systems and by recent advances in multimode complex nonlinear optics [1-13]. In this work, we…
We propose and implement a novel method to produce a spatial anti-bunched field with free propagating twin beams from spontaneous parametric down-conversion. The method consists in changing the spatial propagation by manipulating the…
Novel View Synthesis (NVS) from unconstrained photo collections is challenging in computer graphics. Recently, 3D Gaussian Splatting (3DGS) has shown promise for photorealistic and real-time NVS of static scenes. Building on 3DGS, we…
Visible wavelengths of light control the quantum matter of atoms and molecules and are foundational for quantum technologies, including computers, sensors, and clocks. The development of visible integrated photonics opens the possibility…
Optical pin beams (OPBs) represent a novel class of structured light fields engineered for resilient, long-distance propagation. Their exceptional stability and strong resistance to atmospheric turbulence make them a compelling alternative…
Deep generative models (DGMs) and their conditional counterparts provide a powerful ability for general-purpose generative modeling of data distributions. However, it remains challenging for existing methods to address advanced conditional…
Conventional diffusion models typically relies on a fixed forward process, which implicitly defines complex marginal distributions over latent variables. This can often complicate the reverse process' task in learning generative…