Conference Agenda

We calculate and analyze the quality factors Q and the intensity and sensor

figures of merit (IFoM and SFoM) evaluating the intensity and sensor coupled with the leakage of modes of the reflection flux and of the plane-wave and locally excited transmitted fluxes of insulator-metal-insulator (IMI) and metal-insulator-metal (MIM) 2D planar thin-film stacks, here glass-Ti-Au-air and glass-Ti-Au-SiO2-Au-air respec-

tively. These thin film stacks sustain a single surface plasmon polariton (SPP)

and multiple planar wave guide (PWG) modes. The Q, IFoM and SFoM of the 3D

dispersion graph (in-plane wave vector kρ/k0 ∈[0, 1.52]/frequency ω ∈[0.5,

2.7] eV/observable) are calculated and analyzed along 2D cuts where either the

in-plane wave vector kρ/k0 or the frequency ω are varied the other independent

variables being kept fixed.

A general and simple semi-analytic theory of multilayer dielectric gratings is presented. It extends a previous work [J. Opt. Soc. Am. A 41, 252 (2024)] that assumes symmetric grating profile and Littrow mounting to gratings of asymmetric profiles in off-Littrow mounting.

The prediction of optical properties dominated by light scattering in particulate media composed of high-concentration and polydisperse particles is greatly important in various optical applications. However, the accuracy and efficiency of light propagation simulations are still limited by the huge computational burden and complex interactions between dense and polydisperse particles. Here, we proposed a new optimization strategy that can effectively and accurately predict optical properties based on Monte Carlo simulation with particle size and dependent scattering corrections. Both the scattering parameters of particles and the experimental reflectance spectrum are fully examined for verification. Furthermore, using the weighted solar reflectance of particulate media as a representative optical property, both numerical simulations and experiments confirm the superiority and universality of the proposed optimization approach in a variety of materials systems. Moreover, our work can guide the design of particulate media with specific optical features insightfully and will be applicable in many fields involving multiparticle scattering.

Precise beam shaping is essential for many trapped-ion quantum computing architectures, where grating couplers are the conventional solution for delivering light from a photonic chip to an ion. The required beam properties, such as a Gaussian profile with a well-controlled beam waist, pure circular polarization, and steered in a specific direction, require a sophisticated design space. We replace standard grating structures with metasurfaces consisting of subwavelength pixels, transforming the problem into a complex inverse design challenge. Here, conventional multi-objective optimization methods require extensive computational resources and must be re-run for each new target parameter. We propose a hybrid deep learning-driven approach to accelerate the design process by integrating a surrogate-assisted optimization pipeline and generative models. Our approach significantly reduces computational cost while improving flexibility in beam engineering, making it a promising candidate for scalable ion-trap integration.

Active tuning of photonic integrated circuits (PICs) in the visible regime is essential for programmable devices, but conventional designs suffer from fixed bandwidth and response times. Here, we demonstrate (i) all-optical and (ii) electro-optical control of extraordinary optical transmission (EOT) to achieve on-demand tunability in PICs. In the all-optical scheme, the EOT signal’s intensity and spectral position are dynamically modulated by tailoring surface plasmon resonance (SPR) dynamics via ultrashort light pulses. Time-resolved 3D FDTD simulations and wavelet transform analysis reveal that tuning excitation wavelength and duration optimizes SPR modes, enhancing EOT efficiency to 95% and improving response times by extending SPR lifetimes to 100 fs. For electro-optical control, we integrate a voltage-tunable quantum emitter (QE) into the EOT structure. The QE’s resonance frequency, adjusted by an external bias, modulates the coupled SPR dynamics. This shifts the EOT signal frequency by up to 181 meV across QE transition wavelengths while enabling continuous intensity modulation with a 10³ depth. Our approach enables real-time reconfigurability and performance optimization of EOT device, addressing critical needs for biosensing, high-resolution imaging, and molecular spectroscopy.

This work models light transmission through metal-dielectric-metal microcavities supporting Coupled Surface Plasmons (CSP). An extended Fabry-Pérot formula reveals two plasmonic resonances that merge beyond a critical cavity thickness. Remarkably, transmittance at these resonances remains high and nearly constant for thicknesses exceeding the light's penetration depth. Results at a 1 μm wavelength show over 10% transmittance up to 3.5 μm, offering new insights for photonic device design