Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userSelective tuning of high-Q silicon photonic crystal nanocavities via laser-assisted local oxidation
187
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
We examine the cavity resonance tuning of high-Q silicon photonic crystal heterostructures by localized laser-assisted thermal oxidation using a 532 nm continuous wave laser focused to a 2.5 mm radius spot-size. The total shift is consistent with the parabolic rate law. A tuning range of up to 8.7 nm is achieved with ~ 30 mW laser powers. Over this tuning range, the cavity Q decreases from 3.2times10^5 to 1.2times10^5. Numerical simulations model the temperature distributions in the silicon photonic crystal membrane and the cavity resonance shift from oxidation.
rate research
Read More
We propose and demonstrate the digital resonance tuning of high-Q/Vm silicon photonic crystal nanocavities using a self-limiting atomic layer deposition technique. Control of resonances in discrete steps of 122 +/- 18 pm per hafnium oxide atomic layer is achieved through this post-fabrication process, nearly linear over a full 17 nm tuning range. The cavity Q is maintained in this perturbative process, and can reach up to its initial values of 49,000 or more. Our results are highly controllable, applicable to many material systems, and particularly critical to matching resonances and transitions involving mesoscopic optical cavities.
We demonstrate photonic crystal nanobeam cavities that support both TE- and TM-polarized modes, each with a Quality factor greater than one million and a mode volume on the order of the cubic wavelength. We show that these orthogonally polarized modes have a tunable frequency separation and a high nonlinear spatial overlap. We expect these cavities to have a variety of applications in resonance-enhanced nonlinear optics.
A Deep Learning (DL) based forward modeling approach has been proposed to accurately characterize the relationship between design parameters and the optical properties of Photonic Crystal (PC) nanocavities. The proposed data-driven method using Deep Neural Networks (DNN) is set to replace conventional approaches manually performed in simulation software. The demonstrated DNN model makes predictions not only for the Q factor but also for the modal volume V for the first time, granting us precise control over both properties in the design process. Specifically, a three-channel convolutional neural network (CNN), which consists of two convolutional layers followed by two fully-connected layers, is trained on a large-scale dataset of 12,500 nanocavities. The experimental results show that the DNN has achieved a state-of-the-art performance in terms of prediction accuracy (up to 99.9999% for Q and 99.9890% for V ) and convergence speed (i.e., orders-of-magnitude speedup). The proposed approach overcomes shortcomings of existing methods and paves the way for DL-based on-demand and data-driven optimization of PC nanocavities applicable to the rapid prototyping of nanoscale lasers and integrated photonic devices of high Q and small V.
We propose and experimentally demonstrate a photonic crystal nanocavity with multiple resonances that can be tuned nearly independently. The design is composed of two orthogonal intersecting nanobeam cavities. Experimentally, we measure cavity quality factors of 6,600 and 1000 for resonances separated by 382 nm; we measure a maximum separation between resonances of 506 nm. These structures are promising for enhancing efficiency in nonlinear optical processes such as sum/difference frequency and stimulated Raman scattering.
Photonic nanocavities are a key component in many applications because of their capability of trapping and storing photons and enhancing interactions of light with various functional materials and structures. The maximal number of photons that can be stored in silicon photonic cavities is limited by the free-carrier and thermo-optic effects at room temperature. To reduce such effects, we performed the first experimental study of optical nonlinearities in ultrahigh-Q silicon disk nanocavities at cryogenic temperatures in a superfluid helium environment. At elevated input power, the cavity transmission spectra exhibit distinct blue-shifted bistability behavior when temperature crosses the liquid helium lambda point. At even lower temperatures, the spectra restore to symmetric Lorentzian shapes. Under this condition, we obtain a large stored intracavity photon number of about 40,000, which is limited ultimately by the local helium phase transition. These new discoveries are explained by theoretical calculations and numerical simulations.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
