Related papers: Second-harmonic generation for enhancing the perfo…
Diffractive deep neural networks (D2NNs), which perform computation using light instead of electrons, offer a promising pathway toward accelerating artificial intelligence by leveraging the inherent advantages of optics in speed,…
Optical machine learning offers advantages in terms of power efficiency, scalability and computation speed. Recently, an optical machine learning method based on Diffractive Deep Neural Networks (D2NNs) has been introduced to execute a…
Topological photonics enables robust light manipulation with third-order optical nonlinearity, yet integrating second-order optical nonlinearity into a topological system faces fundamental challenges: frequency-dependent topological…
Second harmonic generation (SHG) is a nonlinear optical response arising exclusively from broken inversion symmetry in the electric-dipole limit. Recently, SHG has attracted widespread interest as a versatile and noninvasive tool for…
Deep neural networks (DNNs) have substantial computational requirements, which greatly limit their performance in resource-constrained environments. Recently, there are increasing efforts on optical neural networks and optical computing…
Second-harmonic generation (SHG) is a direct measure of the strength of second-order nonlinear optical effects, which also include frequency mixing and parametric oscillations. Natural and artificial materials with broken…
Silicon photonics lacks a second-order nonlinear optical response in general because the typical constituent materials are centro-symmetric and lack inversion symmetry, which prohibits second-order nonlinear processes such as second…
Diffractive Neural Networks (DNNs) leverage the power of light to enhance computational performance in machine learning, offering a pathway to high-speed, low-energy, and large-scale neural information processing. However, most existing DNN…
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…
Diffractive neural network (DNN), which can perform machine learning tasks based on the light propagation and diffraction, has recently emerged as a promising optical computing paradigm due to its high parallel processing speed and low…
Nonlinear optics, and particularly second harmonic generation (SHG), is increasingly used in many modern disciplines from material characterization in physical sciences to bio-imaging in medicine and optical signal processing in information…
Second harmonic generation (SHG) is a coherent nonlinear phenomenon that plays an important role in laser color conversion. Lithium niobate (LN), which features both a large band gap and outstanding second-order nonlinearities, acts as an…
Using machine learning, we explore the utility of various deep neural networks (NN) when applied to high harmonic generation (HHG) scenarios. First, we train the NNs to predict the time-dependent dipole and spectra of HHG emission from…
Photonic computation started to shape the future of fast, efficient and accessible computation. The advantages brought by light based Diffractive Deep Neural Networks (D2NN), are shown to be overwhelmingly advantageous especially in…
Optical coating, an integral part of many optical systems, is prone to damage from environmental exposure and laser irradiation. This underscores the need for reliable and sensitive coating diagnostics. We introduce second harmonic…
Photonic neural networks perform brain-inspired computations using photons instead of electrons that can achieve substantially improved computing performance. However, existing architectures can only handle data with regular structures,…
Diffractive optical neural networks (DONNs) have emerged as a promising optical hardware platform for ultra-fast and energy-efficient signal processing for machine learning tasks, particularly in computer vision. Previous experimental…
The effective second-harmonic generation (SHG) coefficient is a crucial data that quantifies the efficiency of transforming fundamental frequency light into its second harmonic. With the help of the symmetry of nonlinear optical…
We report about the experimental observation and characterization of nonlinear optical properties of individual silicon nanowires of different dimensions. Our results show that the nonlinear light has different components, one of them…
Recent advancements in optical computing have garnered considerable research interests owing to its ener-gy-efficient operation and ultralow latency characteristics. As an emerging framework in this domain, dif-fractive deep neural networks…