Reflective low-sideband plasmonic structural colors

It is demonstrated experimentally that an aluminum (Al) nanowire grating structure on silicon substrates can produce low-side-band monochromatic peak when it reflects colored light in the transverse magnetic (TM) mode. The central wavelength of the reflection is shown to be sensitive to the incident angle, which leads to significant color shifts. Formation of the monochromatic peak is attributed to the surface plasmon resonance on the interface between Al and air, together with remarkable diffraction at shorter wavelengths and strong Fabry-Perot (F-P) resonance absorption by Al-surrounding nano-cavities and silicon substrate at longer wavelengths. In contrast, reflection in transverse electric (TE) mode does not show distinct wavelength selectivity due to the cut-off effect of the nano-cavities. The outstanding characters of the proposed structure with polarization dependence, high sensitivity to incident angle, high color rendering facilitate more compact and sophisticated color-filter-based devices for displays, anti-counterfeit, and sensing applications. In addition, the two-dimensional structure with thin grating thickness and high duty ratio tolerance is relatively easy for fabrication

Broad bandwidth waveguide polarizer via grating mediated mode conversion

A polarization beam splitter (PBS) based on a four-layer slab waveguide is proposed, where a sub-wavelength grating is embedded between the waveguide core and the cladding. This grating not only affords Bragg momentum to tune the propagation constant of guiding modes but also converts the forward zero-order waveguide mode to the backward first one for a specific polarization. Thus, the incident light with polarization that satisfies the phase-matching condition is highly reflected in the waveguide, while other light with orthogonal polarization keeps intact and passes through it efficiently. Numerical simulations show that one can make the compact PBS for both polarizations with an extinction ratio higher than 35 dB, a waveband larger than 80 nm, a grating period tolerance of 20 nm, and a waveguide height tolerance of 80 nm. The revealed mode conversion mechanism via the sub-wavelength grating enriches the design of PBSs for integrated silicon waveguide chips

DPM-Solver-v3: Improved Diffusion ODE Solver with Empirical Model Statistics

Diffusion probabilistic models (DPMs) have exhibited excellent performance for high-fidelity image generation while suffering from inefficient sampling. Recent works accelerate the sampling procedure by proposing fast ODE solvers that leverage the specific ODE form of DPMs. However, they highly rely on specific parameterization during inference (such as noise/data prediction), which might not be the optimal choice. In this work, we propose a novel formulation towards the optimal parameterization during sampling that minimizes the first-order discretization error of the ODE solution. Based on such formulation, we propose DPM-Solver-v3, a new fast ODE solver for DPMs by introducing several coefficients efficiently computed on the pretrained model, which we call empirical model statistics. We further incorporate multistep methods and a predictor-corrector framework, and propose some techniques for improving sample quality at small numbers of function evaluations (NFE) or large guidance scales. Experiments show that DPM-Solver-v3 achieves consistently better or comparable performance in both unconditional and conditional sampling with both pixel-space and latent-space DPMs, especially in 5$\sim$10 NFEs. We achieve FIDs of 12.21 (5 NFE), 2.51 (10 NFE) on unconditional CIFAR10, and MSE of 0.55 (5 NFE, 7.5 guidance scale) on Stable Diffusion, bringing a speed-up of 15%$\sim$30% compared to previous state-of-the-art training-free methods. Code is available at https://github.com/thu-ml/DPM-Solver-v3.Comment: Accepted at NeurIPS 202

Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs

Diffusion models have exhibited excellent performance in various domains. The probability flow ordinary differential equation (ODE) of diffusion models (i.e., diffusion ODEs) is a particular case of continuous normalizing flows (CNFs), which enables deterministic inference and exact likelihood evaluation. However, the likelihood estimation results by diffusion ODEs are still far from those of the state-of-the-art likelihood-based generative models. In this work, we propose several improved techniques for maximum likelihood estimation for diffusion ODEs, including both training and evaluation perspectives. For training, we propose velocity parameterization and explore variance reduction techniques for faster convergence. We also derive an error-bounded high-order flow matching objective for finetuning, which improves the ODE likelihood and smooths its trajectory. For evaluation, we propose a novel training-free truncated-normal dequantization to fill the training-evaluation gap commonly existing in diffusion ODEs. Building upon these techniques, we achieve state-of-the-art likelihood estimation results on image datasets (2.56 on CIFAR-10, 3.43/3.69 on ImageNet-32) without variational dequantization or data augmentation.Comment: Accepted in ICML202

On Crystal-Structure Matches in Solid-Solid Phase Transitions

The exploration of solid-solid phase transition (SSPT) suffers from the uncertainty of how two crystal structures match. We devised a theoretical framework to describe and classify crystal-structure matches (CSM). Such description fully exploits the translational and rotational symmetries and is independent of the choice of supercells. This is enabled by the use of the Hermite normal form, an analog of reduced echelon form for integer matrices. With its help, exhausting all CSMs is made possible, which goes beyond the conventional optimization schemes. As a demonstration, our enumeration algorithm unveils the long-sought concerted mechanisms in the martensitic transformation of steel accounting for the most commonly observed Kurdjumov-Sachs (KS) orientation relationship (OR) and the Nishiyama-Wassermann OR. Especially, the predominance of KS OR is explained. Given the unprecedented comprehensiveness and efficiency, our enumeration scheme provide a promising strategy for SSPT mechanism research.Comment: main text: 6 pages, 4 figures; supplemental materials: 14 pages, 6 figure

Highly tunable polarized chromatic plasmonic films based on sub-wavelength grating templates

A kind of polarized chromatic plasmonic film is proposed based on subwavelength grating structure, which enables “blue transmission” for the transverse electric light and “red transmission” for the transverse magnetic light. Metal–insulator–metal plasmonic waveguiding and metallic nanowire scattering are revealed to be responsible for the chromatic shift. Based upon the unique transmission spectrum characteristics of such films, polarized chromatic plasmonic tags (PCPTs) can be flexibly fabricated by patterning dielectric grating templates with designed figures and depositing appropriate thickness of metal. These PCPTs, simultaneously possessing directly visible unpolarized transmission colors and concealed distinct polarization‐dependent color shift, can be widely used as anti‐counterfeiting tags with higher security than the diffractive types of holograms