Design of All-Dielectric Long-wave infrared Wide-angle Metalens

Optical metasurfaces are two-dimensional arrays of nano-scatterers that modify optical wavefronts at subwavelength spatial resolution. They achieve the effect of focusing through phase control under a sub-wavelength scale, named metalens. They are poised to revolutionize optics by enabling complex low-cost systems. However, there are monochromatic severe aberrations in the metasurfaces. In this paper,the long-wave infrared optical system coma is eliminated through a single-layer metasurface. By changing the phase function,this metalens have a numerical aperture of 0.89,a focal length of 150 μm,and a field of view of 120° (0.4@60lp/mm) that enables diffraction-limited monochromatic imaging along the focal plane at a wavelength of 10.6μm. And the designed metasurface maintains a favorable MTF value at different angles. This equipment can be widely used in imaging and industrial processing.

SMALL-SCALE EQUIDISTRIBUTION OF RANDOM WAVES GENERATED BY AN UNFAIR COIN FLIP

In this paper we study the small-scale equidistribution property of random waves whose coefficients are determined by an unfair coin. That is, the coefficients take value $+1$ with probability p and $-1$ with probability $1-p$ . Random waves whose coefficients are associated with a fair coin are known to equidistribute down to the wavelength scale. We obtain explicit requirements on the deviation from the fair ( $p=0.5$ ) coin to retain equidistribution.

Extraction of diffractions from seismic data using convolutional U-net and transfer learning

Diffraction images can be used for modeling reservoir heterogeneities at or below the seismic wavelength scale. However, the extraction of diffractions is challenging because their amplitude is weaker than that of overlapping reflections. Recently, deep learning (DL) approaches have been used as a powerful tool for diffraction extraction. Most DL approaches use a classification algorithm that classifies pixels in the seismic data as diffraction, reflection, noise, or diffraction with reflection, and takes whole values for the classified diffraction pixels. Thus, these DL methods cannot extract diffraction energy from pixels for which diffractions are masked by reflections. We proposed a DL-based diffraction extraction method that preserves the amplitude and phase characteristics of diffractions. Through the systematic generation of a training dataset using synthetic modeling based on t-distributed stochastic neighbor embedding (t-SNE) analysis, this technique extracts not only faint diffractions, but also diffraction tails overlapped by strong reflection events. We also demonstrated that the DL model pre-trained with basic synthetic dataset can be applied to seismic field data through transfer learning. Because the diffractions extracted by our method preserve the amplitude and phase, they can be used for velocity model building and high-resolution diffraction imaging.

Reconfigurable terahertz metasurfaces coherently controlled by wavelength-scale-structured light

Structuring light–matter interaction at a deeply subwavelength scale is fundamental to optical metamaterials and metasurfaces. Conventionally, the operation of a metasurface is determined by the collective electric polarization response of its lithographically defined structures. The inseparability of electric polarization and current density provides the opportunity to construct metasurfaces from current elements instead of nanostructures. Here, we realize metasurfaces using structured light rather than structured materials. Using coherent control, we transfer structure from light to transient currents in a semiconductor, which act as a source for terahertz radiation. A spatial light modulator is used to control the spatial structure of the currents and the resulting terahertz radiation with a resolution of 5.6 ± 0.8 μm $5.6\pm 0.8\mathrm{\,\mu m}$ , or approximately λ / 54 $\lambda /54$ at a frequency of 1 THz. The independence of the currents from any predefined structures and the maturity of spatial light modulator technology enable this metasurface to be reconfigured with unprecedented flexibility.

Photonic Crystal Polymeric Thin-Film Dye-Lasers for Attachable Strain Sensors

In this report, using two-dimensional photonic crystals (PhC) and a one-dimensional PhC nano-beam cavity, we realized the development of all-polymeric dye-lasers on a dye-doped, suspended poly-methylmethacrylate film with a wavelength-scale thickness. In addition to the characterization of basic lasing properties, we also evaluated its capacity to serve as an attachable strain sensor. Through experimentation, we confirmed the stable lasing performances of the dye-laser attaching on a rough surface. Moreover, we also theoretically studied the wavelength responses of the utilized PhC resonators to stretching strain and further improved them via the concept of strain shaping. The attachability and high strain sensing response of the presented thin film PhC dye-lasers demonstrate their potential as attachable strain sensors.