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Functional devices for terahertz (THz) polarization detection in transmission mode are highly desired in integrated applications, but traditional polarization measurement systems are bulky and highly cost. The combination between all-silicon metasurfaces and focused beams carrying polarization information has offered a new opportunity for miniaturized polarization detection behavior. Here, we investigate and experimentally demonstrate a new scheme for realizing efficiently miniaturized polarization detection behavior based on the polarization multiplexing encoding technique. The full-Stokes parameter matrix of the incident polarization state can be reconstructed in a single snapshot by using a microprobe to record, pixel by pixel, the complex amplitude information contained in a pre-designed plane. Subsequently, the polarization detection capability of the proposed design principle is evaluated using random polarization states defined on the surface of a standard Poincaré sphere (PS). Such a scheme offers potential applications for the development of compact photonic meta-platforms for polarization detection in transmission mode, being highly favored in polarization high-resolution imaging, remote sensing, and THz communications.

Blazars are attractive objects for astronomers to observe in order to burrow into the magnetic field in the relativistic jet. This paper presents TimeTubes as a novel visualization scheme that allows astronomers to interactively explore characteristic temporal variation patterns in observed blazar datasets. In the TimeTubes spatialization, the two Stokes parameters and their errors with a common timestamp are transformed into an ellipse. A series of such ellipses are aligned in parallel along the timeline to form a 3D volumetric tube. The resulting tube is then colorized by the observed intensities and colors of the blazar, and finally volume-rendered. A designated user interface is provided with visual exploration functions according to Shneiderman's Visual Information Seeking Mantra. In the latest version, an auxiliary mechanism, called visual data fusion, was incorporated to ameliorate data- and mapping-inherent uncertainties for more efficient and effective visual exploration.

We provide analysis to determine the effects of gravitational waves on electromagnetic waves, using perturbation theory in general relativity. Our analysis is performed in a completely covariant manner without invoking any coordinates. For a given observer, using the geometrical-optics approach, we work out the perturbations of the phase, amplitude, frequency and polarization properties–axes of ellipse and ellipticity of light, due to gravitational waves. With regard to the observation of gravitational waves, we discuss the measurement of Stokes parameters, through which the antenna patterns are presented to show the detectability of the gravitational wave signals.

Moon Mineralogy Mapper (M3), the hyperspectral sensor of ISRO’s Chandrayaan 1 mission, dedicated to map the surface mineral composition, provided an opportunity to map the lunar regolith in Global and Target modes. These high resolution hyperspectral data is used to recalibrate the pioneer work of Lucey et al. (2000) and thus estimated the FeO and TiO2 contents of the regolith. As the FeO and TiO2 estimations have to handle a huge amount of data, Support Vector Regression analysis (SVR) is introduced to reform the FeO and TiO2 wt % equations for Apollo and Luna landing sites. These equations with the optimized origin are used to estimate the FeO and TiO2 contents of the target locations. Catharina crater of the lunar near side is taken as the study area and FeO and TiO2 wt% of the crater are estimated with M3 data. Composite chemical content (FeO wt%+ TiO2 wt %) of the Catharina crater is estimated. LRO mini RF, Hybrid-polarized, dual-frequency synthetic aperture radar of LRO mission is used to characterize the back scattering properties of the crater surface. Stokes parameters are extracted from the LRO mini RF SAR data for the same study area. Composite chemical content estimated using M3 data is compared with the Stokes total intensity parameter extracted from the LRO mini RF data. The total intensity parameter (Stokes vector S1) is directly proportional to the composite chemical content and thus shows a linear relationship.

Formation of the H β λ 4861.34 Å line is an important topic related to the diagnosis of the basic configuration of magnetic fields in the solar and stellar chromospheres. Specifically, broadening of the H β λ 4861.34 Å line occurs due to the magnetic and micro-electric fields in the solar atmosphere. The formation of H β in the model umbral atmosphere is presented based on the assumption of non-local thermodynamic equilibrium. It is found that the model umbral chromosphere is transparent to the Stokes parameters of the H β line, which implies that the observed signals of magnetic fields at sunspot umbrae via the H β line originate from the deep solar atmosphere, where lg τ c ≈ −1 (about 300 km in the photospheric layer for our calculations). This is in contrast to the observed Stokes signals from non-sunspot areas, which are thought to primarily form in the solar chromosphere.

The Soil Moisture Active Passive (SMAP) satellite carries an L-band microwave radiometer. This sensor can be used to observe global soil moisture (SM) and sea surface salinity (SSS) within the protected L-band spectrum (1400–1427 MHz). Owing to the complex effects of radio frequency interference (RFI), the SM and SSS data are missing or have low accuracy. In this paper, a constrained iterative adaptive algorithm for the detection, identification, and localization of RFI sources is designed, named MICA-BEID. The algorithm synthesizes antenna temperatures for the third and fourth Stokes parameters before RFI filtering, creating a new polarization parameter called WSPDA, designed to approximate the level of RFI interference on the L-band microwave radiometer. The algorithm then utilizes the WSPDA intensity and distribution density of RFI detection samples to enhance the identification and classification of RFI sources across various intensity levels. By utilizing statistical methods such as the probability density function (PDF) and the cumulative distribution function (CDF), the algorithm dynamically adjusts adaptive parameters, including the RFI detection threshold and the maximum effective radius of RFI sources. Through the application of multiple iterative clustering methods, the algorithm can adaptively detect and identify RFI sources at various satellite orbits and intensity levels. Through extensive comparative analysis with other localization results and known RFI sources, the MICA-BEID algorithm can achieve optimal localization accuracy of approximately 1.2 km. The localization of RFI sources provides important guidance for identifying and turning off illegal RFI sources. Moreover, the localization and long-time-series characteristic analysis of RFI sources that cannot be turned off is of significant value for simulating the spatial distribution characteristics of localized RFI source intensity in local areas.

Long‐wavelength infrared (LWIR) circular polarimetric imaging plays an important role in many areas. The immediacy of polarimetric imaging and the miniaturization of devices drive considerable efforts to division‐of‐focal‐plane‐array (DoFPA) circular polarimeters. However, the realization of such detectors is hampered by low polarization discrimination, reduced absorption in the detection material, and fabrication complexity. The situation becomes more serious in the LWIR range since the pixel size is only a few wavelengths of the incident light. Here, a quantum well infrared photodetector based LWIR DoFPA circular polarimeter featuring a 320 × 256 pixel array integrated with a chiral meta‐mirror array is established. The spectral range of this detector is from 10 to 11 µm. Taking advantage of the dual polarization selection, a CPER of 23.3 is achieved for the pixels integrated with the same chiral meta‐mirror structure, and a CPER of 5.67 for the pixels integrated with left‐ and right‐handed chiral meta‐mirror structures in a checkerboard pattern. The peak responsivity is improved by a factor of 9.13 compared to a standard reference device. With the LWIR DoFPA circular polarimeter, Stokes parameter S3 imaging is achieved with a noise equivalent S3 difference of 1.16×10−4, and demonstrate background suppression and target highlighting. A quantum well infrared photodetector based long‐wavelength infrared division‐of‐focal‐plane‐array circular polarimeter featuring a 320 × 256 pixel array integrated with a chiral meta‐mirror structure array is established. The device achieves a circular polarization extinction ratio of 5.67, a 9.13‐fold enhancement in responsivity, a noise equivalent S3 difference as small as 1.16 × 10−4, and enables background‐suppressed target‐highlighted imaging.

Herein, we give an overview of several less explored structural and optical characterization techniques useful for biomaterials. New insights into the structure of natural fibers such as spider silk can be gained with minimal sample preparation. Electromagnetic radiation (EMR) over a broad range of wavelengths (from X-ray to THz) provides information of the structure of the material at correspondingly different length scales (nm-to-mm). When the sample features, such as the alignment of certain fibers, cannot be characterized optically, polarization analysis of the optical images can provide further information on feature alignment. The 3D complexity of biological samples necessitates that there be feature measurements and characterization over a large range of length scales. We discuss the issue of characterizing complex shapes by analysis of the link between the color and structure of spider scales and silk. For example, it is shown that the green-blue color of a spider scale is dominated by the chitin slab’s Fabry–Pérot-type reflectivity rather than the surface nanostructure. The use of a chromaticity plot simplifies complex spectra and enables quantification of the apparent colors. All the experimental data presented herein are used to support the discussion on the structure–color link in the characterization of materials.

The design and performance analysis of polarization rotation and conversion (PRC)-based 3 × 3 ternary logic switch using gallium arsenide-based microring resonator (MRR) is investigated in the present communication. The three different polarization states of light represent the three distinct logic levels (− 1, 0, and 1). A pump source with high-intensity and the input light’s polarization state works together to change the output polarization state into one of the three desirable polarization states. The proposed all-optical ternary circuit is numerically investigated at 2.5 Tbps using INTERCONNECT simulation platform. The Stokes parameter and Jones matrix approaches are used to validate the results that were produced. The main benefit of the suggested method is that a single MRR can generate 18 different logical functions using just one circuit.

The geophysical properties of snow are essential to study the mountain snow/glacier system and can be used as an indicator for any related hazard. In this study, an attempt has been made to model the geophysical properties of snow, such as dielectric, density, and wetness using the Sentinel–1 dual-polarized SLC product. A state-of-the-art inversion model has been developed using Sentinel–1 derived stokes parameters to estimate snow dielectric and subsequently used to model density and wetness employing Looyega's and Denoth's equations. The proposed inclusion of stokes parameters in the inversion model has significantly predicted the results. The respective modeled and in-situ snow dielectric, density, and wetness show a good coefficient of determination (R2 > 0.7) with 95% confidence. Utilizing the field-measured values, the estimated root mean squared error (RMSE) of snow dielectric, density, and wetness, is 0.26, 0.08 g/cm3, and 0.84, respectively. The comparison of the proposed model with some of the existing models reflects its good efficiency in predicting the snow geophysical parameters.