Scattering Research Articles

Research and development of a muon entrance trigger for the muEDM experiment at PSI

The muEDM experiment at the Paul Scherrer Institute (PSI) in Switzerland aims to probe the muon electric dipole moment (EDM) using the frozen-spin technique in a compact storage ring, with a sensitivity of 6×10−23 e⋅cm. A fast entrance detector is expected to work in concert with a magnetic pulse generator to direct muons into the desired orbit. Simultaneously, the entrance detector is designed to veto muons that exceed the apparatus's admittance without introducing significant multiple scatterings. We developed a prototype entrance trigger detector consisting of a thin scintillator for detecting incoming muons and four wall scintillators as veto detectors. The prototype was tested at 27.5 MeV/c at the πE1 beamline at PSI. A total of 7×105 events were collected, which were read out by SiPMs coupled to the plastic scintillators under two different beam tunes. These events were analyzed to characterize the detector's performance, which was also cross-checked with Monte Carlo simulations that took into account the beam phase space and scintillation processes.

This is MATE: A Multiple scAttering correcTion rEtrieval algorithm for accurate lidar profiling of seawater optical properties

Lidar has the capability to measure seawater vertical optical properties efficiently both day-time and night-time, though accurate retrieval is still challenging due to multiple scattering. Herein, we propose a Multiple scAttering correcTion and rEtrieval (MATE) algorithm suitable for shipborne, airborne and spaceborne lidars. The MATE algorithm provides the synchronous depth-resolved absorption, backscattering and diffuse attenuation coefficients of seawater. A good consistency was obtained between retrieved results and the in situ data with a root mean square relative difference (RSMRD) of 6.36% for diffuse attenuation coefficient, corresponding to an improvement of 2 times over methods that neglect multiple scattering. These results indicate that the MATE algorithm has valuable application potential in the quantitative evaluation of marine biological parameters.

Design Optimization and Tradeoff Analysis of an Actuated Continuum Probe for Pulmonary Nodule Localization and Resection.

Pulmonary nodules are abnormal tissue masses in the lungs, typically less than 3.0 cm in diameter, commonly detected during imaging of the chest and lungs. While most pulmonary nodules are not cancerous, surgical resection may be required if growth is detected between scans. This resection is typically performed without the benefit of intraoperative imaging, making it difficult for surgeons to confidently provide appropriate margins. To enhance the efficacy of wedge resection, researchers have developed a modified ultrasound imaging approach that utilizes both multiple scattering (MS) and single scattering (SS) to enhance the accuracy of margin delineation. Clinical deployment of this novel ultrasound technology requires a highly maneuverable ultrasound probe, ideally one that could be deployed and actuated with minimal invasiveness. This study details the design optimization and tradeoff analysis of an actuated continuum probe for pulmonary nodule localization and resection. This device, deployed through intercostal ports, would enable the intraoperative imaging and precise mapping of nodules for improved margin delineation and patient outcomes. To achieve this objective, multiple objective genetic algorithms (MOGAs) and a design of experiments (DOE) study are used to explore the design space and quantify key dimensional relationships and their effects on probe actuation.

Tuning Spin-Polarized Lifetime at High Carrier Density through Deformation Potential in Dion-Jacobson-Phase Perovskites.

The control of spin relaxation mechanisms is of great importance for spintronics applications as well as for fundamental studies. Layered metal-halide perovskites represent an emerging class of semiconductors with rich optical spin physics, showing potential for spintronic applications. However, a major hurdle arises in layered metal-halide perovskites with strong spin-orbit coupling, where the spin lifetime becomes extremely short due to D'yakonov-Perel' scattering and Bir-Aronov-Pikus at high carrier density. Using the circularly polarized pump-probe transient reflection technique, we experimentally reveal the important scattering for spin relaxation beyond the electron-hole exchange strength in the Dion-Jacobson (DJ)-type 2D perovskites (3AMP)(MA)n-1PbnI3n+1 [3AMP = 3-(aminomethyl)piperidinium, n = 1-4]. Despite a more than 10-fold increase in carrier concentration, the spin lifetimes for n = 3 and 4 are effectively maintained. We reveal neutral impurity and polar optical phonon scatterings as significant contributors to the momentum relaxation rate. Furthermore, we show that more octahedral distortions induce a larger deformation potential which is reflected on the acoustic phonon properties. Coherent acoustic phonon analysis indicates that the polaronic effect is crucial in achieving control over the scattering mechanism and ensuring spin lifetime protection, highlighting the potential of DJ-phase perovskites for spintronic applications.

Detecting neutrinos from supernova bursts in PandaX-4T* *This project is Supported in part by the National Natural Science Foundation of China (12090060, 12090063, 12105052, 12005131, 11905128, 11925502), and the Office of Science and Technology, Shanghai Municipal Government, China (22JC1410100)

Neutrinos from core-collapse supernovae are essential for understanding neutrino physics and stellar evolution. Dual-phase xenon dark matter detectors can be used to track explosions of galactic supernovae by detecting neutrinos through coherent elastic neutrino-nucleus scatterings. In this study, a variation of progenitor masses and explosion models are assumed to predict neutrino fluxes and spectra, which result in the number of expected neutrino events ranging from 6.6 to 13.7 at a distance of 10 kpc over a 10-s duration with negligible backgrounds at PandaX-4T. Two specialized triggering alarms for monitoring supernova burst neutrinos are built. The efficiency of detecting supernova explosions at various distances in the Milky Way is estimated. These alarms will be implemented in the real-time supernova monitoring system at PandaX-4T in the near future, which will provide supernova early warnings for the astronomical community.

Simple numerical X-ray polarization models of reflecting axially symmetric structures around accreting compact objects

ABSTRACT We present a series of numerical models suitable for X-ray polarimetry of accreting systems. First, we provide a spectropolarimetric routine that integrates reflection from inner optically thick walls of a geometrical torus of arbitrary size viewed under general inclination. In the studied example, the equatorial torus is illuminated by a central isotropic source of X-ray power-law emission, representing a hot corona. Nearly neutral reprocessing inside the walls is precomputed by Monte Carlo code stokes that incorporates both line and continuum processes, including multiple scatterings and absorption. We created a new xspec model, called xsstokes, which in this version enables efficient X-ray polarimetric fitting of the torus parameters, observer’s inclination and primary emission properties, interpolating for arbitrary state of primary polarization. Comparison of the results to a Monte Carlo simulation allowing partial transparency shows that the no-transparency condition may induce different polarization by tens of per cent. Allowing partial transparency leads to lower/higher polarization fraction, if the resulting polarization orientation is perpendicular/parallel to the rotation axis. We provide another version of xsstokes that is suitable for approximating nearly neutral reflection from a distant optically thick disc of small geometrical thickness. It assumes local illumination averaged for a selected range of incident angles, representing a toy model of a diffuse corona of various physical extent. Assessing both xsstokes variants, we conclude that the resulting polarization can be tens of per cent and perpendicularly/parallelly oriented towards the rotation axis, if the reflecting medium is rather vertically/equatorially distributed with respect to a compact central source.

Garlic Origin Traceability and Identification Based on Fusion of Multi-Source Heterogeneous Spectral Information.

The chemical composition and nutritional content of garlic are greatly impacted by its production location, leading to distinct flavor profiles and functional properties among garlic varieties from diverse origins. Consequently, these variations determine the preference and acceptance among diverse consumer groups. In this study, purple-skinned garlic samples were collected from five regions in China: Yunnan, Shandong, Henan, Anhui, and Jiangsu Provinces. Mid-infrared spectroscopy and ultraviolet spectroscopy were utilized to analyze the components of garlic cells. Three preprocessing methods, including Multiple Scattering Correction (MSC), Savitzky-Golay Smoothing (SG Smoothing), and Standard Normalized Variate (SNV), were applied to reduce the background noise of spectroscopy data. Following variable feature extraction by Genetic Algorithm (GA), a variety of machine learning algorithms, including XGboost, Support Vector Classification (SVC), Random Forest (RF), and Artificial Neural Network (ANN), were used according to the fusion of spectral data to obtain the best processing results. The results showed that the best-performing model for ultraviolet spectroscopy data was SNV-GA-ANN, with an accuracy of 99.73%. The best-performing model for mid-infrared spectroscopy data was SNV-GA-RF, with an accuracy of 97.34%. After the fusion of ultraviolet and mid-infrared spectroscopy data, the SNV-GA-SVC, SNV-GA-RF, SNV-GA-ANN, and SNV-GA-XGboost models achieved 100% accuracy in both training and test sets. Although there were some differences in the accuracy of the four models under different preprocessing methods, the fusion of ultraviolet and mid-infrared spectroscopy data yielded the best outcomes, with an accuracy of 100%. Overall, the combination of ultraviolet and mid-infrared spectroscopy data fusion and chemometrics established in this study provides a theoretical foundation for identifying the origin of garlic, as well as that of other agricultural products.

Coupling static multiple light scattering (SMLS) analysis with the Hansen approach for the rationalization of the dispersibility and colloidal stability of TiO2 particle dispersions

While the characterization of dispersibility and colloidal stability remains a key step in many formulation processes, these notions are still confused, and colloidal stability is often interpreted as a direct consequence of dispersibility. In this study, Static Multiple Light Scattering (SMLS) measurements and the predictive Hansen approach are combined to distinguish and characterize the dispersibility and the colloidal stability of TiO2 P25 particles dispersed in pure and mixture of solvents. To this aim, an experimental protocol is proposed using fast time resolved SMLS measurements at a fixed height to assess suspension dispersibility under mechanical stirring as well as space and time resolved SMLS measurements of the suspension stability at rest. Dispersibility is quantified through a Dispersibility Index (DI) depending on the mean diameter of particles and transmission or backscattering signals standard deviation measured with SMLS under mechanical stirring. Quantification of colloidal stability is obtained from a Relative Turbiscan Stability Index (RTSI) measured at rest. Scoring of solvents is performed using the DI and the RTSI to build Hansen dispersibility and stability spheres respectively. It is found that the dispersibility and the stability spheres are clearly separated arguing that a lower colloidal stability is not necessarily a consequence of a poor dispersibility. Beyond this clarification, this combined SMLS-Hansen approach is a major step toward the optimization of dispersibility and stability of formulations. It can be also intended to find better dispersion media, greener and cheaper solvents to optimize particles suspensions, to reduce the content of costly stabilizing additive or to satisfy product regulatory requirements evolution.

Surface Scattering Expansion of the Casimir–Polder Interaction for Magneto-Dielectric Bodies: Convergence Properties for Insulators, Conductors, and Semiconductors

Fluctuation-induced forces are a hallmark of the interplay between fluctuations and geometry. We recently proved the existence of a multi-parametric family of exact representations of Casimir and Casimir–Polder interactions between bodies of arbitrary shape and material composition, admitting a multiple scattering expansion (MSE) as a sequence of inter-body and intra-body multiple wave scatterings. The approach requires no knowledge of the scattering amplitude (T-matrix) of the bodies. In this paper, we investigate the convergence properties of the MSE for the Casimir–Polder interaction of a polarizable particle with a macroscopic body. We consider representative materials from different classes, such as insulators, conductors, and semiconductors. Using a sphere and a cylinder as benchmarks, we demonstrate that the MSE can be used to efficiently and accurately compute the Casimir–Polder interaction for bodies with smooth surfaces.

Photonic Flatband Resonances in Multiple Light Scattering

Photonic Flatband Resonances in Multiple Light Scattering

Radar-Based Identification of Insect Species With Ensemble Learning Algorithms Utilizing Multiple Electromagnetic Scattering Parameters

Radar-Based Identification of Insect Species With Ensemble Learning Algorithms Utilizing Multiple Electromagnetic Scattering Parameters

A Hybrid Multiple Scattering Approach for Efficient Scattering Modeling of 2D Periodic Gratings

A Hybrid Multiple Scattering Approach for Efficient Scattering Modeling of 2D Periodic Gratings

Misspecification of Multiple Scattering in Scalar Wave Fields and its Impact in Ultrasound Tomography

Misspecification of Multiple Scattering in Scalar Wave Fields and its Impact in Ultrasound Tomography

High-Resolution SAR Imaging Characteristics for Multiple Scattering of Rotating Targets

High-Resolution SAR Imaging Characteristics for Multiple Scattering of Rotating Targets

A Novel Semi-Analytical Method for Modeling Polarized Oceanic Profiling LiDAR Multiple Scattering Signals

A Novel Semi-Analytical Method for Modeling Polarized Oceanic Profiling LiDAR Multiple Scattering Signals

An Efficient Multiple Scattering Solution to Radiative Transfer Equations in Strong Forward Scattering Environments for Vegetated Land Emission and its Representation Through an Equivalent Albedo-Tau Formalism

An Efficient Multiple Scattering Solution to Radiative Transfer Equations in Strong Forward Scattering Environments for Vegetated Land Emission and its Representation Through an Equivalent Albedo-Tau Formalism

Time Series Classification with Multiple Wavelength Scattering Signals for Nuisance Alarm Mitigation

Smoke detectors are the most widely used fire detectors due to their high sensitivity. However, they have persistently faced issues with false alarms, known as nuisance alarms, as they cannot distinguish smoke particles, and their responsiveness varies depending on the particle size and concentration. Although technologies for distinguishing smoke particles have shown promising results, the hardware limitations of smoke detectors necessitate an intelligent approach to analyze scattering signals of various wavelengths and their temporal changes. In this paper, we propose a pipeline that can distinguish smoke particles based on scattering signals of various wavelengths as input. In the data extraction phase, we propose methods for extracting datasets from time series data. We propose a method that combines traditional approaches, early detection methods, and a Dynamic Time Warping technique that utilizes only the shape of the signal without preprocessing. In the learning model and classification phase, we present a method to select and compare various architectures and hyperparameters to create a model that achieves the best classification performance for time series data. We create datasets for six different targets in our presented sensor and smoke particle test environment and train classification models. Through performance comparisons, we identify architecture and parameter combinations that achieve up to 98.7% accuracy. Ablation studies under various conditions demonstrate the validity of the chosen architecture and the potential of other models.

Polarization-artifact reduction and accuracy improvement of Jones-matrix polarization-sensitive optical coherence tomography by multi-focus-averaging based multiple scattering reduction.

Polarization-sensitive optical coherence tomography (PS-OCT) is a promising biomedical imaging tool for the differentiation of various tissue properties. However, the presence of multiple-scattering (MS) signals can degrade the quantitative polarization measurement accuracy. We demonstrate a method to reduce MS signals and increase the measurement accuracy of Jones matrix PS-OCT. This method suppresses MS signals by averaging multiple Jones matrix volumes measured using different focal positions. The MS signals are decorrelated among the volumes by focus position modulation and are thus reduced by averaging. However, the single scattering signals are kept consistent among the focus-modulated volumes by computational refocusing. We validated the proposed method using a scattering phantom and a postmortem medaka fish. The results showed reduced artifacts in birefringence and degree-of-polarization uniformity measurements, particularly in deeper regions in the samples. This method offers a practical solution to mitigate MS-induced artifacts in PS-OCT imaging and improves quantitative polarization measurement accuracy.

The Role of Multiple Light Scattering in the Interpretation of Transmission Spectra of Magnetic Fluids With Magnetite Nanoparticles in the Visible and Near-IR Regions

The Role of Multiple Light Scattering in the Interpretation of Transmission Spectra of Magnetic Fluids With Magnetite Nanoparticles in the Visible and Near-IR Regions

Artificial Magnetism in Theory of Wave Multiple Scattering by Random Ensemble of Nonmagnetic Spheres with Negative Dielectric Permittivity

Artificial Magnetism in Theory of Wave Multiple Scattering by Random Ensemble of Nonmagnetic Spheres with Negative Dielectric Permittivity