Interpreting asteroid photometry and polarimetry using a model of shadowing and coherent backscattering

The shadow-hiding models for the opposition effect and negative polarization of atmosphereless solar system bodies do not explain some experimental findings, such as the enhancing opposition effect and negative polarization with decreasing particle size down to wavelength scales. The enhancement for laboratory photometric and polarimetric data on artificial glass samples with different particle size is shown. These results are in agreement with the so-called coherent backscattering or interference mechanism proposed for the interpretation of the opposition effect and negative polarization. Two different approaches for describing the opposition effect and negative polarization produced by the shadow-interference mechanism were developed. One is based on exact electromagnetic solutions for simple scattering systems that include dipole-dipole and dipole-surface coupling; The other is based on a point-scatterer approximation characterized by model photometric and polarimetric phase functions, and the mutual shadowing effect is derived using virtual volumes associated with the point-scatterers. Both approaches yield qualitatively similar results, although neither is entirely satisfactory. We regard them as prototypes for a future unified model of shadowing and coherent backscattering. The sharp opposition effect of 44 Nysa and the asteroid albedo-polarization rule are here explained using the point-scatterer approach

Determinations of Shape and Photometric Phase Function of Selected Asteroids

The ground-based photometric observations of asteroids still is the main source to understand their basic physical properties, even though some space mission and space-based instruments have been applied in physical studies of asteroids. Owing to developments on scattering theories and 3D shape models of asteroid, we can carry out determination for basic physical parameters of asteroids from the photometric data. Here, we present photometric observations for some selected asteroids and light inversion results for these asteroids. In detail, they are: (1) To determine photometric phase functions of asteroids (107)Camilla and (106) Dione considering an ellipsoid shape and a cellinoid shape respectively; and (2) To inverse convex shape of main-belt slow rotating asteroids (168) Sibylla and (346)Hermentaria and a near Earth asteroid (3200) Phaethon. Based on derived photometric phase functions, the geometric albedo, and even rough taxonomic classification of asteroids are inferred. With the virtual photometry Monta Carlo method, the uncertainties of spin parameters of selected asteroids were compared.Peer reviewe

Radiation fields in radiative transfer : spherical-wavelet representation

The spherical wavelet based on the lifting scheme is introduced for adaptive discrete-ordinate sampling of the radiation fields, particularly, in the radiative transfer computation using iterative schemes. The lifting scheme for wavelet transform is described from an implementation point of view, including the construction of hierarchical geodesic grids on the sphere and wavelet constructions. In addition, we compare the method with the conventional spherical harmonics, numerically investigating the transformation error and efficiency. The transformation matrices are built in the least-squares sense. The results demonstrate the feasibility of using spherical wavelets as an adaptive discrete-ordinate sampling method at the cost of O(N), where N is the number of significant coefficients. (C) 2019 The Authors. Published by Elsevier Ltd.Peer reviewe

Dynamics of Interstellar Dust Particles in Electromagnetic Radiation Fields

We establish a theoretical framework for solving the equations of motion for an arbitrarily shaped, isotropic, and homogeneous dust particle in the presence of radiation pressure. The scattering problem involved is solved by a surface integral equation method, and a rudimentary sketch of the numerical implementation is introduced with preliminary results agreeing with predictions.Peer reviewe

Törmäilevät asteroidit

Planeetta Maa tapaa radallaan pienempiä Auringon kiertolaisia: asteroideja, komeettoja ja meteoroideja, edellisten palasia. Pienkappaleet voivat törmätä Maahan monimuotoisin seurauksin: ilmakehä suojaa meitä useimmilta törmääjiltä, muttei pysäytä maailmanlaajuisia katastrofeja aiheuttavia kilometriluokan törmääjiä

Polarized scattering by Gaussian random particles under radiative torques

We study the internal alignment of a statistical ensemble of Gaussian random ellipsoids with respect to the radiation direction. We solve the rigid body dynamics due to scattering forces and torques, using a numerically exact and efficient T-matrix solver for arbitrary particle shapes and compositions. We then compare the polarization of the aligned ensemble to a randomly oriented ensemble and a perfectly aligned ensemble. We find that the ensemble becomes partially aligned under monochromatic radiation and that the internal alignment has an significant effect on the intensity and polarization of the scattered light. (C) 2017 Elsevier Ltd. All rights reserved.Peer reviewe

Taxonomy of Asteroids From the Legacy Survey of Space and Time Using Neural Networks

The Legacy Survey of Space and Time (LSST) is one of the ongoing or future surveys, together with the Gaia and Euclid missions, which will produce a wealth of spectrophotometric observations of asteroids. This article shows how deep learning techniques with neural networks can be used to classify the upcoming observations, particularly from LSST, into the Bus-DeMeo taxonomic system. We report here a success ratio in classification up to 90.1% with a reduced set of Bus-DeMeo types for simulated observations using the LSST photometric filters. The scope of this work is to introduce tools to link future observations into existing Bus-DeMeo taxonomy.Peer reviewe

Light scattering by fractal roughness elements on ice crystal surfaces

Atmospheric ice crystals scatter sunlight, affecting Earth's climate through the radiation properties of cirrus clouds. Naturally occurring surface roughness and its effect on the scattering properties of ice crystals remain largely unknown. Scattering by ice crystals with rough surfaces is studied by placing a finite, thin surface-roughness element on an infinitely large, planar vacuum-ice boundary. The elements are generated using a statistical model based on fractional Brownian motion. The horizontal roughness scale is described by the Hurst exponent Hand the vertical roughness scale with the root-mean-square roughness parameter R-q. The computations are performed with the surface mode of the Discrete Dipole Approximation software ADDA (version 1.34b). Several incident directions for wavelength of 0.5 mu m from both above and below the planar surface are studied. A refractive index for ice m = 1.313 + i5.889 x10(-10) is used throughout the computations. Results are averaged over ten rough surface realizations for a specific H, R-q-pair. Scattering by the rough elements is compared to that by the corresponding smooth elements. The rougher the element is, the more of the scattered intensity is transmitted through the surface. The rough elements have distinctively smoother angular distributions for the degree of linear polarization than their smooth counterparts. Also, it is found that while roughness itself affects polarization, the exact surface morphology does not seem to have a significant effect. The vertical roughness scale R-q has a larger effect on the light scattering results than the horizontal scale H. Enhanced angular scattering is detected in directions nearly parallel to the vacuum-ice boundary within the ice medium. The phenomenon is explained with a strong internal reflection mechanism. The model for surface roughness, along with the light scattering methodology used here, could be incorporated into geometric optics ray-tracing computations for large ice crystals and other particles. (C) 2021 The Authors. Published by Elsevier Ltd.Peer reviewe

Scattering of light by dense particulate media in the geometric optics regime

We present a hybrid radiative transfer geometric optics approximation to model multiple light scattering in arbitrary finite discrete random media in the geometric optics regime. In the hybrid model, the medium is divided into a mantle composed of discrete particles and into a diffusely scattering core. In the mantle, multiple scattering is handled by using a ray-tracing algorithm with the generalized Snel’s law for inhomogeneous waves, whereas, in the core, ray tracing with diffuse scatterers is incorporated to approximate multiple scattering and absorption. The extinction distances required to compute the scattering in the core are derived numerically by tracing the distances of the scattering and absorption events instead of using the classical extinction mean free path length. We have written a new framework that can treat arbitrary meshes consisting of watertight surface meshes with multiple diffuse scatterers and refractive indices. Comparison between the “ground truth” obtained from pure geometric optics ray tracing, the solutions obtained by using radiative transfer, and the hybrid model show that the hybrid model can produce better results, particularly, if a densely-packed medium is studied. In the future, the new approximation could be used to solve light scattering from larger media, such as asteroid surfaces, that are out of reach for the pure geometric optics methods due to their computational complexity.Peer reviewe

Asteroid Spectral Taxonomy Using Neural Networks

Aims. We explore the performance of neural networks in automatically classifying asteroids into their taxonomic spectral classes. We particularly focus on what the methodology could offer the ESA Gaia mission.Methods. We constructed an asteroid dataset that can be limited to simulating Gaia samples. The samples were fed into a custom-designed neural network that learns how to predict the samples' spectral classes and produces the success rate of the predictions. The performance of the neural network is also evaluated using three real preliminary Gaia asteroid spectra.Results. The overall results show that the neural network can identify taxonomic classes of asteroids in a robust manner. The success in classification is evaluated for spectra from the nominal 0.45-2.45 mu m wavelength range used in the Bus-DeMeo taxonomy, and from a limited range of 0.45-1.05 mu m following the joint wavelength range of Gaia observations and the Bus-DeMeo taxonomic system.Conclusions. The obtained results indicate that using neural networks to execute automated classification is an appealing solution for maintaining asteroid taxonomies, especially as the size of the available datasets grows larger with missions like Gaia.Peer reviewe