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Register a new userRealistic gravitational focusing of meteoroid streams
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The number density and flux of a meteoroid stream is enhanced near a massive body due to the phenomenon known as gravitational focusing. The greatest enhancement occurs directly opposite the massive body from the stream radiant: as an observer approaches this location, the degree of focusing is unbound for a perfectly collimated stream. However, real meteoroid streams exhibit some dispersion in radiant and speed that will act to eliminate this singularity. In this paper, we derive an analytic approximation for this smoothing that can be used in meteoroid environment models and is based on real measurements of meteor shower radiant dispersion.
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Meteoroid modelling of fireball data typically uses a one dimensional model along a straight line triangulated trajectory. The assumption of a straight line trajectory has been considered an acceptable simplification for fireballs, but it has not been rigorously tested. The unique capability of the Desert Fireball Network (DFN) to triangulate discrete observation times gives the opportunity to investigate the deviation of a meteoroids position to different model fits. Here we assess the viability of a straight line assumption for fireball data in two meteorite-dropping test cases observed by the Desert Fireball Network (DFN) in Australia -- one over 21 seconds (textit{DN151212_03}), one under 5 seconds (textit{DN160410_03}). We show that a straight line is not valid for these two meteorite dropping events and propose a three dimensional particle filter to model meteoroid positions without any straight line constraints. The single body equations in three dimensions, along with the luminosity equation, are applied to the particle filter methodology described by citet{Sansom2017}. Modelling fireball camera network data in three dimensions has not previously been attempted. This allows the raw astrometric, line-of-sight observations to be incorporated directly. In analysing these two DFN events, the triangulated positions based on a straight line assumption result in the modelled meteoroid positions diverging up to $3.09, km$ from the calculated observed point (for textit{DN151212_03}). Even for the more typical fireball event, textit{DN160410_03}, we see a divergence of up to $360$,m. As DFN observations are typically precise to $<100$,m, it is apparent that the assumption of a straight line is an oversimplification that will affect orbit calculations and meteorite search regions for a significant fraction of events.
This is an overview of recent research on meteors and the parent bodies from which they are produced. While many meteor showers result from material ejected by comets, two out of the three strongest annual showers (the Geminids and the Quadrantids) are associated with objects whose physical properties are apparently those of asteroids. In the last decades dynamical and observational studies have confirmed the existence of a number of Asteroid-Meteoroid Complexes, comprising streams and several macroscopic, split fragments. Spectroscopy of meteor showers has been utilized to investigate the perihelion-dependent thermal alteration while in interplanetary space. In this chapter, we review characteristics of the complexes, including those of some minor streams. The scientific interest is to trace the physical and dynamical properties of the complexes back to the evolutionary pathways to learn about the variety of production processes of meteoroids to form streams. We also discuss open questions in the field for the next decade.
We propose an approach to generate realistic and high-fidelity stock market data based on generative adversarial networks (GANs). Our Stock-GAN model employs a conditional Wasserstein GAN to capture history dependence of orders. The generator design includes specially crafted aspects including components that approximate the markets auction mechanism, augmenting the order history with order-book constructions to improve the generation task. We perform an ablation study to verify the usefulness of aspects of our network structure. We provide a mathematical characterization of distribution learned by the generator. We also propose statistics to measure the quality of generated orders. We test our approach with synthetic and actual market data, compare to many baseline generative models, and find the generated data to be close to real data.
Fireball observations from camera networks provide position and time information along the trajectory of a meteoroid that is transiting our atmosphere. The complete dynamical state of the meteoroid at each measured time can be estimated using Bayesian filtering techniques. A particle filter is a novel approach to modelling the uncertainty in meteoroid trajectories and incorporates errors in initial parameters, the dynamical model used and observed position measurements. Unlike other stochastic approaches, a particle filter does not require predefined values for initial conditions or unobservable trajectory parameters. The Bunburra Rockhole fireball (Spurny et al. 2012), observed by the Australian Desert Fireball Network (DFN) in 2007, is used to determine the effectiveness of a particle filter for use in fireball trajectory modelling. The final mass is determined to be $2.16pm1.33, kg$ with a final velocity of $6030pm216, m,s^{-1}$, similar to previously calculated values. The full automatability of this approach will allow an unbiased evaluation of all events observed by the DFN and lead to a better understanding of the dynamical state and size frequency distribution of asteroid and cometary debris in the inner solar system.
The orbital distributions of dust particles in interplanetary space are inferred from several meteoroid data sets under the constraints imposed by the orbital evolution of the particles due to the planetary gravity and Poynting-Robertson effect. Infrared observations of the zodiacal cloud by the COBE DIRBE instrument, flux measurements by the dust detectors on board Galileo and Ulysses spacecraft, and the crater size distributions on lunar rock samples retrieved by the Apollo missions are fused into a single model. Within the model, the orbital distributions are expanded into a sum of contributions due to a number of known sources, including the asteroid belt with the emphasis on the prominent families Themis, Koronis, Eos and Veritas, as well as comets on Jupiter-encountering orbits. An attempt to incorporate the meteor orbit database acquired by the AMOR radar is also discussed.
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