3,034 research outputs found

    Improved Algorithms for Radar-based Reconstruction of Asteroid Shapes

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    We describe our implementation of a global-parameter optimizer and Square Root Information Filter (SRIF) into the asteroid-modelling software SHAPE. We compare the performance of our new optimizer with that of the existing sequential optimizer when operating on various forms of simulated data and actual asteroid radar data. In all cases, the new implementation performs substantially better than its predecessor: it converges faster, produces shape models that are more accurate, and solves for spin axis orientations more reliably. We discuss potential future changes to improve SHAPE's fitting speed and accuracy.Comment: 12 pages, 9 figure

    Prospects of dynamical determination of General Relativity parameter beta and solar quadrupole moment J2 with asteroid radar astronomy

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    We evaluated the prospects of quantifying the parameterized post-Newtonian parameter beta and solar quadrupole moment J2 with observations of near-Earth asteroids with large orbital precession rates (9 to 27 arcsec century−1^{-1}). We considered existing optical and radar astrometry, as well as radar astrometry that can realistically be obtained with the Arecibo planetary radar in the next five years. Our sensitivity calculations relied on a traditional covariance analysis and Monte Carlo simulations. We found that independent estimates of beta and J2 can be obtained with precisions of 6×10−46\times10^{-4} and 3×10−83\times10^{-8}, respectively. Because we assumed rather conservative observational uncertainties, as is the usual practice when reporting radar astrometry, it is likely that the actual precision will be closer to 2×10−42\times10^{-4} and 10−810^{-8}, respectively. A purely dynamical determination of solar oblateness with asteroid radar astronomy may therefore rival the helioseismology determination.Comment: The astrophysical journal (ApJ), in pres

    Bi-class classification of humpback whale sound units against complex background noise with Deep Convolution Neural Network

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    Automatically detecting sound units of humpback whales in complex time-varying background noises is a current challenge for scientists. In this paper, we explore the applicability of Convolution Neural Network (CNN) method for this task. In the evaluation stage, we present 6 bi-class classification experimentations of whale sound detection against different background noise types (e.g., rain, wind). In comparison to classical FFT-based representation like spectrograms, we showed that the use of image-based pretrained CNN features brought higher performance to classify whale sounds and background noise.Comment: arXiv admin note: text overlap with arXiv:1702.02741 by other author

    Yarkovsky Drift Detections for 247 Near-Earth Asteroids

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    The Yarkovsky effect is a thermal process acting upon the orbits of small celestial bodies, which can cause these orbits to slowly expand or contract with time. The effect is subtle (da/dt ~ 10^-4 au/My for a 1 km diameter object) and is thus generally difficult to measure. We analyzed both optical and radar astrometry for 600 near-Earth asteroids (NEAs) for the purpose of detecting and quantifying the Yarkovsky effect. We present 247 NEAs with measured drift rates, which is the largest published set of Yarkovsky detections. This large sample size provides an opportunity to examine the Yarkovsky effect in a statistical manner. In particular, we describe two independent population-based tests that verify the measurement of Yarkovsky orbital drift. First, we provide observational confirmation for the Yarkovsky effect's theoretical size dependence of 1/D, where D is diameter. Second, we find that the observed ratio of negative to positive drift rates in our sample is 2.34, which, accounting for bias and sampling uncertainty, implies an actual ratio of 2.7−0.7+0.32.7^{+0.3}_{-0.7}. This ratio has a vanishingly small probability of occurring due to chance or statistical noise. The observed ratio of retrograde to prograde rotators is two times lower than the ratio expected from numerical predictions from NEA population studies and traditional assumptions about the sense of rotation of NEAs originating from various main belt escape routes. We also examine the efficiency with which solar energy is converted into orbital energy and find a median efficiency in our sample of 12%. We interpret this efficiency in terms of NEA spin and thermal properties.Comment: 27 pages, 9 figures, published in the Astronomical Journal, 159, 92, 202

    Combined small angle X-ray solution scattering with atomic force microscopy for characterizing radiation damage on biological macromolecules

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    Background Synchrotron radiation facilities are pillars of modern structural biology. Small-Angle X-ray scattering performed at synchrotron sources is often used to characterize the shape of biological macromolecules. A major challenge with high-energy X-ray beam on such macromolecules is the perturbation of sample due to radiation damage. Results By employing atomic force microscopy, another common technique to determine the shape of biological macromolecules when deposited on flat substrates, we present a protocol to evaluate and characterize consequences of radiation damage. It requires the acquisition of images of irradiated samples at the single molecule level in a timely manner while using minimal amounts of protein. The protocol has been tested on two different molecular systems: a large globular tetremeric enzyme (ÎČ-Amylase) and a rod-shape plant virus (tobacco mosaic virus). Radiation damage on the globular enzyme leads to an apparent increase in molecular sizes whereas the effect on the long virus is a breakage into smaller pieces resulting in a decrease of the average long-axis radius. Conclusions These results show that radiation damage can appear in different forms and strongly support the need to check the effect of radiation damage at synchrotron sources using the presented protocol

    FASTLens (FAst STatistics for weak Lensing) : Fast method for Weak Lensing Statistics and map making

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    International audienceWith increasingly large data sets, weak lensing measurements are able to measure cosmological parameters with ever-greater precision. However, this increased accuracy also places greater demands on the statistical tools used to extract the available information. To date, the majority of lensing analyses use the two-point statistics of the cosmic shear field. These can be either studied directly using the two-point correlation function or in Fourier space, using the power spectrum. But analysing weak lensing data inevitably involves the masking out of regions, for example to remove bright stars from the field. Masking out the stars is common practice but the gaps in the data need proper handling. In this paper, we show how an inpainting technique allows us to properly fill in these gaps with only NlogN operations, leading to a new image from which we can compute straightforwardly and with a very good accuracy both the power spectrum and the bispectrum. We then propose a new method to compute the bispectrum with a polar FIT algorithm, which has the main advantage of avoiding any interpolation in the Fourier domain. Finally, we propose a new method for dark matter mass map reconstruction from shear observations, which integrates this new inpainting concept. A range of examples based on 3D N-body simulations illustrates the results

    Réalisation de structures optiques verticales en verres de chalcogénure pour des applications dans le proche et moyen infrarouge

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    National audienceDes structures verticales que sont des miroirs de Bragg et des microcavités ont été élaborées en verres de chalcogénure. Une étude préliminaire a permis d'étudier l'indice de réfraction des différentes couches de verres massifs de chalcogénure ainsi que la vitesse de formation de ces couches déposées par PLD. L'objectif de ce travail est de réaliser des microcavités actives en dopant la couche séparatrice par des ions Erbium émettant à 1,53 et à 4,65 ”m
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