Astronomie

Résumé

thumb|350px|Nébuleuse M17 : photographie prise par le télescope Hubble. L'astronomie est la science de l'observation des astres, cherchant à expliquer leur origine, leur évolution, ainsi que leurs propriétés physiques et chimiques. Le terme astronomie vient du grec (de , « astre, étoile », et , « loi ») : la loi des astres. Avec plus de d'histoire, les origines de l'astronomie remontent au-delà de l'Antiquité dans les pratiques religieuses préhistoriques. L'astronomie est l'une des rares sciences où les amateurs jouent encore un rôle actif. Elle est pratiquée à titre de loisir par un large public d'astronomes amateurs. Histoire Histoire de l'astronomie thumb|Sur tous les continents et depuis la haute antiquité, l'observation du ciel a une grande importance (Diego Durán). L'astronomie est considérée comme la plus ancienne des sciences. L'archéologie révèle en effet que certaines civilisations de l'Âge du bronze, et peut-être du Néolithique, avaie

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https://fr.wikipedia.org/wiki/Astronomie

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One method for locating extrasolar planets is to observe the lateral movement of a star in the sky caused by a planet in orbit around it. In order to detect this displacement, the angular position of the star has to be measured with high accuracy. This technique is called astrometry. The Very Large Telescope Interferometer (VLTI) is operated by the European Southern Observatory and located at the Paranal Observatory in Chile. The purpose of the PRIMA instrument (Phase Referenced Imaging and Micro-arcsecond Astrometry) of the VLTI is to perform high-resolution astrometric measurements and high-resolution imaging of faint stars using white light interferometry, by combining the light collected by two telescopes. In order to allow the detection of extrasolar planets, the astrometric measurement has to be performed with micro-arcsecond accuracy. In astrometric mode the PRIMA instrument observes two targets at the same time: the object of scientific interest, and a bright reference star. The angular position of the science object relative to the reference star is obtained by monitoring the differential optical path travelled by the light of each object in two separate white-light interferometers. The aim of this work was to develop a high-resolution laser metrology based on superheterodyne interferometry, with an accuracy of 5 nm over a differential optical path of 100 mm. Moreover the laser source had to be stabilised on an absolute frequency reference, in order to ensure the long-term stability and calibration required to achieve the target performance. Superheterodyne interferometry allowed the direct measurement of the differential optical path using two heterodyne interferometers working with two different frequency shifts. The differential phase measurement between the two interferometers was obtained by electronic mixing of the two heterodyne signals, leading to the differential optical path needed for the astrometric measurement

Institut de Microtechnique, Université de Neuchâtel2006

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Beamforming in radio astronomy focuses at and around a direction using matched beamforming or a derivative, to both maximise the energy coming from this point and reduce the data rate to the central processor. Such beamformers often result in large side-lobes, with influence from undesired directions. Moreover, there is a fundamental lack of flexibility when, for example, targeting extended regions or tracking objects with uncertainty as to their location. We show how the analytic framework Flexibeam can be leveraged to achieve beamshapes that cover general spatial areas with substantially more energy concentration within the region-of-interest. The method is numerically stable, and scalable in the number of antennas, and does not magnify noise.

2016

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Low-dimensional data embedding for scalable astronomical imaging in the SKA telescope era

Vijay Kartik

Astronomy is one of the oldest sciences known to humanity. We have been studying celestial objects for millennia, and continue to peer deeper into space in our thirst for knowledge about our origins and the universe that surrounds us. Radio astronomy -- observing celestial objects at radio frequencies -- has helped push the boundaries on the kind of objects we can study. Indeed, some of the most important discoveries about the structure of our universe, like the cosmic microwave background, and entire classes of objects like quasars and pulsars, were made using radio astronomy. Radio interferometers are telescopes made of multiple antennas spread over a distance. Signals detected at different antennas are combined to provide images with much higher resolution and sensitivity than with a traditional single-dish radio telescope. The Square Kilometre Array (SKA) is one such radio interferometer, with plans to have antennas separated by as much as 3000,km. In its quest for ever-higher resolution and ever-wider coverage of the sky, the SKA heralds a data explosion, with an expected acquisition rate of 5,terabits per second. The high data rate fed into the pipeline can be handled with a two-pronged approach -- (i) scalable, parallel imaging algorithms that fully utilize the latest computing technologies like accelerators and distributed clusters, and (ii) dimensionality reduction methods that embed the high-dimensional telescope data to much smaller sizes without losing information and guaranteeing accurate recovery of the images, thereby enabling imaging methods to scale to big data sizes and alleviating heavy loads on pipeline buffers without compromising on the science goals of the SKA. In this thesis we propose fast and robust dimensionality reduction methods that embed data to very low sizes while preserving information present in the original data. These methods are presented in the context of compressed sensing theory and related signal recovery techniques. The effectiveness of the reduction methods is illustrated by coupling them with advanced convex optimization algorithms to solve a sparse recovery problem. Images thus reconstructed from extremely low-sized embedded data are shown to have quality comparable to those obtained from full data without any reduction. Comparisons with other standard `data compression' techniques in radio interferometry (like averaging) show a clear advantage in using our methods which provide higher quality images from much lower data sizes. We confirm these claims on both synthetic data simulating SKA data patterns as well as actual telescope data from a state-of-the-art radio interferometer. Additionally, imaging with reduced data is shown to have a lighter computational load -- smaller memory footprint owing to the size and faster iterative image recovery owing to the fast embedding. Extensions to the work presented in this thesis are already underway. We propose an `on-line' version of our reduction methods that works on blocks of data and thus can be applied on-the-fly on data as they are being acquired by telescopes in real-time. This is of immediate interest to the SKA where large buffers in the data acquisition pipeline are very expensive and thus undesirable. Some directions to be probed in the immediate future are in transient imaging, and imaging hyperspectral data to test computational load while in a high resolution, multi-frequency setting.

EPFL2018

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Low-dimensional data embedding for scalable astronomical imaging in the SKA telescope era

Vijay Kartik

EPFL2018

Institut de Microtechnique, Université de Neuchâtel2006