265 research outputs found

    Fast ray-tracing algorithm for circumstellar structures (FRACS) I. Algorithm description and parameter-space study for mid-IR interferometry of B[e] stars

    Get PDF
    The physical interpretation of spectro-interferometric data is strongly model-dependent. On one hand, models involving elaborate radiative transfer solvers are too time consuming in general to perform an automatic fitting procedure and derive astrophysical quantities and their related errors. On the other hand, using simple geometrical models does not give sufficient insights into the physics of the object. We propose to stand in between these two extreme approaches by using a physical but still simple parameterised model for the object under consideration. Based on this philosophy, we developed a numerical tool optimised for mid-infrared (mid-IR) interferometry, the fast ray-tracing algorithm for circumstellar structures (FRACS) which can be used as a stand-alone model, or as an aid for a more advanced physical description or even for elaborating observation strategies. FRACS is based on the ray-tracing technique without scattering, but supplemented with the use of quadtree meshes and the full symmetries of the axisymmetrical problem to significantly decrease the necessary computing time to obtain e.g. monochromatic images and visibilities. We applied FRACS in a theoretical study of the dusty circumstellar environments (CSEs) of B[e] supergiants (sgB[e]) in order to determine which information (physical parameters) can be retrieved from present mid-IR interferometry (flux and visibility). From a set of selected dusty CSE models typical of sgB[e] stars we show that together with the geometrical parameters (position angle, inclination, inner radius), the temperature structure (inner dust temperature and gradient) can be well constrained by the mid-IR data alone. Our results also indicate that the determination of the parameters characterising the CSE density structure is more challenging but, in some cases, upper limits as well as correlations on the parameters characterising the mass loss can be obtained. Good constraints for the sgB[e] central continuum emission (central star and inner gas emissions) can be obtained whenever its contribution to the total mid-IR flux is only as high as a few percents. Ray-tracing parameterised models such as FRACS are thus well adapted to prepare and/or interpret long wavelengths (from mid-IR to radio) observations at present (e.g. VLTI/MIDI) and near-future (e.g. VLTI/MATISSE, ALMA) interferometers

    Panchromatic observations and modeling of the HV Tau C edge-on disk

    Get PDF
    We present new high spatial resolution (<~ 0.1") 1-5 micron adaptive optics images, interferometric 1.3 mm continuum and 12CO 2-1 maps, and 350 micron, 2.8 and 3.3 mm fluxes measurements of the HV Tau system. Our adaptive optics images reveal an unusually slow orbital motion within the tight HV Tau AB pair that suggests a highly eccentric orbit and/or a large deprojected physical separation. Scattered light images of the HV Tau C edge-on protoplanetary disk suggest that the anisotropy of the dust scattering phase function is almost independent of wavelength from 0.8 to 5 micron, whereas the dust opacity decreases significantly over the same range. The images further reveal a marked lateral asymmetry in the disk that does not vary over a timescale of 2 years. We further detect a radial velocity gradient in the disk in our 12CO map that lies along the same position angle as the elongation of the continuum emission, which is consistent with Keplerian rotation around an 0.5-1 Msun central star, suggesting that it could be the most massive component in the triple system. We use a powerful radiative transfer model to compute synthetic disk observations and use a Bayesian inference method to extract constraints on the disk properties. Each individual image, as well as the spectral energy distribution, of HV Tau C can be well reproduced by our models with fully mixed dust provided grain growth has already produced larger-than-interstellar dust grains. However, no single model can satisfactorily simultaneously account for all observations. We suggest that future attempts to model this source include more complex dust properties and possibly vertical stratification. (Abridged)Comment: 26 pages, 11 figures, editorially accepted for publication in Ap

    Radio-Astronomical Imaging on Accelerators

    Get PDF
    Imaging is considered the most compute-intensive and therefore most challenging part of a radio-astronomical data-processing pipeline. To reach the high dynamic ranges imposed by the high sensitivity and large field of view of the new generation of radio telescopes such as the Square Kilometre Array (SKA), we need to be able to correct for direction-independent effects (DIEs) such as the curvature of the earth as well as for direction-dependent time-varying effects (DDEs) such as those caused by the ionosphere during imaging. The novel Image-Domain gridding (IDG) algorithm was designed to avoid the performance bottlenecks of traditional imaging algorithms. We implement, optimize, and analyze the performance and energy efficiency of IDG on a variety of hardware platforms to find which platform is the best for IDG. We analyze traditional CPUs, as well as several accelerators architectures. IDG alleviates the limitations of traditional imaging algorithms while it enables the advantages of GPU acceleration: better performance at lower power consumption. The hardware-software co-design has resulted in a highly efficient imager. This makes IDG on GPUs an ideal candidate for meeting the computational and energy efficiency constraints of the SKA. IDG has been integrated with a widely-used astronomical imager (WSClean) and is now being used in production by a variety of different radio observatories such as LOFAR and the MWA. It is not only faster and more energy-efficient than its competitors, but it also produces better quality images

    ATPMN: accurate positions and flux densities at 5 and 8 GHz for 8,385 sources from the PMN survey

    Full text link
    We present a source catalogue of 9,040 radio sources resulting from high-resolution observations of 8,385 PMN sources with the Australia Telescope Compact Array. The catalogue lists flux density and structural measurements at 4.8 and 8.6 GHz, derived from observations of all PMN sources in the declination range -87 deg < delta < -38.5 deg (exclusive of galactic latitudes |b| 70 mJy (50 mJy south of delta = -73 deg). We assess the quality of the data, which was gathered in 1992-1994, describe the population of catalogued sources, and compare it to samples from complementary catalogues. In particular we find 127 radio sources with probable association with gamma-ray sources observed by the orbiting Fermi Large Area Telescope.Comment: 20 pages, 21 figure

    The circumstellar matter distribution of massive young stellar objects

    Get PDF
    A multiwavelength study of the circumstellar matter distribution of massive young stellar objects (MYSOs) was conducted. First, the potential of the new Herschel 70 micron data to resolve MYSOs in the Hi-GAL survey was analysed. These data have the highest resolution achieved at far infrared wavelengths where the spectral energy distribution of MYSOs peaks. These data showed that relatively isolated sources with high L^0.5/d, where L is the luminosity and d the distance of the source, are resolved at 70 micron. The analysis of these data and 1-D spherically symmetric radiative transfer modelling of three sources in the l=30 deg and 59 deg fields showed that they have a shallower density power law index than expected for infalling material. This suggests that the far-IR emission may be dominated by warm dust from the outflow cavity walls rather than rotational flattening as suggested by earlier studies. In order to explain the 70 micron observations, the circumstellar matter of the proto-typical MYSO AFGL 2591 was studied by utilising and modelling full resolution Herschel data from the HOBYS survey and other multi-wavelength dust continuum observations including high-resolution near-IR and mm interferometric data. A 2-D axi-symmetric radiative transfer model was used to find the density and temperature distributions that better reproduce the observations. The model that best fits the continuum observations has a rotationally flattened envelope, paraboloidal outflow cavities and a flared disc with a mass of 1 solar mass. As a result it was found that the extended emission observed at 70 micron can be explained in part by dust emission from the envelope outflow cavity walls. The modelling was able to reproduce most of the other multi-wavelength observations. Finally, the velocity structure of gas in the envelope of AFGL 2591 was studied by modelling methyl cyanide observations in the CH3CN J=12-11 transition at 1.3 mm. The transition K-ladder was fitted assuming a constant density and isothermal distribution of gas, and an excitation temperature ranging between 100-300 K was found. In addition, the first moment (velocity) maps are consistent with rotation of the inner envelope, and its linear velocity gradient is slower than the one observed at smaller scales. The radiative transfer modelling of the methyl cyanide data with a velocity structure of a rotating and infalling envelope suggests that rotation is faster than predicted by the model. This may be solved by magnetic fields transporting angular momentum from the accretion disc

    An RFI simulation pipeline to help teach interferometry and machine learning

    Get PDF
    Thesis (MEng)--Stellenbosch University, 2022.ENGLISH ABSTRACT: An interferometer is a collection of radio antennas that together form one instrument. Machine Learning is the collective term that is used to refer to a set of algorithms that can automatically learn to perform a specific task if it is provided with training examples. Interferometry has become an intricate part of the scientific landscape in South Africa with the advent of MeerKAT. Similarly, utilizing Machine Learning (ML to improve our lives has grown in popularity worldwide. Machine Learning is nowadays used to determine the likes of people, to interpret human utterings, to automatically classify images and the like. As these two fields grow in popularity and importance within the South African context, so does the development of tools that can aid in teaching these fields to undergraduate students. A major problem for radio observatories worldwide is Radio Frequency Interference (RFI. RFI can be detected using ML. A simulator that can simulate interferometric observations that are corrupted by RFI can serve as a testbed for different ML approaches. Moreover, if the simulator is simplistic enough it can even be utilized as a teaching tool. In this thesis such a simulator is developed. This simulator can aid in teaching students how visibilities can be simulated and how RFI can be detected via ML. In effect, one tool that can help teach two relevant undergraduate topics, namely interferometry and ML. In particular, an experiment is proposed which an undergraduate student can repeat to gain a deeper understanding of interferometry and ML. In this experiment, visibilities are simulated, RFI is injected and detected using four different ML techniques, namely Naive Bayes, Logistic Regression, k-means and Gaussian Mixture Models (GMM). The results are then analysed and conclusions are drawn. For the simplistic setup considered here, the ranking of the four algorithms is from best to worst: Naive Bayes, Logistic Regression, GMM and then k-means. In the future, if the simulator is extended somewhat, it can also be used as a testbed for comparing numerous other ML algorithms. The thesis also provides a comprehensive review of all the theory that a student requires to master both interferometry and ML.AFRIKAANSE OPSOMMING: 'n Interferometer is 'n versameling van radio antennas wat saam een instrument vorm. Masjienleer is die kollektiewe term wat grebruik word om te verwys na 'n stel algoritmes wat automaties kan leer hoe om 'n spesifieke funksies te verrig, gegee afrigtingsvoorbeelde. Interferometrie, het 'n belangrike deel van die wetenskaplike landskap in Suid-Afrika geword met die loots van MeerKAT. Soortgelyk, masjienleer se gebruik het wˆereldwyd drasties gegroei. Masjienleer word deesdae gebruik om die voorkeure van mense te bepaal, om die woorde wat mense uiter te herken, om prentjies te klassifiseer en dies meer. Soos wat die twee velde se gewildheid groei, word dit al hoe meer belangrik om toepassings te ontwikkel wat gebruik kan word om te help om die twee velde aan voorgraadse studente te verduidelik. 'n Groot probleem wat radio-sterrewagte in die gesig staar is Radio Frekwensie Inmenging (RFI. RFI kan met behulp van masjienleer geïdentifiseer word. 'n Simulator wat sigbaarheidsmetings kan genereer wat besmet is met RFI kan gebruik word om verkillende masjienleer tegnieke met mekaar te vergelyk. Verder, as 'n simulator eenvoudig genoeg is, kan dit ook gebruik word as 'n onderrigstoepassing. In hierdie tesis word so 'n simulator ontwikkel. Die simulator kan gebruik word om beide, interferometrie en masjienleer, aan studente te verduidelik. Meer spesifiek, 'n eksperiment word voorgestel wat studente sal kan herhaal. In die eksperiment word sigbaarhaeidsmetings gegenereer wat vermeng word met RFI. Vier masjienleer algoritmes word dan gebruik om die RFI te identi seer. Die vier algoritmes is: Naïewe Bayes, Lo gistiese Regressie, Gausiese Mengsel Modelle (GMM) en k-gemdideldes. Die akkuraatheidsrangorde van die vier algoritmes, soos in die studie bevind, is dieselfde as wat hier gegee is. As die simulator uitgebrei word kan dit ook gebruik word om verkeie ander masjienleeralgoritmes met mekaar te vergelyk. Die tesis bevat ook 'n oorsig van al die teorie wat 'n student sou kon help om beide velde te bemeester.Master

    Forecasting Excessive Rainfall and Low-Cloud Bases East of the Northern Andes and Mesoscale Convective Complex Movement in Central South America

    Get PDF
    This research produces better forecast tools for SOUTHCOM\u27s 25th Operational Weather Squadron (OWS) over multiple areas of operation in South America. Heavy rainfall and low-cloud base events along the northeastern Andes foothills are examined, as well as, mesoscale convective complexes (MCCs) in Central South America (CSA). Low clouds, fog, and flooding rains hamper daily Department of Defense (DoD) counter-drug operations in Northwestern South America (NWSA). In addition, fierce MCCs interfere with joint-military exercises in CSA

    Calibrating Low Frequency Aperture Arrays With High Sidelobes: Imaging at 300 MHz With the Murchison Wide-field Array

    Get PDF
    This thesis developed a calibration and imaging strategy for 300MHz MWA observations. Due to highly sensitive grating sidelobes MWA observations in this high frequency regime until now have been largely unprocessed. This thesis uses a model of the sky at 300MHz with a model the MWA beam at 300MHz to calibrate MWA observations. Deep images of calibrated observations were created by subtracting out the grating sidelobes. These are the first deep MWA images at 300MHz
    corecore