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The data volumes generated by the WALLABY atomic Hydrogen (HI) survey using the Australiian Square Kilometre Array Pathfinder (ASKAP) necessitate greater automation and reliable automation in the task of source-finding and cataloguing. To…

The spectral line datacubes obtained from the Square Kilometre Array (SKA) and its precursors, such as the Australian SKA Pathfinder (ASKAP), will be sufficiently large to necessitate automated detection and parametrisation of sources.…

天体物理仪器与方法 · 物理学 2015-06-03 Russell Jurek

We consider wavelets as a tool to perform a variety of tasks in the context of analyzing cosmic microwave background (CMB) maps. Using Spherical Haar Wavelets we define a position and angular-scale-dependent measure of power that can be…

天体物理学 · 物理学 2009-10-31 L. Tenorio , A. H. Jaffe , S. Hanany , C. H. Lineweaver

The Australian Square Kilometre Array Pathfinder (ASKAP) presents a number of challenges in the area of source finding and cataloguing. The data rates and image sizes are very large, and require automated processing in a high-performance…

天体物理仪器与方法 · 物理学 2015-06-11 Matthew Whiting , Ben Humphreys

This paper presents and discusses the results of basic source finding tests in three dimensions (using spectroscopic data cubes) with Duchamp, the standard source finder for the Australian SKA Pathfinder. For this purpose, we generated…

天体物理仪器与方法 · 物理学 2015-06-03 Tobias Westmeier , Attila Popping , Paolo Serra

We present a new detection algorithm based on the wavelet transform for the analysis of high energy astronomical images. The wavelet transform, due to its multi-scale structure, is suited for the optimal detection of point-like as well as…

天体物理学 · 物理学 2009-10-31 Davide Lazzati , Sergio Campana , Piero Rosati , Maria Rosa Panzera , Gianpiero Tagliaferri

The 21 cm spectral line emission of atomic neutral hydrogen (HI) is one of the primary wavelengths observed in radio astronomy. However, the signal is intrinsically faint and the HI content of galaxies depends on the cosmic environment,…

天体物理仪器与方法 · 物理学 2023-02-08 J. A. Barkai , M. A. W. Verheijen , E. T. Martínez , M. H. F. Wilkinson

Today, image denoising by thresholding of wavelet coefficients is a commonly used tool for 2D image enhancement. Since the data product of spectroscopic imaging surveys has two spatial and one spectral dimension, the techniques for…

天体物理仪器与方法 · 物理学 2015-06-03 Lars Flöer , Benjamin Winkel

Context. Source extraction for large-scale HI surveys currently involves large amounts of manual labor. For data volumes expected from future HI surveys with upcoming facilities, this approach is not feasible any longer. Aims. We describe…

天体物理仪器与方法 · 物理学 2014-10-01 Lars Flöer , Benjamin Winkel , Jürgen Kerp

Automated source extraction and parameterization represents a crucial challenge for the next-generation radio interferometer surveys, such as those performed with the Square Kilometre Array (SKA) and its precursors. In this paper we present…

天体物理仪器与方法 · 物理学 2016-05-09 S. Riggi , A. Ingallinera , P. Leto , F. Cavallaro , F. Bufano , F. Schillirò , C. Trigilio , G. Umana , C. S. Buemi , R. P. Norris

This paper describes the Duchamp source finder, a piece of software designed to find and describe sources in 3-dimensional, spectral-line data cubes. Duchamp has been developed with HI (neutral hydrogen) observations in mind, but is widely…

天体物理仪器与方法 · 物理学 2012-04-12 Matthew T. Whiting

Soon to be operational HI survey instruments such as APERTIF and ASKAP will produce large datasets. These surveys will provide information about the HI in and around hundreds of galaxies with a typical signal-to-noise ratio of $\sim$ 10 in…

天体物理仪器与方法 · 物理学 2016-09-14 D. Punzo , J. M. van der Hulst , J. B. T. M. Roerdink

Here I will outline successes and challenges for finding spectral line sources in large data cubes that are dominated by noise. This is a 3D challenge as the sources we wish to catalog are spread over several spatial pixels and spectral…

宇宙学与河外天体物理 · 物理学 2015-06-05 Baerbel S. Koribalski

The process of determining the number and characteristics of sources in astronomical images is so fundamental to a large range of astronomical problems that it is perhaps surprising that no standard procedure has ever been defined that has…

天体物理仪器与方法 · 物理学 2015-06-03 Minh Huynh , Andrew Hopkins , Ray Norris , Paul Hancock , Tara Murphy , Russell Jurek , Matthew Whiting

We present a framework for the optimal filtering of spherical signals contaminated by realizations of an additive, zero-mean, uncorrelated and anisotropic noise process on the sphere. Filtering is performed in the wavelet domain given by…

信号处理 · 电气工程与系统科学 2021-02-09 Adeem Aslam , Zubair Khalid , Jason D. McEwen

We discuss the optimal detection of point sources from multiwavelength imaging data using an approach, referred to as MDET, which requires no prior knowledge of the source spectrum. MDET may be regarded as a somewhat more general version of…

天体物理仪器与方法 · 物理学 2015-06-03 Kenneth A. Marsh , Thomas H. Jarrett

A simple approach to microphone- and speaker-arrays is described in which the microphone array is regarded as a sampling grid for the acoustic field, and the corresponding speaker-array is treated as a "spatial digital to analog converter"…

声音 · 计算机科学 2019-11-19 Julius O. Smith

The Australian Square Kilometer Array Pathfinder (ASKAP) will revolutionise our knowledge of gas-rich galaxies in the Universe. Here we present predictions for two proposed extragalactic ASKAP neutral hydrogen (HI) emission-line surveys,…

We describe a novel method for removing noise (in wavelet domain) of unknown variance from microarrays. The method is based on a smoothing of the coefficients of the highest subbands. Specifically, we decompose the noisy microarray into…

信号处理 · 电气工程与系统科学 2018-08-01 Mario Mastriani , Alberto. E. Giraldez

In our work, we examine, for the first time, the possibility of fast and efficient source localization directly from the uvobservations, omitting the recovering of the dirty or clean images. We propose a deep neural network-based framework…

天体物理仪器与方法 · 物理学 2023-06-21 O. Taran , O. Bait , M. Dessauges-Zavadsky , T. Holotyak , D. Schaerer , S. Voloshynovskiy
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