Kiwi Advanced Research and Education Network (KAREN) has been used to transfer large volumes of radio astronomical data between the Radio Astronomical Observatory at Warkworth, New Zealand and various international organizations involved in joint projects and VLBI observations. Here we report on the current status of connectivity and on the results of testing different data transfer protocols. ...

High performance computing has been used in various fields of astrophysical research. But most of it is implemented on massively parallel systems (supercomputers) or graphical processing unit clusters. With the advent of multicore processors in the last decade, many serial software codes have been re-implemented in parallel mode to utilize the full potential of these processors. In this paper, ...

Background. Recent major advances in the understanding of galaxy owe a great deal to highly successful galaxy surveys conducted with the Sloan Telescope. With massive amount of data, modern techniques such as machine learning comes in naturally for efficient handling. While many applications focused on characterizing and classifying astronomical objects within a predefined area of interest, uns...

DevOps is the contemporary term for a software development culture that purposefully blurs distinction between software development and IT operations by treating “infrastructure as code.” DevOps teams typically implement practices summarised by the colloquial directive to “eat your own dogfood;” meaning that software tools developed by a team should be used internally rather thrown over the fen...

In the framework of EuroNEAR network several databases around the world were datamined. The main scientifi c objective was the astrometry of Near-Earth Asteroids (NEAs) for both precovery and secure orbits of these objects. The article presents few aspects of data-mining and the developed procedures for accomplishing these objectives. Introduction EuroNEAR is a network composed by both astronom...

An overview is given of Bayesian inversion and regularization procedures. In particular, the conceptual basis of the maximum entropy method (MEM) is discussed, and extensions to positive/negative and complex data are highlighted. Other deconvolution methods are also discussed within the Bayesian context, focusing mainly on the comparison of Wiener filtering, Massive Inference and the Pixon meth...

Binary stars form a significant part of stellar population. They are registered and observed by a number of methods. This is the reason for variety of present-day resources of astronomical data dealing with binaries and multiples. The review of observational types of binary stars and of basic data resources for them is presented. The properties of stars within these types and possible relations...

Virtual Observatories give us access to huge amounts of image data that are often redundant. Our goal is to take advantage of this redundancy by combining images of the same field of view into a single object. To achieve this goal, we propose to develop a multi-source data fusion method that relies on probability and band-limited signal theory. The target object is an image to be inferred from ...

In this paper we present a method for hyper-spectral image restoration for integral field spectrographs (IFS) data. We specifically address two topics: (i) the design of a fast approximation of spectrally varying operators and (ii) the comparison between two kind of regularization functions: quadratic and spatial sparsity functions. We illustrate this method with simulations coming from the Mul...

The removal of chromaticity in high precision astrometric measurements is a very important challenge because chromaticity can represent a relevant source of systematic error; we perform this task using a feed forward neural network and focus on the usefulness of a proper preprocessing applied to the network parameters. We use a few statistical moments properly selected with a careful preprocess...