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July - December 2014

Fast Direct Methods for Gaussian Processes and the Analysis of NASA Kepler Mission Data

Sivaram Ambikasaran, Daniel Foreman-Mackey, Leslie Greengard, David W. Hogg, Michael O'Neil

A number of problems in probability and statistics can be addressed using the multivariate normal (or multivariate Gaussian) distribution. In the one-dimensional case, computing the probability for a given mean and variance simply requires the evalu ...
The Lutz-Kelker paradox

Francis, Charles

The Lutz-Kelker correction is intended to give an unbiased estimate for stellar parallaxes and magnitudes, but it is shown explicitly that it does not. This paradox results from the application of an argument about sample statistics to the treatment ...
Frequentism and Bayesianism: A Python-driven Primer

Jake VanderPlas

This paper presents a brief, semi-technical comparison of the essential features of the frequentist and Bayesian approaches to statistical inference, with several illustrative examples implemented in Python. The differences between frequentism and B ...
Introduction to astroML: Machine Learning for Astrophysics

Jacob T. VanderPlas, Andrew J. Connolly, Zeljko Ivezic, Alex Gray

Astronomy and astrophysics are witnessing dramatic increases in data volume as detectors, telescopes and computers become ever more powerful. During the last decade, sky surveys across the electromagnetic spectrum have collected hundreds of terabyte ...
RobPer: An R Package to Calculate Periodograms for Light Curves Based On Robust Regression

Anita Monika Thieler, Roland Fried, Jonathan Rathjens

An important task in astroparticle physics is the detection of periodicities in irregularly sampled time series, called light curves. The classic Fourier periodogram cannot deal with irregular sampling and with the measurement accuracies that are ty ...
Unveiling the cosmological information beyond linear scales: forecasts for sufficient statistics

M. Wolk, J. Carron and I. Szapudi

Beyond the linear regime, Fourier modes of cosmological random fields become correlated, and the power spectrum of density fluctuations contains only a fraction of the available cosmological information. To unveil this formerly hidden information, t ...
Chandrasekhar's relation and the stellar rotation in the Kepler field

J. R. P. Silva, B. B. Soares, and D. B. de Freitas

According to the statistical law of large numbers, the expected mean of identically distributed random variables of a sample tends toward the actual mean as the sample increases. Under this law, it is possible to test the Chandrasekhar's relation (C ...
Combining Human and Machine Learning for Morphological Analysis of Galaxy Images

Evan Kuminski,Joe George,John Wallin, Lior Shamir

The increasing importance of digital sky surveys collecting many millions of galaxy images has reinforced the need for robust methods that can perform morphological analysis of large galaxy image databases. Citizen science initiatives such as Galaxy ...
Computing in Astronomy: To See the Unseen

Pankratius, V. ; Mattmann, C.

Advances in computing have empowered astronomers to explore the universe in greater detail. Software-defined instruments relying on digital data capture and processing are more powerful than ever and continue to bring us new knowledge about the univ ...
Signal Processing: On the Edge of Astronomy's New Frontier

Edwards, J.

Digital signal processing (DSP) plays several important roles in modern radio astronomy, such as processing data to create highresolution radio images, isolating weak emissions from celestial sources, and reducing distortions in incoming signals. DS ...
Uniformity of Kilo-Pixel Arrays of Transition-Edge Sensors for X-ray Astronomy

Smith, S.J.; Adams, J.S.; Bandler, S.R.; Betancourt-Martinez, G.; Chervenak, J.A.; Eckart, M.E.; Finkbeiner, F.M.; Kelley, R.L.; Kilbourne, C.A.; Sang-Jun Lee; Porter, F.S.; Sadleir, J.E.; Wassell, E.J.

We are developing kilo-pixel arrays of transition-edge sensor (TES) microcalorimeters for use in future laboratory and space based X-ray astrophysics experiments. These arrays are required to achieve an energy resolution of ΔEFWHM <; 3 eV full-widt ...
SUPERVISED DETECTION OF ANOMALOUS LIGHT CURVES IN MASSIVE ASTRONOMICAL CATALOGS

Isadora Nun, Karim Pichara, Pavlos Protopapas, and Dae-Won Kim

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. In order to process this information and to extract all possible knowledge, machine learning technique ...
Computing in Astronomy: Applications and Examples

Bogert, F. A.; Smith, N.; Holdener, J.; De Jong, E. M.; Hart, A. F.; Cinquini, L.; Khudikyan, S. E.; Thompson, D. R.; Mattmann, C. A.; Wagstaff, K.; Lazio, J.; Jones, D. L.; Allen, A.; Shamir, L.; Teuben, P.

Computing in astronomy has a wide variety of applications. We grouped a series of sidebars to provide pointers to ongoing work as well to give illustrative examples on astronomical visualization, event classification, Big Data, and software librarie ...