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How to take the interstellar weather with you in pulsar timing analysis
Lindley Lentati, Paul Alexander, Michael P. Hobson
Here we present a Bayesian method of including discrete measurements of dispersion measure due to the interstellar medium in the direction of a pulsar as prior information in the a…
Planck intermediate results. XVII. Emission of dust in the diffuse interstellar medium from the far-infrared to microwave frequencies
Planck Collaboration, A. Abergel, P. A. R. Ade +196
The dust-HI correlation is used to characterize the emission properties of dust in the diffuse interstellar medium. We cross-correlate sky maps from Planck, WMAP, and DIRBE, at 17…
Planck 2013 results. XI. All-sky model of thermal dust emission
Planck Collaboration, A. Abergel, P. A. R. Ade +244
This paper presents an all-sky model of dust emission from the Planck 857, 545 and 353 GHz, and IRAS 100 micron data. Using a modified black-body fit to the data we present all-sky…
TempoNest: A Bayesian approach to pulsar timing analysis
Lindley Lentati, Paul Alexander, Michael P. Hobson +4
A new Bayesian software package for the analysis of pulsar timing data is presented in the form of TempoNest which allows for the robust determination of the non-linear pulsar timi…
Planck 2013 results. XXX. Cosmic infrared background measurements and implications for star formation
Planck Collaboration, P. A. R. Ade, N. Aghanim +238
We present new measurements of CIB anisotropies using Planck. Combining HFI data with IRAS, the angular auto- and cross frequency power spectrum is measured from 143 to 3000 GHz, a…
SKYNET: an efficient and robust neural network training tool for machine learning in astronomy
Philip Graff, Farhan Feroz, Michael P. Hobson +1
We present the first public release of our generic neural network training algorithm, called SkyNet. This efficient and robust machine learning tool is able to train large and deep…