The NRL Program in X-ray Navigation [IMA]

http://arxiv.org/abs/1712.03832


This chapter describes the development of X-ray Navigation at the Naval Research Laboratory (NRL) within its astrophysics research programs. The prospects for applications emerged from early discoveries of X-ray source classes and their properties. Starting around 1988 some NRL X-ray astronomy programs included navigation as one of the motivations. The USA experiment (1999) was the first flight payload with an explicit X-ray navigation theme. Subsequently, NRL has continued to work in this area through participation in DARPA and NASA programs. Throughout, the general concept of X-ray navigation (XRNAV) has been broad enough to encompass many different uses of X-ray source observations for attitude determination, position determination, and timekeeping. Pulsar-based X-ray navigation (XNAV) is a special case.

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K. Wood and P. Ray
Tue, 12 Dec 17
21/78

Comments: 30 pages, 15 figures, to appear in Proceedings of the 593. WE-Heraeus Seminar on Autonomous Spacecraft Navigation, ed. W. Becker

Improved performance of semiconductor laser tracking frequency gauge [IMA]

http://arxiv.org/abs/1712.03526


We describe new results from the semiconductor-laser tracking frequency gauge, an instrument that can perform sub-picometer distance measurements and has applications in gravity research and in space-based astronomical instruments proposed for the study of light from extrasolar planets. Compared with previous results, we have improved incremental distance accuracy by a factor of two and absolute distance accuracy by a factor of 20. After an interruption of operation of a tracking frequency gauge used to control a distance, it is now possible, using a nonresonant measurement interferometer, to restore the distance to picometer accuracy by combining absolute and incremental distance measurements.

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D. Kaplan, T. Roberts, J. Phillips, et. al.
Tue, 12 Dec 17
32/78

Comments: 7 pages, 4 figures. Submitted to JINST

How proper are Bayesian models in the astronomical literature? [IMA]

http://arxiv.org/abs/1712.03549


The well-known Bayes theorem assumes that a posterior distribution is a probability distribution. However, the posterior distribution may no longer be a probability distribution if an improper prior distribution (non-probability measure) such as an unbounded uniform prior is used. Improper priors are often used in the astronomical literature to reflect on a lack of prior knowledge, but checking whether the resulting posterior is a probability distribution is sometimes neglected. It turns out that 24 articles out of 75 articles (32\%) published online in two renowned astronomy journals (ApJ and MNRAS) between Jan 1, 2017 and Oct 15, 2017 make use of Bayesian analyses without rigorously establishing posterior propriety. A disturbing aspect is that a Gibbs-type Markov chain Monte Carlo (MCMC) method can produce a seemingly reasonable posterior sample even when the posterior is not a probability distribution (Hobert and Casella, 1996). In such cases, researchers may erroneously make probabilistic inferences without noticing that the MCMC sample is from a non-existent probability distribution. We review why checking posterior propriety is fundamental in Bayesian analyses when improper priors are used and discuss how we can set up scientifically motivated proper priors to avoid the pitfalls of using improper priors.

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H. Tak, S. Ghosh and J. Ellis
Tue, 12 Dec 17
45/78

Comments: N/A

Measurement of the real dielectric permittivity epsilon_r of glacial ice [IMA]

http://arxiv.org/abs/1712.03301


Using data collected by the Askaryan Radio Array (ARA) experiment at the South Pole, we have used long-baseline propagation of radio-frequency signals to extract information on the radio-frequency index-of-refraction in South Polar ice, comparing the arrival times of directly propagating rays with refracted rays. We also observe indications, for the first time, of radio-frequency ice birefringence for signals propagating along predominantly horizontal trajectories, corresponding to an asymmetry of order 0.1% between the ordinary and extra-ordinary birefringent axes, numerically compatible with previous measurements of birefringent asymmetries for vertically-propagating radio-frequency signals at South Pole.

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U. Abdul, P. Allison, S. Archambault, et. al.
Tue, 12 Dec 17
63/78

Comments: N/A

Supervised detection of exoplanets in high-contrast imaging sequences [IMA]

http://arxiv.org/abs/1712.02841


Post-processing algorithms play a key role in pushing the detection limits of high-contrast imaging (HCI) instruments. State-of-the-art image processing approaches for HCI enable the production of science-ready images relying on unsupervised learning techniques, such as low-rank approximations, for generating a model PSF and subtracting the residual starlight and speckle noise. In order to maximize the detection rate of HCI instruments and survey campaigns, advanced algorithms with higher sensitivities to faint companions are needed, especially for the speckle-dominated innermost region of the images. We propose a reformulation of the exoplanet detection task (for ADI sequences) that builds on well-established machine learning techniques to take HCI post-processing from an unsupervised to a supervised learning context. In this new framework, we present algorithmic solutions using two different discriminative models: SODIRF (random forests) and SODINN (neural networks). We test these algorithms on real ADI datasets from VLT/NACO and VLT/SPHERE HCI instruments. We then assess their performances by injecting fake companions and using receiver operating characteristic analysis. This is done in comparison with state-of-the-art ADI algorithms, such as ADI-PCA. This study shows the improved sensitivity vs specificity trade-off of the proposed approach. At the diffraction limit, SODINN improves the true positive rate by a factor ranging from ~2 to ~10 (depending on the dataset and angular separation) with respect to ADI-PCA when working at the same false positive level. The proposed supervised detection framework outperforms state-of-the-art techniques in the task of discriminating planet signal from speckles. In addition, it offers the possibility of re-processing existing HCI databases to maximize their scientific return and potentially improve the demographics of directly imaged exoplanets.

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C. Gonzalez, O. Absil and M. Droogenbroeck
Mon, 11 Dec 17
2/62

Comments: Submitted to A&A, 1st revision

The Astrophysics Source Code Library: What's new, what's coming [IMA]

http://arxiv.org/abs/1712.02973


The Astrophysics Source Code Library (ASCL, ascl.net), established in 1999, is a citable online registry of source codes used in research that are available for download; the ASCL’s main purpose is to improve the transparency, reproducibility, and falsifiability of research. In 2017, improvements to the resource included real-time data backup for submissions and newly-published entries, improved cross-matching of research papers with software entries in ADS, and expansion of preferred citation information for the software in the ASCL.

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A. Allen, G. Berriman, K. DuPrie, et. al.
Mon, 11 Dec 17
4/62

Comments: 4 pages; to be published in proceedings of the October 22-26 2017 ADASS XXVII meeting in Santiago, Chile

An algorithm to resolve γ-rays from charged cosmic rays with DAMPE [CL]

http://arxiv.org/abs/1712.02939


The DArk Matter Particle Explorer (DAMPE), also known as Wukong in China, launched on December 17, 2015, is a new high energy cosmic ray and {\gamma}-ray satellite-borne observatory in space. One of the main scientific goals of DAMPE is to observe GeV-TeV high energy {\gamma}-rays with accurate energy, angular, and time resolution, to indirectly search for dark matter particles and for the study of high energy astrophysics. Due to the comparatively higher fluxes of charged cosmic rays with respect to {\gamma}-rays, it is challenging to identify {\gamma}-rays with sufficiently high efficiency minimizing the amount of charged cosmic ray contamination. In this work we present a method to identify {\gamma}-rays in DAMPE data based on Monte Carlo simulations, using the powerful electromagnetic/hadronic shower discrimination provided by the calorimeter and the veto detection of charged particles provided by the plastic scintillation detector. Monte Carlo simulations show that after this selection the number of electrons and protons that contaminate the selected {\gamma}-ray events at $\sim10$ GeV amounts to less than 1% of the selected sample. Finally, we use flight data to verify the effectiveness of the method by highlighting known {\gamma}-ray sources in the sky and by reconstructing preliminary light curves of the Geminga pulsar.

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Z. Xu, K. Duan, Z. Shen, et. al.
Mon, 11 Dec 17
51/62

Comments: 15 pages,16 figures