A Fresh Approach to Forecasting in Astroparticle Physics and Dark Matter Searches [IMA]


We present a toolbox of new techniques and concepts for the efficient forecasting of experimental sensitivities. These are applicable to a large range of scenarios in (astro-)particle physics, and based on the Fisher information formalism. Fisher information provides an answer to the question what is the maximum extractable information from a given observation?. It is a common tool for the forecasting of experimental sensitivities in many branches of science, but rarely used in astroparticle physics or searches for particle dark matter. After briefly reviewing the Fisher information matrix of general Poisson likelihoods, we propose very compact expressions for estimating expected exclusion and discovery limits (equivalent counts method). We demonstrate by comparison with Monte Carlo results that they remain surprisingly accurate even deep in the Poisson regime. We show how correlated background systematics can be efficiently accounted for by a treatment based on Gaussian random fields. Finally, we introduce the novel concept of Fisher information flux. It can be thought of as a generalization of the commonly used signal-to-noise ratio, while accounting for the non-local properties and saturation effects of background and instrumental uncertainties. It is a powerful and flexible tool ready to be used as core concept for informed strategy development in astroparticle physics and searches for particle dark matter.

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T. Edwards and C. Weniger
Thu, 20 Apr 17

Comments: 19 pages, 12 figures

Dynamic nested sampling: an improved algorithm for parameter estimation and evidence calculation [CL]


We introduce dynamic nested sampling: a generalisation of the nested sampling algorithm in which the number of “live points” varies to allocate samples more efficiently. In empirical tests the new method increases accuracy by up to a factor of ~8 for parameter estimation and ~3 for evidence calculation compared to standard nested sampling with the same number of samples – equivalent to speeding up the computation by factors of ~64 and ~9 respectively. In addition unlike in standard nested sampling more accurate results can be obtained by continuing the calculation for longer. Dynamic nested sampling can be easily included in existing nested sampling software such as MultiNest and PolyChord.

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E. Higson, W. Handley, M. Hobson, et. al.
Thu, 13 Apr 17

Comments: 16 pages + appendix, 8 figures, submitted to Bayesian Analysis. arXiv admin note: text overlap with arXiv:1703.09701

Periodic behaviour of coronal mass ejections, eruptive events, and solar activity proxies during solar cycles 23 and 24 [SSA]


We report on the parallel analysis of the periodic behaviour of coronal mass ejections (CMEs) based on 21 years [1996-2016] of observations with the SOHO/LASCO-C2 coronagraph, solar flares, prominences, and several proxies of solar activity. We consider values of the rates globally and whenever possible, distinguish solar hemispheres and solar cycles 23 and 24. Periodicities are investigated using both frequency (periodogram) and time-frequency (wavelet) analysis. We find that these different processes, in addition to following the ~11-year Solar Cycle, exhibit diverse statistically significant oscillations with properties common to all solar, coronal, and heliospheric processes: variable periodicity, intermittency, asymmetric development in the northern and southern solar hemispheres, and largest amplitudes during the maximum phase of solar cycles, being more pronounced during solar cycle 23 than the weaker cycle 24. However, our analysis reveals an extremely complex and diverse situation. For instance, there exists very limited commonality for periods of less than one year. The few exceptions are the periods of 3.1-3.2 months found in the global occurrence rates of CMEs and in the sunspot area (SSA) and those of 5.9-6.1 months found in the northern hemisphere. Mid-range periods of ~1 and ~2 years are more wide spread among the studied processes, but exhibit a very distinct behaviour with the first one being present only in the northern hemisphere and the second one only in the southern hemisphere. These periodic behaviours likely results from the complexity of the underlying physical processes, prominently the emergence of magnetic flux.

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T. Barlyaeva, J. Wojak, P. Lamy, et. al.
Tue, 11 Apr 17

Comments: 32 pages, 15 figures, 2 tables

Fast and scalable Gaussian process modeling with applications to astronomical time series [IMA]


The growing field of large-scale time domain astronomy requires methods for probabilistic data analysis that are computationally tractable, even with large datasets. Gaussian Processes are a popular class of models used for this purpose but, since the computational cost scales as the cube of the number of data points, their application has been limited to relatively small datasets. In this paper, we present a method for Gaussian Process modeling in one-dimension where the computational requirements scale linearly with the size of the dataset. We demonstrate the method by applying it to simulated and real astronomical time series datasets. These demonstrations are examples of probabilistic inference of stellar rotation periods, asteroseismic oscillation spectra, and transiting planet parameters. The method exploits structure in the problem when the covariance function is expressed as a mixture of complex exponentials, without requiring evenly spaced observations or uniform noise. This form of covariance arises naturally when the process is a mixture of stochastically-driven damped harmonic oscillators – providing a physical motivation for and interpretation of this choice – but we also demonstrate that it is effective in many other cases. We present a mathematical description of the method, the details of the implementation, and a comparison to existing scalable Gaussian Process methods. The method is flexible, fast, and most importantly, interpretable, with a wide range of potential applications within astronomical data analysis and beyond. We provide well-tested and documented open-source implementations of this method in C++, Python, and Julia.

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D. Foreman-Mackey, E. Agol, R. Angus, et. al.
Thu, 30 Mar 17

Comments: Submitted to the AAS Journals. Comments welcome. Code available: this https URL

Flare forecasting at the Met Office Space Weather Operations Centre [SSA]


The Met Office Space Weather Operations Centre produces 24/7/365 space weather guidance, alerts, and forecasts to a wide range of government and commercial end users across the United Kingdom. Solar flare forecasts are one of its products, which are issued multiple times a day in two forms; forecasts for each active region on the solar disk over the next 24 hours, and full-disk forecasts for the next four days. Here the forecasting process is described in detail, as well as first verification of archived forecasts using methods commonly used in operational weather prediction. Real-time verification available for operational flare forecasting use is also described. The influence of human forecasters is highlighted, with human-edited forecasts outperforming original model results, and forecasting skill decreasing over longer forecast lead times.

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S. Murray, S. Bingham, M. Sharpe, et. al.
Tue, 21 Mar 2017

Comments: Accepted for publication in Space Weather. 18 pages, 8 figures, 3 tables

Parametric analysis of Cherenkov light LDF from EAS in the range 30-3000 TeV for primary gamma rays and nuclei [IMA]


A simple ‘knee-like’ approximation of the Lateral Distribution Function (LDF) of Cherenkov light emitted by EAS (extensive air showers) in the atmosphere is proposed for solving various tasks of data analysis in HiSCORE and other wide angle ground-based experiments designed to detect gamma rays and cosmic rays with the energy above tens of TeV. Simulation-based parametric analysis of individual LDF curves revealed that on the radial distance 20-500 m the 5-parameter ‘knee-like’ approximation fits individual LDFs as well as the mean LDF with a very good accuracy. In this paper we demonstrate the efficiency and flexibility of the ‘knee-like’ LDF approximation for various primary particles and shower parameters and the advantages of its application to suppressing proton background and selecting primary gamma rays.

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A. Elshoukrofy, E. Postnikov, E. Korosteleva, et. al.
Tue, 28 Feb 17

Comments: 7 pages, 1 table, 2 figures; Bulletin of the Russian Academy of Sciences: Physics, 81, 4 (2017), in press

Parametric Analysis of Cherenkov Light LDF from EAS for High Energy Gamma Rays and Nuclei: Ways of Practical Application [IMA]


In this paper we propose a ‘knee-like’ approximation of the lateral distribution of the Cherenkov light from extensive air showers in the energy range 30-3000 TeV and study a possibility of its practical application in high energy ground-based gamma-ray astronomy experiments (in particular, in TAIGA-HiSCORE). The approximation has a very good accuracy for individual showers and can be easily simplified for practical application in the HiSCORE wide angle timing array in the condition of a limited number of triggered stations.

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A. Elshoukrofy, E. Postnikov, E. Korosteleva, et. al.
Tue, 28 Feb 17

Comments: 4 pages, 5 figures, proceedings of ISVHECRI 2016 (19th International Symposium on Very High Energy Cosmic Ray Interactions)