On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions

The Metropolis algorithm is arguably the most fundamental Markov chain Monte Carlo (MCMC) method. But the algorithm is not guaranteed to converge to the desired distribution in the case of multivariate binary distributions (e.g., Ising models or stochastic neural networks such as Boltzmann machines) if the variables (sites or neurons) are updated in a fixed order, a setting commonly used in practice. The reason is that the corresponding Markov chain may not be irreducible. We propose a modified Metropolis transition operator that behaves almost always identically to the standard Metropolis operator and prove that it ensures irreducibility and convergence to the limiting distribution in the multivariate binary case with fixed-order updates. The result provides an explanation for the behaviour of Metropolis MCMC in that setting and closes a long-standing theoretical gap. We experimentally studied the standard and modified Metropolis operator for models were they actually behave differently. If the standard algorithm also converges, the modified operator exhibits similar (if not better) performance in terms of convergence speed

First Study of Combined Blazar Light Curves with FACT and HAWC

For studying variable sources like blazars, it is crucial to achieve unbiased monitoring, either with dedicated telescopes in pointing mode or survey instruments. At TeV energies, the High Altitude Water Cherenkov (HAWC) observatory monitors approximately two thirds of the sky every day. It uses the water Cherenkov technique, which provides an excellent duty cycle independent of weather and season. The First G-APD Cherenkov Telescope (FACT) monitors a small sample of sources with better sensitivity, using the imaging air Cherenkov technique. Thanks to its camera with silicon-based photosensors, FACT features an excellent detector performance and stability and extends its observations to times with strong moonlight, increasing the duty cycle compared to other imaging air Cherenkov telescopes. As FACT and HAWC have overlapping energy ranges, a joint study can exploit the longer daily coverage given that the observatories' locations are offset by 5.3 hours. Furthermore, the better sensitivity of FACT adds a finer resolution of features on hour-long time scales, while the continuous duty cycle of HAWC ensures evenly sampled long-term coverage. Thus, the two instruments complement each other to provide a more complete picture of blazar variability. In this presentation, the first joint study of light curves from the two instruments will be shown, correlating long-term measurements with daily sampling between air and water Cherenkov telescopes. The presented results focus on the study of the variability of the bright blazars Mrk 421 and Mrk 501 during the last two years featuring various flaring activities.Comment: 6 pages, 2 figures. Contribution to the 6th International Symposium on High Energy Gamma-Ray Astronomy (Gamma2016), Heidelberg, Germany. To be published in the AIP Conference Proceeding

Contribución al conocimiento de Porosagrotis gypaetina (Guen.) (Lep.:Noctuidae)

p.15-22Este trabajo tiene por finalidad brindar una descripcion detallada de los diferentes estados de desarrollo, asi como de los estadios larvales, de Porosagrotis gypaetina (Guen.) y estimar sus principales parametros biologicos. Se trata de una oruga conocida vulgarmente como gusano pardo que frecuenta cultivos de alfalfa, trebol bianco, maiz y girasol y determinadas malezas. Los caracteres considerados para su identificacion fueron, en el huevo: numero y distribucion de costas; en la larva: pigmentacion, distribucion de manchas y cerdas corporales; en la pupa: tamaño, forma y color y caracteristicas del cremaster; y en el adulto: ubicacion y coloracion de maculas y nervaduras alares. La emergencia de imagos alcanzo su maximo en abril y mayo. El periodo embrionario se completo en 22 a 26 dias. Aproximadamente la mitad de las larvas cumplieron su ciclo en 6 estadios y las restantes en 7; la duracion total del periodo larval fue de 134 a 141 dias, sin considerar la forma prepupal e independientemente del numero de estadios. Las orugas permanecieron como prepupas durante la temporada estival (aproximadamente 161 dias). El estado pupal duro 40 a 57 dias. Las observaciones realizadas permiten expresar que, inediante los caracteres descriptos, es factible reconocer la especie a traves no solo de los adultos, sino de sus estados inmaduros. Posee una sola generacion anual; transcurre el inviemo como larva; el daño tipico de corte lo produce a partir del cuarto estadio larval

The Coastal Observing System for Northern and Arctic Seas (COSYNA)

The Coastal Observing System for Northern and Arctic Seas (COSYNA) was established in order to better understand the complex interdisciplinary processes of northern seas and the Arctic coasts in a changing environment. Particular focus is given to the German Bight in the North Sea as a prime example of a heavily used coastal area, and Svalbard as an example of an Arctic coast that is under strong pressure due to global change. The COSYNA automated observing and modelling system is designed to monitor real-time conditions and provide short-term forecasts, data, and data products to help assess the impact of anthropogenically induced change. Observations are carried out by combining satellite and radar remote sensing with various in situ platforms. Novel sensors, instruments, and algorithms are developed to further improve the understanding of the interdisciplinary interactions between physics, biogeochemistry, and the ecology of coastal seas. New modelling and data assimilation techniques are used to integrate observations and models in a quasi-operational system providing descriptions and forecasts of key hydrographic variables. Data and data products are publicly available free of charge and in real time. They are used by multiple interest groups in science, agencies, politics, industry, and the public

Gammapy: A Python package for gamma-ray astronomy

In this article, we present Gammapy, an open-source Python package for the analysis of astronomical $\gamma$-ray data, and illustrate the functionalities of its first long-term-support release, version 1.0. Built on the modern Python scientific ecosystem, Gammapy provides a uniform platform for reducing and modeling data from different $\gamma$-ray instruments for many analysis scenarios. Gammapy complies with several well-established data conventions in high-energy astrophysics, providing serialized data products that are interoperable with other software packages. Starting from event lists and instrument response functions, Gammapy provides functionalities to reduce these data by binning them in energy and sky coordinates. Several techniques for background estimation are implemented in the package to handle the residual hadronic background affecting $\gamma$-ray instruments. After the data are binned, the flux and morphology of one or more $\gamma$-ray sources can be estimated using Poisson maximum likelihood fitting and assuming a variety of spectral, temporal, and spatial models. Estimation of flux points, likelihood profiles, and light curves is also supported. After describing the structure of the package, we show, using publicly available $\gamma$-ray data, the capabilities of Gammapy in multiple traditional and novel $\gamma$-ray analysis scenarios, such as spectral and spectro-morphological modeling and estimations of a spectral energy distribution and a light curve. Its flexibility and power are displayed in a final multi-instrument example, where datasets from different instruments, at different stages of data reduction, are simultaneously fitted with an astrophysical flux model.Comment: 26 pages, 16 figure

Long-term monitoring of bright blazars in the multi-GeV to TeV range with FACT

Blazars like Markarian 421 or Markarian 501 are active galactic nuclei (AGN), with their jets orientated towards the observer. They are among the brightest objects in the very high energy (VHE) gamma ray regime (>100 GeV). Their emitted gamma-ray fluxes are extremely variable, with changing activity levels on timescales between minutes, months, and even years. Several questions are part of the current research, such as the question of the emission regions or the engine of the AGN and the particle acceleration. A dedicated longterm monitoring program is necessary to investigate the properties of blazars in detail. A densely sampled and unbiased light curve allows for observation of both high and low states of the sources, and the combination with multi-wavelength observation could contribute to the answer of several questions mentioned above. FACT (First G-APD Cherenkov Telescope) is the first operational telescope using silicon photomultiplier (SiPM, also known as Geigermode—Avalanche Photo Diode, G-APD) as photon detectors. SiPM have a very homogenous and stable longterm performance, and allow operation even during full moon without any filter, leading to a maximal duty cycle for an Imaging Air Cherenkov Telescope (IACT). Hence, FACT is an ideal device for such a longterm monitoring of bright blazars. A small set of sources (e.g., Markarian 421, Markarian 501, 1ES 1959+650, and 1ES 2344+51.4) is currently being monitored. In this contribution, the FACT telescope and the concept of longterm monitoring of bright blazars will be introduced. The results of the monitoring program will be shown, and the advantages of densely sampled and unbiased light curves will be discussed

Unmasking the gamma-ray sky: comprehensive and reproducible analysis for Cherenkov telescopes

Imaging atmospheric Cherenkov telescopes (IACT) observe the sky in the highest energy ranges. From the remnants of cataclysmic supernovae to jets powered by supermassive blackholes in the center of distant galaxies, IACTs can capture the light emerging from the most extreme sources in the universe. With the recent advent of multi-messenger astronomy it has become critical for IACTs to publicly share their data and software. For the first time since the inception of IACT technology, in a combined effort of the H.E.S.S., MAGIC, VERITAS, and FACT collaborations, observations of the Crab Nebula were made available to the general public in a common data format. The first part of my thesis demonstrates the viability of the common data format by performing a spectral analysis of the Crab Nebula on the published datasets. The text gives detailed descriptions and mathematical formalizations of instrument response functions (IRFs) and the statistical modeling used for typical spectral analyses. This is essential to understand the measurement process of IACTs. The ultimate goal of this part of the thesis will be to use Hamilton Markov Monte Carlo methods to test spectral models and unfold flux-point estimates for the Crab Nebula. The common data format paves the road for the operation of the upcoming Cherenkov Telescope Array (CTA). Once CTA has been constructed, it will be the largest and most sophisticated experiment in the field of ground-based gamma-ray astronomy. It will be operated as an open observatory allowing anyone to access the recorded data. The second part of my thesis concentrates on reproducible analysis for the Cherenkov Telescope Array (CTA). Once operational, CTA will produce a substantial amount of data creating new challenges for data storage and analysis technologies. In this part of the thesis I use simulated CTA data to build a comprehensive analysis chain based on fully open-source methods. The goal is to create a pipeline that rivals the physics performance of CTA’s closed-source reference implementation. Every step of the analysis, from raw-data processing to the calculation of sensitivity curves, will be optimized with respect to complexity, reproducibility and run-time

RISE Germany Internship: Unfolding FACT Data

In this report the results from a 10 week internship are presented. The goal of the internship was to apply different unfolding approaches to conduct measurements of energy spectra from data aquired by FACT, the First G-APD Cherenkov Telescope. FACT is the first operational telescope of its kind, employing a camera equipped with silicon photo multipliers (G-APD aka SiPM) to primarily detect gamma rays. Improving the unfolding method can help with better interpretation of the data and more accurate physics results without the need for new equipment or more observations. The approaches tested during this internship range from simplistic matrix inversion to an improvement over of the previous standard (TRUEE)