67 research outputs found
Application of Complex Event Processing Software to Error Detection and Recovery for Arrays of Cherenkov Telescopes
No full textCorrecting for atmospheric variations in IACT data analyses
No full textA fundamental concept of atmospheric Cherenkov detectors is the use of the Earth’s atmosphereas calorimeter. Apart from the advantages of employing this large existing air volume as partof a detector, this implies an accurate characterisation of the atmospheric conditions to correctlyinterpret the collected data. As extensive Monte Carlo simulations form the basis for common dataanalyses of such instruments, it can be unpractical and computationally expensive to adequatelycover the full phase space of possible conditions under which measurements are performed. Often,this is resolved by excluding data that was taken under non-favourable conditions from an analysis.To avoid discarding valuable data, a scheme to correct for deviations between simulated andactual atmospheric conditions is presented in this contribution. The proposed scheme employsatmospheric data from various sources to build refined atmospheric models. The transmissionprofile used in MC simulations is then compared to a range of transmission profiles for conditionsunder which observations were conducted. By applying parametrised air-shower profiles, event-wise zenith and energy dependent correction factors can be determined to refine particle energiesand instrument response functions without the need to rerun the full MC simulation chain. Aproof of concept is shown on the example of observations of the Crab Nebula with the imagingatmospheric Cherenkov telescopes (IACTs) of the H.E.S.S. experiment with a focus on varyingaerosol levels. The scheme can, however, be adapted to correct for the influence of variousatmospheric parameters
Exploring the γ-ray sky around the stellar cluster Westerlund 2 with the H.E.S.S. Experiment
No full textIn dieser Arbeit wird eine Analyse der TeV gamma-Strahlung in der Region um den galaktischen Sternhaufen Westerlund 2 präsentiert. Der dazu analysierte Datensatz beruht auf Observationen mit den Cherenkov Teleskopen des High Energy Stereoscopic System (H.E.S.S.) Experiments und umfasst ~80h Beobachtungszeit. Für die Datenanalyse wird die open-source Software gammapy benutzt, um morphologische und spektrale Modelle der gamma-Emission zu erstellen. Zur Modellauswahl wird das Akaike-Informationskriterium angewandt. Die Ergebisse der Analysen werden weiter mit Daten aus anderen Wellenlängenbereichen kombiniert, um Schlüsse auf den möglichen Ursprung der TeV-Signale zu ziehen. Neben Hinweisen auf eine diffuse gamma-Emission und mehrerer Hotspots um Westerlund 2 ist die Detektion von drei ausgedehnten gamma-Strahlungsquellen das Hauptergebnis der dargelegten Analysen. Zusätzlich zu den bekannten Quellen HESS J1023-575 und HESS J1026-582 wird die Detektion einer neuen, elliptischen Quelle südöstlich von HESS J1023-575 präsentiert. Diese neue Quelle, als ''TeV jet cloud'' bezeichnet, zeigt räumliche Übereinstimmung mit länglichen Gaswolken, die in CO und HI Radio Daten gefunden wurden. Der Ursprung dieser Gaswolken könnte der Jet eines Mikroquasars oder einer anisotropischen Supernova sein. Eine weitere räumliche Übereinstimmung zeigt HESS J1023-575 mit einer sphärischen Gaswolke, die ihren Ursprung in einer Supernova haben könnte. HESS J1023-575 und die Gaswolken sind dabei symmetrisch zur Hauptachse der neuen elliptischen gamma-Quelle ausgerichtet, was eine Verbindung der Komponenten in einem hadronischen Emissionszenario nahelegt. Aus den Wolkenmassen und der gamma-Emission ergibt sich eine Verstärkung der kosmischen Strahlung in der Region, was auf aktive Teilchenbeschleunigung hindeutet. Sollte ein Mikroquasar in der Region gefunden werden, könnte dieses die erste Detektion eines galaktischen hochenergetischen Jets mit Cherenkov Teleskopen sein.This work presents a study of the TeV gamma-ray emission in the region of the stellar cluster Westerlund 2. The main dataset analysed in this work was obtained with the imaging atmospheric Cherenkov telescopes of the High Energy Stereoscopic System (H.E.S.S.), comprising a total of ~80h of observation time. The high-level analysis of the dataset is performed with the open-source software gammapy to produce extensive spectral and spatial models for the observed emission. The best-fitting models are determined by using the Akaike information criterion. The results are combined with findings from other wavelengths to probe different emission scenarios. Besides hints of a diffuse emission and the detection of multiple hotspots, the presented studies yield three extended gamma-ray sources around Westerlund 2. Besides the known sources HESS J1026-582 and HESS J1023-575, an elongated elliptical gamma-ray source referred to as ''TeV jet cloud'' is newly found to the south east of HESS J1023-575. It shows a spatial coincidence with elongated cloud structures seen in CO and HI radio data which may originate from a high energy jet of a mircroquasar or an anisotropic supernova. Another spatial agreement is seen between HESS J1023-575 and a spherical shell of hydrogen gas which may be the remains of an old supernova remnant. HESS J1023-575 and the gas cloud structures symmetrically align along the major axis of the TeV jet cloud. This suggests a connection of these components in a hadronic emission scenario. Combining the masses of the clouds with the measured gamma-ray flux yields a high cosmic ray enhancement factor, suggesting active particle acceleration in the region. If a microquasar would be found around the best-fit position of HESS J1023-575, this could be the first detection of a galactic high energy jet at TeV energies with Cherenkov telescopes
Investigating the effect of aerosol variations in high-level analyses of Cherenkov telescope data
No full textAs aerosols influence the optical transmission properties of the atmosphere, variations in atmospheric aerosols yield variations in the signals from extensive air-showers (EAS) as measured with imaging atmospheric Cherenkov telescopes (IACTs). With the optical transmission of the atmosphere affecting the amount of Cherenkov light reaching IACTs, wrongly accounted aerosol levels yield a misinterpretation of the brightness of the detected signals. And as the number of Cherenkov photons produced in an EAS is related to its primary particle's energy, such unaccounted aerosol variations cause errors in the reconstructed particle energies. As this reconstructed energy is commonly used to bin the data for further spectral, morphological or temporal modelling, any error on the reconstructed air-shower energy propagates to all higher levels of an analysis. In this contribution, the effect of unaccounted aerosol variations on high-level results obtained from IACT data is investigated by simulating observations with the CTAO South in gammapy and adapting the reconstructed EAS energies as expected for variations in atmospheric aerosol content observed around the observatory site. This data is then used to reconstruct the properties of the simulated gamma-ray sources and the results are compared to results obtained from simulated observations which are not affected by deviations in aerosol conditions
HexagDLy—Processing hexagonally sampled data with CNNs in PyTorch
No full textHexagDLy is a Python-library extending the PyTorch deep learning framework with convolution and pooling operations on hexagonal grids. It aims to ease the access to convolutional neural networks for applications that rely on hexagonally sampled data as, for example, commonly found in ground-based astroparticle physics experiments. Keywords: Convolutional neural networks, Hexagonal grid, PyTorch, Astroparticle physic
HexagDLy - Hexagonal Convolutions with PyTorch
No full text<p>HexagDLy provides convolution and pooling methods for hexagonally sampled input data on the basis of the deep learning framework PyTorch.</p>
North Consortium: Scientific Explanations for Aggression and Gender Essentialism
No full textPeople’s perceptions of the relative importance of biological and social factors in understanding and determining behaviour can influence their endorsement of gender stereotypes. For example, media reports of scientific studies showing brain differences between women and men can lead to greater endorsement of gender stereotypes (Brescoll & LaFrance, 2004). This project builds on previous research in this area (e.g. Klysing, 2020) by investigating how information about biological and social explanations of gender differences in aggression can affect stereotype endorsement. It also examines a number of relevant moderators: Locus of Control, Biological Essentialism, and Belief in a Just World
This project is a joint “consortium” project, where students from Leeds Beckett University (supervised by Dr Trish Holch and Dr Sofia Persson), Manchester Metropolitan University (supervised by Dr. Thomas Hostler), and the University of Sheffield (supervised by Dr. Tim Riley) collaborate on the design of the study and data collection. This project utilises Open Science best practices (e.g., pre-registration and data sharing).
Part of this pre-registration are dedicated to the full project (i.,e. the full combined datasets from each of the institutions) with the full set of moderators, and parts are dedicated to the individual student's projects, with one of the moderators each
HexagDLy-Processing hexagonally sampled data with CNNs in PyTorch
No full textHexagDLy is a Python-library extending the PyTorch deep learning framework with convolution and pooling operations on hexagonal grids. It aims to ease the access to convolutional neural networks for applications that rely on hexagonally sampled data as, for example, commonly found in ground-based astroparticle physics experiments
An updated view of the VHE gamma-ray sky around thestellar cluster Westerlund 2 with the H.E.S.S. experiment
No full textSince the last H.E.S.S. publication on the stellar cluster Westerlund 2 in 2011, the H.E.S.S. dataseton this region has increased more than three-fold in exposure to ∼ 220 h of total observation time.By applying a novel approach to correct for atmospheric variations in IACT data, the commonlyapplied data quality selection criteria can be adapted to exploit as much of this dataset as possible.In combination with current analysis techniques, it is furthermore possible to disentangle andbetter characterise this complex region of the gamma-ray sky. Applying an extensive 3D fittingprocedure, we find three distinct VHE gamma-ray sources in the vicinity of Westerlund 2, adding anew emission region to the previously reported sources HESS J1023−575 and HESS J1026−582.Even though the sources partly overlap, their spectral indices differ from one another, providingnew clues on the relativistic particle acceleration and propagation in the region around the massivestar cluster. The new source component shows an elongated morphology that seems to emergefrom the star cluster, following the multi-parsec-scale CO jet cloud initially found in NANTENdata as reported in 2009
Katie's pre-reg: The Effect of Theoretical Explanations of Intimate Partner Violence and Domestic Violence Myth Acceptance on Perceptions of Perpetrators and Survivors
No full textPeople’s perceptions of the relative importance of biological and social factors in understanding and determining behaviour can influence their endorsement of gender stereotypes. For example, media reports of scientific studies showing brain differences between women and men can lead to greater endorsement of gender stereotypes (Brescoll & LaFrance, 2004). This project builds on previous research in this area (e.g., Klysing, 2020) by investigating how information about biological and social explanations of gender differences in aggression affects attributions of interpersonal violence. It also examines a number of relevant moderators: Domestic Violence Myth Acceptance and Gender Essentialism. This registration concerns DVMA.
This project is a joint “consortium” project, where students from Leeds Beckett University (supervised by Dr Trish Holch and Dr Sofia Persson), Manchester Metropolitan University (supervised by Dr. Thomas Hostler), and the University of Sheffield (supervised by Dr. Tim Riley) collaborate on the design of the study and data collection. This project utilises Open Science best practices (e.g., pre-registration and data sharing).
The project is specifically exploring how biological and socio-cultural explanations of intimate partner violence against women affects perpetrator and victim culpability, perceptions of violence severity and sentencing recommendations of male perpetrators. A control condition has been included as a baseline measure to establish whether the UK population generally endorse a biological or socio-cultural positioning. The moderator for this particular study is domestic violence myth acceptance. Therefore, the moderation aspect of this study will be exploring whether domestic violence myth acceptance interacts with theoretical IPV explanations to affect perpetrator and victim culpability
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