Monitoring and data quality assessment of the ATLAS liquid argon calorimeter

The liquid argon calorimeter is a key component of the ATLAS detector installed at the CERN Large Hadron Collider. The primary purpose of this calorimeter is the measurement of electron and photon kinematic properties. It also provides a crucial input for measuring jets and missing transverse momentum. An advanced data monitoring procedure was designed to quickly identify issues that would affect detector performance and ensure that only the best quality data are used for physics analysis. This article presents the validation procedure developed during the 2011 and 2012 LHC data-taking periods, in which more than 98% of the proton-proton luminosity recorded by ATLAS at a centre-of-mass energy of 7–8 TeV had calorimeter data quality suitable for physics analysis.

Electron reconstruction and identification efficiency measurements with the ATLAS detector using the 2011 LHC proton-proton collision data

Many of the interesting physics processes to be measured at the LHC have a signature involving one or more isolated electrons. The electron reconstruction and identification efficiencies of the ATLAS detector at the LHC have been evaluated using proton–proton collision data collected in 2011 at √s = 7 TeV and corresponding to an integrated luminosity of 4.7 fb−1. Tag-and-probe methods using events with leptonic decays of W and Z bosons and J/ψ mesons are employed to benchmark these performance parameters. The combination of all measurements results in identification efficiencies determined with an accuracy at the few per mil level for electron transverse energy greater than 30 GeV.

Granular computing as a tool of human data interaction - a cognitive cities use case

The article proposes granular computing as a theoretical, formal and methodological basis for the newly emerging research field of human–data interaction (HDI). We argue that the ability to represent and reason with information granules is a prerequisite for data legibility. As such, it allows for extending the research agenda of HDI to encompass the topic of collective intelligence amplification, which is seen as an opportunity of today’s increasingly pervasive computing environments. As an example of collective intelligence amplification in HDI, we introduce a collaborative urban planning use case in a cognitive city environment and show how an iterative process of user input and human-oriented automated data processing can support collective decision making. As a basis for automated human-oriented data processing, we use the spatial granular calculus of granular geometry.

Shape-invariant multibeam backscatter data of the eastern slope of the Porcupine Seabight (50 m grid size)

In this study multibeam angular backscatter data acquired in the eastern slope of the Porcupine Seabight are analysed. Processing of the angular backscatter data using the 'NRGCOR' software was made for 29 locations comprising different geological provinces like: carbonate mounds, buried mounds, seafloor channels, and inter-channel areas. A detailed methodology is developed to produce a map of angle-invariant (normalized) backscatter data by correcting the local angular backscatter values. The present paper involves detailed processing steps and related technical aspects of the normalization approach. The presented angle-invariant backscatter map possesses 12 dB dynamic range in terms of grey scale. A clear distinction is seen between the mound dominated northern area (Belgica province) and the Gollum channel seafloor at the southern end of the site. Qualitative analyses of the calculated mean backscatter values i.e., grey scale levels, utilizing angle-invariant backscatter data generally indicate backscatter values are highest (lighter grey scale) in the mound areas followed by buried mounds. The backscatter values are lowest in the inter-channel areas (lowest grey scale level). Moderate backscatter values (medium grey level) are observed from the Gollum and Kings channel data, and significant variability within the channel seafloor provinces. The segmentation of the channel seafloor provinces are made based on the computed grey scale levels for further analyses based on the angular backscatter strength. Three major parameters are utilized to classify four different seafloor provinces of the Porcupine Seabight by employing a semi-empirical method to analyse multibeam angular backscatter data. The predicted backscatter response which has been computed at 20° is the highest for the mound areas. The coefficient of variation (CV) of the mean backscatter response is also the highest for the mound areas. Interestingly, the slope value of the buried mound areas are found to be the highest. However, the channel seafloor of moderate backscatter response presents the lowest slope and CV values. A critical examination of the inter-channel areas indicates less variability within the estimated three parameters.

Crete fault scarp point cloud data

This paper assesses the along strike variation of active bedrock fault scarps using long range terrestrial laser scanning (t-LiDAR) data in order to determine the distribution behaviour of scarp height and the subsequently calculate long term throw-rates. Five faults on Cretewhich display spectacular limestone fault scarps have been studied using high resolution digital elevation model (HRDEM) data. We scanned several hundred square metres of the fault system including the footwall, fault scarp and hanging wall of the investigated fault segment. The vertical displacement and the dip of the scarp were extracted every metre along the strike of the detected fault segment based on the processed HRDEM. The scarp variability was analysed by using statistical and morphological methods. The analysis was done in a geographical information system (GIS) environment. Results show a normal distribution for the scanned fault scarp's vertical displacement. Based on these facts, the mean value of height was chosen to define the authentic vertical displacement. Consequently the scarp can be divided into above, below and within the range of mean (within one standard deviation) and quantify the modifications of vertical displacement. Therefore, the fault segment can be subdivided into areas which are influenced by external modification like erosion and sedimentation processes. Moreover, to describe and measure the variability of vertical displacement along strike the fault, the semi-variance was calculated with the variogram method. This method is used to determine how much influence the external processes have had on the vertical displacement. By combining of morphological and statistical results, the fault can be subdivided into areas with high external influences and areas with authentic fault scarps, which have little or no external influences. This subdivision is necessary for long term throw-rate calculations, because without this differentiation the calculated rates would be misleading and the activity of a fault would be incorrectly assessed with significant implications for seismic hazard assessment since fault slip rate data govern the earthquake recurrence. Furthermore, by using this workflow areas with minimal external influences can be determined, not only for throw-rate calculations, but also for determining samples sites for absolute dating techniques such as cosmogenic nuclide dating. The main outcomes of this study include: i) there is no direct correlation between the fault's mean vertical displacement and dip (R² less than 0.31); ii) without subdividing the scanned scarp into areas with differing amounts of external influences, the along strike variability of vertical displacement is ±35%; iii) when the scanned scarp is subdivided the variation of the vertical displacement of the authentic scarp (exposed by earthquakes only) is in a range of ±6% (the varies depending on the fault from 7 to 12%); iv) the calculation of the long term throw-rate (since 13 ka) for four scarps in Crete using the authentic vertical displacement is 0.35 ± 0.04 mm/yr at Kastelli 1, 0.31 ± 0.01 mm/yr at Kastelli 2, 0.85 ± 0.06 mm/yr at the Asomatos fault (Sellia) and 0.55 ± 0.05 mm/yr at the Lastros fault.