Quantum Populations in Zeno Regions inside Black Holes

Schwarzschild black-hole interiors border on space-like singularities representing classical information leaks. We show that local quantum physics is decoupled from these leaks due to dynamically generated boundaries, called Zeno borders. Beyond Zeno borders black-hole interiors become asymptotically silent, and quantum fields evolve freely towards the geodesic singularity with vanishing probability measure for populating the geodesic boundary. Thus Zeno borders represent a probabilistic completion of Schwarzschild black holes within the semiclassical framework.Comment: 5 pages, 2 figures, more pedagogical presentation of our unchanged results including an introduction to Zeno region

Meta Reinforcement Learning with Latent Variable Gaussian Processes

Learning from small data sets is critical in many practical applications where data collection is time consuming or expensive, e.g., robotics, animal experiments or drug design. Meta learning is one way to increase the data efficiency of learning algorithms by generalizing learned concepts from a set of training tasks to unseen, but related, tasks. Often, this relationship between tasks is hard coded or relies in some other way on human expertise. In this paper, we frame meta learning as a hierarchical latent variable model and infer the relationship between tasks automatically from data. We apply our framework in a model-based reinforcement learning setting and show that our meta-learning model effectively generalizes to novel tasks by identifying how new tasks relate to prior ones from minimal data. This results in up to a 60% reduction in the average interaction time needed to solve tasks compared to strong baselines.Comment: 11 pages, 7 figure

Executive AI Literacy: A Text-Mining Approach to Understand Existing and Demanded AI Skills of Leaders in Unicorn Firms

Despite the growing relevance of artificial intelligence (AI) for busi-nesses, there is a lack of research on how top-level executives must be skilled in AI. Drawing on upper echelons theory, this paper explores executive AI literacy, defined as the combined AI skills of top-level executives, and its relevance for different executive roles. We conducted a text-mining analysis of 1,625 execu-tives’ online profiles and 1,033 executive job postings from unicorn firms re-trieved via web-scraping from an online professional social network. We find that AI skills are mostly required in product-related executive roles (vs. adminis-trative roles). Thus, we provide an AI-specific perspective complementing prior information systems research on executives, which asserts that (non-AI) IT is driven by administrative executive roles. Our paper contributes to AI literacy lit-erature by shedding light on the substance of executive AI literacy within firms. Lastly, we provide implications for AI-related information systems strategy

Dynamik granularer Materie auf kleinen Körpern im Sonnensystem

The European Space Agency’s ROSETTA spacecraft, en route towards its target Comet 67P/Churyumov-Gerasimenko, passed by the Asteroid (21) Lutetia on the 10 July 2010 at a distance of 3170km.OSIRIS - the Optical, Spectroscopic, and Infrared Remote Imaging System on board Rosetta - took 462 images. These images show that (21) Lutetia is covered with a thick layer of regolith. On slopes of several craters this regolith layer collapsed in landslide-like events. A possible trigger mechanism for these low-gravity avalanches is the slow impact of a small mm to cm-sized body. An experiment was conducted to investigate if such an impact is a viably mechanism to trigger an avalanche on an asteroid. The data collected during the experimental investigation show that these minor impacts can trigger a landslide-like event if the target material is tilted close to the angle of repose. The grain size distribution also influences the likelihood of an avalanche depending on the type of material under investigation. Using the findings of this experiment a set of Monte-Carlo-Simulations was conducted to find out on which time scales minor impacts can influence the surfaces of asteroids in the main belt. The results show that a steep slope can be completely resurfaced within 100.000 years by minor impacts alone. The microphysical processes governing the energy distribution during a minor impact were also studied using the Discrete Element Method (DEM) software ESyS-Particles. The simulations show that the energy that gets introduced into the target system by the impactor is largely retained close to the surface of the target. The energy gets dissipated in inelastic collisions that happen more frequently in the depth of the material where the mean number of contacts per particle is higher than at the surface. The energy retained at the surface gets distributed radially away from the impact site. This distribution can be governed by gravity (when g is large) or the local arrangement of the particles (when gravity is low). These findings reinforce the conclusion that low-energy impacts are a viable trigger mechanism for avalanches, both in low and normal gravity.Die ROSETTA Sonde der Europäischen Raumfahrtorganisation ESA passierte auf dem Weg zu ihrem Zielobjekt, dem Kometen 67P/Tschurjumow-Gerasimenko, am 10. Juli 2010 den Asteroiden (21) Lutetia in einer Entfernung von 3170 km. Das Kamera-System der Sonde, OSIRIS (Optical, Spectroscopic, and Infrared Remote Imaging System), machte während des Vorbeiflugs 462 Photoaufnahmen. Anhand dieser Aufnahmen fand man heraus, dass (21) Lutetia von einer Schicht aus Regolith bedeckt ist, die teilweise mehrere Hundert Meter dick ist. An einigen Kraterhängen ließen sich lawinenartige Abrutsche erkennen. Ein möglicher Auslösemechanismus für solche Lawinen in niedriger Schwerkraft ist der Einschlag von langsamen Partikeln in einem Größenbereich von mm bis cm. In dieser Arbeit wurde experimentell untersucht, unter welchen Voraussetzungen ein solcher kleinskaliger Einschlag in der Lage ist, eine Lawine auf einem Asteroiden auszulösen. Die Auswertung der gesammelten Daten ergab, dass kleinskalige Einschläge in der Lage sind Lawinen auszulösen, wenn der Neigungswinkel des Hanges nah am Schüttwinkel des untersuchten Materials sein muss. Außerdem spielt die Korngrößenverteilung des Hangmaterials eine wichtige Rolle für die Wahrscheinlichkeit eine Lawine auszulösen. Auf Grundlage der Ergebnisse dieses Experiments wurden Monte-Carlo-Simulationen durchgeführt, um die Zeitskala zu bestimmen, auf der dieser Prozess der kleinskaligen Einschläge die Oberfläche eines Asteroiden beeinflusst. Die Lebensdauer eines steil geneigten Hanges auf einem Asteroiden im Hauptgürtel ergab sich daraus zu etwa Hunderttausend Jahren. Die mikrophysikalischen Prozesse während eines kleinskaligen Einschlags wurden mit Hilfe der so genannten Discrete Element Method untersucht. Dazu wurde die Software ESyS-Particle benutzt. Die Ergebnisse zeigen, dass die durch den Einschlag in das System eingebrachte Energie größtenteils in Partikeln nahe der Oberfläche verbleibt. Die Energie wird durch inelastische Stöße zwischen den Körnern des Target-Materials dissipiert. Die Energie, die in der Oberflächenschicht verbleibt, wird vom Einschlagspunkt ausgehend radialsymmetrisch verteilt. Für einen hohen Wert von g wird dieser Prozess von der Gravitation dominiert, für kleine Werte von g spielt die Geometrie der Teilchen im Target die größere Rolle. Diese Erkenntnisse bestätigen den Schluss, dass kleinskalige Einschläge, sowohl in reduzierter wie auch in normaler Schwerkraft, geeignet sind, Erdrutsche und Lawinen auszulösen

Ability of Black-Box Optimisation to Efficiently Perform Simulation Studies in Power Engineering

In this study, the potential of the so-called black-box optimisation (BBO) to increase the efficiency of simulation studies in power engineering is evaluated. Three algorithms ("Multilevel Coordinate Search"(MCS) and "Stable Noisy Optimization by Branch and Fit"(SNOBFIT) by Huyer and Neumaier and "blackbox: A Procedure for Parallel Optimization of Expensive Black-box Functions"(blackbox) by Knysh and Korkolis) are implemented in MATLAB and compared for solving two use cases: the analysis of the maximum rotational speed of a gas turbine after a load rejection and the identification of transfer function parameters by measurements. The first use case has a high computational cost, whereas the second use case is computationally cheap. For each run of the algorithms, the accuracy of the found solution and the number of simulations or function evaluations needed to determine the optimum and the overall runtime are used to identify the potential of the algorithms in comparison to currently used methods. All methods provide solutions for potential optima that are at least 99.8% accurate compared to the reference methods. The number of evaluations of the objective functions differs significantly but cannot be directly compared as only the SNOBFIT algorithm does stop when the found solution does not improve further, whereas the other algorithms use a predefined number of function evaluations. Therefore, SNOBFIT has the shortest runtime for both examples. For computationally expensive simulations, it is shown that parallelisation of the function evaluations (SNOBFIT and blackbox) and quantisation of the input variables (SNOBFIT) are essential for the algorithmic performance. For the gas turbine overspeed analysis, only SNOBFIT can compete with the reference procedure concerning the runtime. Further studies will have to investigate whether the quantisation of input variables can be applied to other algorithms and whether the BBO algorithms can outperform the reference methods for problems with a higher dimensionality