Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy

Astrophysics and cosmology are rich with data. The advent of wide-area digital cameras on large aperture telescopes has led to ever more ambitious surveys of the sky. Data volumes of entire surveys a decade ago can now be acquired in a single night and real-time analysis is often desired. Thus, modern astronomy requires big data know-how, in particular it demands highly efficient machine learning and image analysis algorithms. But scalability is not the only challenge: Astronomy applications touch several current machine learning research questions, such as learning from biased data and dealing with label and measurement noise. We argue that this makes astronomy a great domain for computer science research, as it pushes the boundaries of data analysis. In the following, we will present this exciting application area for data scientists. We will focus on exemplary results, discuss main challenges, and highlight some recent methodological advancements in machine learning and image analysis triggered by astronomical applications

Threading of Unconcatenated Ring Polymers at High Concentrations: Double-Folded vs Time-Equilibrated Structures

Unconcatenated ring polymers in concentrated solutions and melt are remarkably well described as double-folded conformations on randomly branched primitive trees. This picture though contrasts recent evidence for extensive intermingling between close-by rings in the form of long-lived topological constraints or threadings. Here, we employ the concept of ring minimal surface to quantify the extent of threadings in polymer solutions of the double-folded rings vs rings in equilibrated molecular dynamics computer simulations. Our results show that the double-folded ring polymers are significantly less threaded compared to their counterparts at equilibrium. Second, threadings form through a slow process whose characteristic time-scale is of the same order of magnitude as that of the diffusion of the rings in solution. These findings are robust, being based on universal (model-independent) observables as the average fraction of threaded length or the total penetrations between close-by rings and the corresponding distribution functions

HISTORICAL GAME STUDIES: AN OUTLINE OF THE RESEARCH FIELD

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Free-energy landscape of polymer-crystal polymorphism

Polymorphism rationalizes how processing can control the final structure of a material. The rugged free-energy landscape and exceedingly slow kinetics in the solid state have so far hampered computational investigations. We report for the first time the free-energy landscape of a polymorphic crystalline polymer, syndiotactic polystyrene. Coarse-grained metadynamics simulations allow us to efficiently sample the landscape at large. The free-energy difference between the two main polymorphs, $\alpha$ and $\beta$, is further investigated by quantum-chemical calculations. The two methods are in line with experimental observations: they predict $\beta$ as the more stable polymorph at standard conditions. Critically, the free-energy landscape suggests how the $\alpha$ polymorph may lead to experimentally observed kinetic traps. The combination of multiscale modeling, enhanced sampling, and quantum-chemical calculations offers an appealing strategy to uncover complex free-energy landscapes with polymorphic behavior.Comment: 10 pages, 4 figure

Smart Products for Smart Production – A Use Case Overview

Industry 4.0 is driven by Cyber-Physical Systems and Smart Products. Smart Products provide a value to both its users and its manufacturers in terms of a closer connection to the customer and his data as well as the provided smart services. However, many companies, especially SMEs, struggle with the transformation of their existing product portfolio into smart products. In order to facilitate this process, this paper presents a set of smart product use-cases from a manufacturer’s perspective. These use-cases can guide the definition of a smart product and be used during its architecture development and realization. Initially the paper gives an introduction in the field of smart products. After that the research results, based on case-study research, are presented. This includes the methodological approach, the case-study data collection and analysis. Finally, a set of use-cases, their definitions and components are presented and highlighted from the perspective of a smart product manufacturer