Technische Universität Darmstadt

About: Technische Universität Darmstadt is a education organization based out in Darmstadt, Germany. It is known for research contribution in the topics: Neutron & Finite element method. The organization has 17316 authors who have published 40619 publications receiving 937916 citations. The organization is also known as: Darmstadt University of Technology & University of Darmstadt.

Discrepancy between experimental and theoretical β-decay rates resolved from first principles

Abstract: The dominant decay mode of atomic nuclei is beta decay (β-decay), a process that changes a neutron into a proton (and vice versa). This decay offers a window to physics beyond the standard model, and is at the heart of microphysical processes in stellar explosions and element synthesis in the Universe1–3. However, observed β-decay rates in nuclei have been found to be systematically smaller than for free neutrons: this 50-year-old puzzle about the apparent quenching of the fundamental coupling constant by a factor of about 0.75 (ref. 4) is without a first-principles theoretical explanation. Here, we demonstrate that this quenching arises to a large extent from the coupling of the weak force to two nucleons as well as from strong correlations in the nucleus. We present state-of-the-art computations of β-decays from light- and medium-mass nuclei to 100Sn by combining effective field theories of the strong and weak forces5 with powerful quantum many-body techniques6–8. Our results are consistent with experimental data and have implications for heavy element synthesis in neutron star mergers9–11 and predictions for the neutrino-less double-β-decay3, where an analogous quenching puzzle is a source of uncertainty in extracting the neutrino mass scale12. The difference between the β-decay rate predicted for free neutrons and that measured in real nuclei is explained by first-principles calculations to arise from strong correlations and the weak-force coupling between nucleons.

Temperature-Transferable Coarse-Grained potentials for ethylbenzene, polystyrene, and their mixtures

Abstract: In this article, we present coarse-grained potentials of ethylbenzene developed at 298 K and of amorphous polystyrene developed at 500 K by the pressure-corrected iterative Boltzmann inversion method. The potentials are optimized against the fully atomistic simulations until the radial distribution functions generated from coarse-grained simulations are consistent with atomistic simulations. In the coarse-grained polystyrene melts of different chain lengths, the Flory exponent of 0.58 is obtained for chain statistics. Both potentials of polystyrene and ethylbenzene are transferable over a broad range of temperature. The thermal expansion coefficients of the fully atomistic simulations are well reproduced in the coarse-grained models for both systems. However, for the case of ethylbenzene, the coarse-grained potential is temperature-dependent. The potential needs to be modified by a temperature factor of T/T0 when it is transferred to other temperatures; T0 = 298 K is the temperature at which the coarse-gr...

Hybrid web service composition: business processes meet business rules

Abstract: Over the last few years several process-based web service composition languages have erged, such as BPEL4WS and BPML. These languages define the composition on the basis of a process that specifies the control and data flow among the services to be composed. In this approach, the whole business logic underlying the composition including business policies and constraints is coded as a monolithic block. As a result, business rules are hard to change without affecting the core composition logic. In this paper, we propose a hybrid composition approach: The composition logic is broken down into a core part (the process) and several well-modularized business rules that exist and evolve independently. We also discuss two alternative technologies for implenting business rules in encapsulated units, using aspects and a rule-based engine. Our approach allows for a more modular and flexible web service composition.

Automated API Property Inference Techniques

Abstract: Frameworks and libraries offer reusable and customizable functionality through Application Programming Interfaces (APIs). Correctly using large and sophisticated APIs can represent a challenge due to hidden assumptions and requirements. Numerous approaches have been developed to infer properties of APIs, intended to guide their use by developers. With each approach come new definitions of API properties, new techniques for inferring these properties, and new ways to assess their correctness and usefulness. This paper provides a comprehensive survey of over a decade of research on automated property inference for APIs. Our survey provides a synthesis of this complex technical field along different dimensions of analysis: properties inferred, mining techniques, and empirical results. In particular, we derive a classification and organization of over 60 techniques into five different categories based on the type of API property inferred: unordered usage patterns, sequential usage patterns, behavioral specifications, migration mappings, and general information.