University of Stuttgart

About: University of Stuttgart is a education organization based out in Stuttgart, Germany. It is known for research contribution in the topics: Laser & Finite element method. The organization has 27715 authors who have published 56370 publications receiving 1363382 citations. The organization is also known as: Universität Stuttgart.

Box Splines

Abstract: This chapter provides a brief introduction to box and half-box splines with particular focus on triangular splines and surface design. A particular example of box splines are the B-splines with equidistant knots. In general, box splines consist of regularly arranged polynomial pieces and they have a useful geometric interpretation. Namely they can be viewed as density functions of the shadows of higher dimensional boxes and half-boxes. Of particular interest for Geometric Design are box spline surfaces that consist of triangular polynomial pieces. These box spline surfaces have planar domains, but it is quite simple to construct arbitrary two-dimensional surfaces, i.e., manifolds, with these box splines.

Room-temperature entanglement between single defect spins in diamond

Abstract: Entanglement is the central yet fleeting phenomenon of quantum physics. Once being considered a peculiar counter-intuitive property of quantum theory1, it has developed into the most central element of quantum technology. Consequently, there have been a number of experimental demonstrations of entanglement between photons2, atoms3, ions4 and solid-state systems such as spins or quantum dots5, 6, 7, superconducting circuits8, 9 and macroscopic diamond10. Here we experimentally demonstrate entanglement between two engineered single solid-state spin quantum bits (qubits) at ambient conditions. Photon emission of defect pairs reveals ground-state spin correlation. Entanglement (fidelity = 0.67±0.04) is proved by quantum state tomography. Moreover, the lifetime of electron spin entanglement is extended to milliseconds by entanglement swapping to nuclear spins. The experiments mark an important step towards a scalable room-temperature quantum device being of potential use in quantum information processing as well as metrology.

A micro-macro approach to rubber-like materials—Part I: the non-affine micro-sphere model of rubber elasticity

Abstract: The contribution presents a new micro-mechanically based network model for the description of the elastic response of rubbery polymers at large strains and considers details of its numerical implementation. The approach models a rubber-like material based on a micro-structure that can be symbolized by a micro-sphere where the surface represents a continuous distribution of chain orientations in space. Core of the model is a new two-dimensional constitutive setting of the micro-mechanical response of a single polymer chain in a constrained environment defined by two micro-kinematic variables: the stretch of the chain and the contraction of the cross section of a micro-tube that contains the chain. The second key feature is a new non-affine micro-to-macro transition that defines the three-dimensional overall response of the polymer network based on a characteristic homogenization procedure of micro-variables defined on the micro-sphere of space orientations. It determines a stretch fluctuation field on the micro-sphere by a principle of minimum averaged free energy and links the two micro-kinematic variables in a non-affine format to the line-stretch and the area-stretch of the macro-continuum. Hence, the new model describes two superimposed contributions resulting from free chain motions and their topological constraints in an attractive dual geometric structure on both the micro- and the macro-level. Averaging operations on the micro-sphere are directly evaluated by an efficient numerical integration scheme. The overall model contains five effective material parameters obtained from the single chain statistics and properties of the network with clearly identifiable relationships to characteristic phenomena observed in stress–strain experiments. The approach advances features of the affine full network and the eight chain models by a substantial improvement of their modeling capacity. The excellent predictive performance is illustrated by comparative studies with previously developed network models and by fitting of various available experimental data of homogeneous and non-homogeneous tests.