Electronic transport in graphene nanostructures on SiO2

We report two experiments on graphene nanostructures. The first was performed on a graphene nanoribbon, where the nature of electronic transport was investigated in detail. Electrons or holes are found to localize in pockets of the potential along the ribbon. Transport is governed by the joint action of localization and Coulomb interaction. The temperature-dependence of the conductance shows activated behavior at temperatures above a few Kelvin. The activation energy retraces the edges of Coulomb blockade diamonds found in nonlinear transport. In the second experiment the metallic tip of a low-temperature scanning force microscope was scanned above a graphene quantum dot. In addition to the familiar Coulomb blockade fringes, localized states are detected forming in the constrictions connecting the dot to source and drain.     

Light emission from nanocrystalline silicon clusters embedded in silicon dioxide: Role of the suboxide states

Silicon clusters embedded in a silicon dioxide matrix were prepared by ultrasound-assisted implantation resulting in a modified concentration of suboxide states as revealed by high-resolution photoelectron spectroscopy. It is suggested that ultrasound treatment results in formation of different interface structure between silicon cluster and silicon dioxide matrix which is characterized by a distinctly reduced concentration of the suboxide states. It is observed that photoluminescence properties are strongly correlated with the concentration of the suboxide states thereby providing an evidence that besides a quantum confinement effect a closer look at the chemical composition of the nc-Si/SiO₂ system is important.     

Renormalisation of q-Regularised Multiple Zeta Values

We consider a particular one-parameter family of q-analogues of multiple zeta values. The intrinsic q-regularisation permits an extension of these q-multiple zeta values to negative integers. Renormalised multiple zeta values satisfying the quasi-shuffle product are obtained using an Hopf-algebraic Birkhoff factorisation together with minimal subtraction.     

Investigation of Simulated Trading — A multi agent based trading system for optimization purposes

Some years ago, Bachem, Hochstättler, and Malich proposed a heuristic algorithm called Simulated Trading for the optimization of vehicle routing problems. Computational agents place buy-orders and sell-orders for customers to be handled at a virtual financial market, the prices of the orders depending on the costs of inserting the customer in the tour or for his removal. According to a proposed rule set, the financial market creates a buy-and-sell graph for the various orders in the order book, intending to optimize the overall system. Here I present a thorough investigation for the application of this algorithm to the traveling salesman problem.     

Improved signal-to-noise ratio in spectral-domain compared with time-domain optical coherence tomography

A signal-to-noise ratio (SNR) analysis is presented for optical coherence tomography (OCT) signals in which time-domain performance is compared with that of the spectral domain. A significant SNR gain of several hundredfold is found for acquisition in the spectral domain. The SNR benefit is demonstrated experimentally in a hybrid time-domain-spectral-domain OCT system.     

Colour rearrangement for dipole showers

We present an algorithm to rearrange the colour chains of dipole showers in the shower process according to the colour amplitudes of a simple matrix element. We implement the procedure in the dipole shower of Herwig and show comparisons to data.     

Sauna,sweat and science II – do we sweat what we drink?

ABSTRACT

Inspired by a previous ‘Sauna, sweat and science’ study [Zech et al. Isot Environ Health Stud. 2015;51(3):439–447] and out of curiosity and enthusiasm for stable isotope and sauna research we aimed at answering the question ‘do we sweat (isotopically) what we drink’? We, therefore, pulse-labelled five test persons in a sauna experiment with beverages that were ²H-enriched at about +25,600?‰. Sweat samples were collected during six sauna rounds and the hydrogen isotope composition δ²H_sweat was determined using an isotope ratio mass spectrometer. Before pulse labelling, δ²H_sweat – reflecting by approximation body water – ranged from –32 to –22?‰. This is ～35?‰ enriched compared to usual mid-European drinking water and can be explained with hydrogen-bearing food as well as with the respiratory loss of ²H-depleted vapour. The absence of a clearly detectable ²H pulse in sweat after pulse labelling and δ²H_sweat results of ≤+250?‰ due to a fast ²H equilibration with body water are moreover a clearly negative answer to our research question also in a short-term consideration. Given that the recovery of the tracer based on an isotope mass balance calculation is clearly below 100?%, we finally answer the question ‘where did the rest of the tracer go?’     

Generalized sensitivity analysis of nonlinear programs using a sequence of quadratic programs

ABSTRACT

Local sensitivity information is obtained for KKT points of parametric NLPs that may exhibit active set changes under parametric perturbations; under appropriate regularity conditions, computationally relevant generalized derivatives of primal and dual variable solutions of parametric NLPs are calculated. Ralph and Dempe obtained directional derivatives of solutions of parametric NLPs exhibiting active set changes from the unique solution of an auxiliary quadratic program. This article uses lexicographic directional derivatives, a newly developed tool in nonsmooth analysis, to generalize the classical NLP sensitivity analysis theory of Ralph and Dempe. By viewing said auxiliary quadratic program as a parametric NLP, the results of Ralph and Dempe are applied to furnish a sequence of coupled QPs, whose unique solutions yield generalized derivative information for the NLP. A practically implementable algorithm is provided. The theory developed here is motivated by widespread applications of nonlinear programming sensitivity analysis, such as in dynamic control and optimization problems.