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Apeldoorn, Netherlands

Roehling J.D.,University of California at Davis | Batenburg K.J.,Centrum Wiskunde and Informatica | Batenburg K.J.,University of Antwerp | Swain F.B.,Luna Innovations, Inc. | And 2 more authors.
Advanced Functional Materials | Year: 2013

The three-dimensional morphology of mixed organic layers are quantitatively measured using high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) with electron tomography for the first time. The mixed organic layers used for organic photovoltaic applications have not been previously imaged using STEM tomography as there is insufficient contrast between donor and acceptor components. Contrast is generated by substituting fullerenes with endohedral fullerenes that contain a Lu3N cluster within the fullerene cage. The high contrast and signal-to-noise ratio, in combination with use of the discrete algebraic reconstruction technique (DART), allows generation of the most detailed and accurate three-dimensional map of BHJ morphology to date. From the STEM-tomography reconstructions it is determined that three distinct material phases are present within the BHJs. By observing changes to morphology and mixing ratio during thermal and solvent annealing, the effects of mutual solubility and fullerene crystallization on morphology and long term stability are determined. This material/technique combination shows itself as a powerful tool for examining morphology in detail and allows for observation of nanoscopic changes in local concentration. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Source


Melo F.D.,Centrum Wiskunde and Informatica | Cwiklinski P.,RWTH Aachen | Terhal B.M.,RWTH Aachen
New Journal of Physics | Year: 2013

We consider the realization of universal quantum computation through braiding of Majorana fermions supplemented by unprotected preparation of noisy ancillae. It has been shown by Bravyi (2006 Phys. Rev. A 73 042313) that under the assumption of perfect braiding operations, universal quantum computation is possible if the noise rate on a particular four-fermion ancilla is below 40%. We show that beyond a noise rate of 89% on this ancilla the quantum computation can be efficiently simulated classically: we explicitly show that the noisy ancilla is a convex mixture of Gaussian fermionic states in this region, while for noise rates below 53% we prove that the state is not a mixture of Gaussian states. These results are obtained by generalizing concepts in entanglement theory to the setting of Gaussian states and their convex mixtures. In particular, we develop a complete set of criteria, namely the existence of a Gaussian-symmetric extension, which determine whether a state is a convex mixture of Gaussian states. © IOP Publishing and Deutsche Physikalische Gesellschaft. Source


Bosman P.A.N.,Centrum Wiskunde and Informatica
IEEE Transactions on Evolutionary Computation | Year: 2012

Algorithms that make use of the gradient, i.e., the direction of maximum improvement, to search for the optimum of a single-objective function have been around for decades. They are commonly accepted to be important and have been applied to tackle single-objective optimization problems in many fields. For multiobjective optimization problems, much less is known about the gradient and its algorithmic use. In this paper, we aim to contribute to the understanding of gradients for numerical, i.e., real-valued, multiobjective optimization. Specifically, we provide an analytical parametric description of the set of all nondominated, i.e., most promising, directions in which a solution can be moved such that the objective values either improve or remain the same. This result completes previous work where this set is described only for one particular case, namely when some of the nondominated directions have positive, i.e., nonimproving, components and the final set can be computed by taking the subset of directions that are all nonpositive. In addition we use our result to assess the utility of using gradient information for multiobjective optimization where the goal is to obtain a Pareto set of solutions that approximates the optimal Pareto set. To this end, we design and consider various multiobjective gradient-based optimization algorithms. One of these algorithms uses the description of the multiobjective gradient provided here. Also, we hybridize an existing multiobjective evolutionary algorithm (MOEA) with the various multiobjective gradient-based optimization algorithms. During optimization, the performance of the gradient-based optimization algorithms is monitored and the available computational resources are redistributed to allow the (currently) most effective algorithm to spend the most resources. We perform an experimental analysis using a few well-known benchmark problems to compare the performance of different optimization methods. The results underline that the use of a population of solutions that is characteristic of MOEAs is a powerful concept if the goal is to obtain a good Pareto set, i.e., instead of only a single solution. This makes it hard to increase convergence speed in the initial phase using gradient information to improve any single solution. However, in the longer run, the use of gradient information does ultimately allow for better fine-tuning of the results and thus better overall convergence. © 2011 IEEE. Source


Fehr S.,Centrum Wiskunde and Informatica | Berens S.,Leiden University
IEEE Transactions on Information Theory | Year: 2014

The Rényi entropy of general order unifies the well-known Shannon entropy with several other entropy notions, like the min-entropy or collision entropy. In contrast to the Shannon entropy, there seems to be no commonly accepted definition for the conditional Rényi entropy: several versions have been proposed and used in the literature. In this paper, we reconsider the definition for the conditional Rényi entropy of general order as proposed by Arimoto in the seventies. We show that this particular notion satisfies several natural properties. In particular, we show that it satisfies monotonicity under conditioning, meaning that conditioning can only reduce the entropy, and (a weak form of) chain rule, which implies that the decrease in entropy due to conditioning is bounded by the number of bits one conditions on. None of the other suggestions for the conditional Rényi entropy satisfies both these properties. Finally, we show a natural interpretation of the conditional Rényi entropy in terms of (unconditional) Rényi divergence, and we show consistency with a recently proposed notion of conditional Rényi entropy in the quantum setting. © 2014 IEEE. Source


Mancinska L.,University of Waterloo | Scarpa G.,Centrum Wiskunde and Informatica | Severini S.,University College London
IEEE Transactions on Information Theory | Year: 2013

We introduce two generalizations of Kochen-Specker (KS) sets: projective KS sets and generalized KS sets. We then use projective KS sets to characterize all graphs for which the chromatic number is strictly larger than the quantum chromatic number. Here, the quantum chromatic number is defined via a nonlocal game based on graph coloring. We further show that from any graph with separation between these two quantities, one can construct a classical channel for which entanglement assistance increases the one-shot zero-error capacity. As an example, we exhibit a new family of classical channels with an exponential increase. © 1963-2012 IEEE. Source

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