Topologically protected quantum gates for computation with non-Abelian anyons in the Pfaffian quantum Hall state

We extend the topological quantum computation scheme using the Pfaffian quantum Hall state, which has been recently proposed by Das Sarma et al., in a way that might potentially allow for the topologically protected construction of a universal set of quantum gates. We construct, for the first time, a topologically protected Controlled-NOT gate which is entirely based on quasihole braidings of Pfaffian qubits. All single-qubit gates, except for the pi/8 gate, are also explicitly implemented by quasihole braidings. Instead of the pi/8 gate we try to construct a topologically protected Toffoli gate, in terms of the Controlled-phase gate and CNOT or by a braid-group based Controlled-Controlled-Z precursor. We also give a topologically protected realization of the Bravyi-Kitaev two-qubit gate g_3.Comment: 6 pages, 7 figures, RevTeX; version 3: introduced section names, new reference added; new comment added about the embedding of the one- and two- qubit gates into a three-qubit syste

Facial soft tissue thicknesses in Bulgarian adults: relation to sex, body mass index and bilateral asymmetry

Background: The aim of the study is to measure the facial soft tissue thicknesses (STTs) in Bulgarians, to evaluate the relation of the STTs to the nutritional status, sex and bilateral asymmetry, and to examine the correlations between the separate STTs as well as between the STTs and body weight, height, and body mass index (BMI). In the present study, the facial STTs were measured on computed tomography scans of the head of Bulgarian adults. Materials and methods: The STTs were measured at 7 midline and 9 bilateral landmarks. The measurements were performed in the free software InVesalius in the axial and sagittal planes. The mean, standard deviation, minimum and maximum values, median and coefficient of variation were reported for the STT at each landmark according to the sex and BMI category. The BMI, sex and bilateral differences were assessed for statistical significance. Pearson correlation analysis was applied to assess the strength and direction of the relationships between the STTs and body height, weight and BMI, as well as between separate STTs. Results and Conclusions: The facial soft tissues in Bulgarian adults changed in accordance with the nutritional status of the individual and in both sexes all STTs augmented with the increasing BMI. For both normal and overweight BMI categories, males had more soft tissue at the majority of facial points than females, as the only exceptions were observed in the cheek zone, where STTs were thicker in females. Significant bilateral differences were observed in either sex and BMI category. Stronger correlations were established for the STTs in the jaw region and between the cheek and jaw soft tissues. Besides, the correlations between the homologous bilateral landmarks were among the strongest ones

Fluctuations and Correlations in Lattice Models for Predator-Prey Interaction

Including spatial structure and stochastic noise invalidates the classical Lotka-Volterra picture of stable regular population cycles emerging in models for predator-prey interactions. Growth-limiting terms for the prey induce a continuous extinction threshold for the predator population whose critical properties are in the directed percolation universality class. Here, we discuss the robustness of this scenario by considering an ecologically inspired stochastic lattice predator-prey model variant where the predation process includes next-nearest-neighbor interactions. We find that the corresponding stochastic model reproduces the above scenario in dimensions 1< d \leq 4, in contrast with mean-field theory which predicts a first-order phase transition. However, the mean-field features are recovered upon allowing for nearest-neighbor particle exchange processes, provided these are sufficiently fast.Comment: 5 pages, 4 figures, 2-column revtex4 format. Emphasis on the lattice predator-prey model with next-nearest-neighbor interaction (Rapid Communication in PRE

The 2D/3D Best-Fit Problem

In computer systems, the best-fit problem can be described as a search for the best transformation matrix to transform input mea- sured points from their coordinate system into a CAD model coordinate system using a criteria function for optimization. For example, if the criterion is Mini- mum Sum of Deviations, we search for a transformation matrix M that minimizes the sum of all distances from an matrix-transformed measure points to a CAD model

PREHRANA KLENA Leuciscus cephalus (Linnaeasus, 1758) IZ RIJEKE BABUNE

On the total number of 550 fish being caught in 1978 on three parts of the river Babuna there was investigated quantitative composition of the food seasonally and on the age classes. Chub from the river Babuna is omnivorous with the predominance of the floristic compound in his nutrition. The main mass of the food has autochtonous character. In the spring time the main mass of the food has autochtonous character. In the spring time, the main component are algues from Chrysophyceae plant group and Ephemeroptera by the animal part, along all the habitat of L. cephalus when Plecoptera are present in the upper and meddle part of the river. In the summer period, the dominant plant group is Conjugatophyceae different animal component from the river. Chrysophyceae are dominant also in the autumn period from the plant composition, group s by the animal composition vary from part to part, while Pisces can be found in the meddle part. In the winter time, dominant plant particle are Bacillariophyceae. Animal particles are also different from part to part. Pisces are present in the meddle part, too. Young fish are fed by Diatomeae and Chironomidae. Fish old er than 1+ principally take the food of plant origin and Conjugatae, also insects larves, partially detritus, and the oldest age classes are fed by Pisces.Godine 1978. na trima lokacijama u rijeci Babuni ulovljeno je 550 klenova. Kvantitativni sastav njihove hrane proučen je prema sezonama i dobnim razredima. Klen je u rijeci Babuni omnivoran, pri čemu prevladava floristička komponenta u njihovoj prehrani. Glavnina je njegove hrane autohtonog podrijetla. U cijelom području rijeke u proljeće u prehrani klena od biljaka prevladavaju alge Chrysophyceae, a od životinja Ephemeroptera. U gornjem i srednjem toku rijeke prisutni su Plecoptera. Ljeti od biljaka prevladavaju Conjugatophyceae, a životinje su različite u pojedinim dijelovima rijeke. Raznolikost životinja prevladava i u jesen, kada se u srednjem dijelu rijeke mogu naći u ribljoj ishrani. Tada su od biljaka prevladavale Chrysophyceae. Životinjska komponenta u hrani bila je slična i zimi, a od biljaka je uočena dominacija Bacillariophyceae. U prehrani mladih riba prevladavaju Diatomeae i Chironomidae, dok se prehrana ribe starije od 1+ sastoji ponajprije od Conjugatophyceae, zatim ličinki kukaca, djelomično detritusa, a u najstarijim razredima i od riba

Collaborative Deep Learning for Recommender Systems

Collaborative filtering (CF) is a successful approach commonly used by many recommender systems. Conventional CF-based methods use the ratings given to items by users as the sole source of information for learning to make recommendation. However, the ratings are often very sparse in many applications, causing CF-based methods to degrade significantly in their recommendation performance. To address this sparsity problem, auxiliary information such as item content information may be utilized. Collaborative topic regression (CTR) is an appealing recent method taking this approach which tightly couples the two components that learn from two different sources of information. Nevertheless, the latent representation learned by CTR may not be very effective when the auxiliary information is very sparse. To address this problem, we generalize recent advances in deep learning from i.i.d. input to non-i.i.d. (CF-based) input and propose in this paper a hierarchical Bayesian model called collaborative deep learning (CDL), which jointly performs deep representation learning for the content information and collaborative filtering for the ratings (feedback) matrix. Extensive experiments on three real-world datasets from different domains show that CDL can significantly advance the state of the art