Dynamics of interacting Dicke model in a coupled-cavity array

We consider the dynamics of an array of mutually interacting cavities, each containing an ensemble of N two-level atoms. By exploring the possibilities offered by ensembles of various dimensions and a range of atom-light and photon-hopping values, we investigate the generation of multisite entanglement, as well as the performance of excitation transfer across the array, resulting from the competition between on-site nonlinearities of the matter-light interaction and intersite photon hopping. In particular, for a three-cavity interacting system it is observed that the initial excitation in the first cavity completely transfers to the ensemble in the third cavity through the hopping of photons between the adjacent cavities. Probabilities of the transfer of excitation of the cavity modes and ensembles exhibit characteristics of fast and slow oscillations governed by coupling and hopping parameters, respectively. In the large-hopping case, by seeding an initial excitation in the cavity at the center of the array, a tripartite W state, as well as a bipartite maximally entangled state, is obtained, depending on the interaction time. Population of the ensemble in a cavity has a positive impact on the rate of excitation transfer between the ensembles and their local cavity modes. In particular, for ensembles of five to seven atoms, tripartite W states can be produced even when the hopping rate is comparable to the cavity-atom coupling rate. A similar behavior of the transfer of excitation is observed for a four-coupled-cavity system with two initial excitations.

Clustering-Based Ensemble Method as an Alternative to Stacking

One of the most popular techniques of generating classifier ensembles is known as stacking which is based on a meta-learning approach. In this paper, we introduce an alternative method to stacking which is based on cluster analysis. Similar to stacking, instances from a validation set are initially classified by all base classifiers. The output of each classifier is subsequently considered as a new attribute of the instance. Following this, a validation set is divided into clusters according to the new attributes and a small subset of the original attributes of the instances. For each cluster, we find its centroid and calculate its class label. The collection of centroids is considered as a meta-classifier. Experimental results show that the new method outperformed all benchmark methods, namely Majority Voting, Stacking J48, Stacking LR, AdaBoost J48, and Random Forest, in 12 out of 22 data sets. The proposed method has two advantageous properties: it is very robust to relatively small training sets and it can be applied in semi-supervised learning problems. We provide a theoretical investigation regarding the proposed method. This demonstrates that for the method to be successful, the base classifiers applied in the ensemble should have greater than 50% accuracy levels.

The effect of niobium and tantalum on physicochemical and catalytic properties of silver and platinum catalysts based on MCF mesoporous cellular foams

MCF, NbMCF and TaMCF Mesostructured Cellular Foams were used as supports for platinum and silver (1 wt%). Metallic and bimetallic catalysts were prepared by grafting of metal species on APTMS (3-aminopropyltrimethoxysilane) and MPTMS (2-mercaptopropyltrimethoxysilane) functionalized supports. Characterizations by X-ray diffraction (XRD), ultraviolet–visible (UV–Vis) spectroscopy, X-ray photoelectron spectroscopy (XPS), X-ray fluorescence (XRF) spectroscopy, and in situ Fourier Transform Infrared (FTIR) spectroscopy allowed to monitor the oxidation state of metals and surface properties of the catalysts, in particular the formation of bimetallic phases and the strong metal–support interactions. It was evidenced that the functionalization agent (APTMS or MPTMS) influenced the metals dispersion, the type of bimetallic species and Nb/Ta interaction with Pt/Ag. Strong Nb–Ag interaction led to the reduction of niobium in the support and oxidation of silver. MPTMS interacted at first with Pt to form Pt–Ag ensembles highly active in CH3OH oxidation. The effect of Pt particle size and platinum–silver interaction on methanol oxidation was also considered. The nature of the functionalization agent strongly influenced the species formed on the surface during reaction with methanol and determined the catalytic activity and selectivity.