Quantum walks: a comprehensive review

Quantum walks, the quantum mechanical counterpart of classical random walks, is an advanced tool for building quantum algorithms that has been recently shown to constitute a universal model of quantum computation. Quantum walks is now a solid field of research of quantum computation full of exciting open problems for physicists, computer scientists and engineers. In this paper we review theoretical advances on the foundations of both discrete- and continuous-time quantum walks, together with the role that randomness plays in quantum walks, the connections between the mathematical models of coined discrete quantum walks and continuous quantum walks, the quantumness of quantum walks, a summary of papers published on discrete quantum walks and entanglement as well as a succinct review of experimental proposals and realizations of discrete-time quantum walks. Furthermore, we have reviewed several algorithms based on both discrete- and continuous-time quantum walks as well as a most important result: the computational universality of both continuous- and discrete-time quantum walks.     

An XPS and reduction study of PrCoO3

The perovskite-type oxide PrCoO₃ has been studied by means of X-ray photoelectron spectroscopy (XPS), reduction in H₂ and X-ray diffraction. Two types of oxygen were detected: lattice oxygen (binding energy = 528.4 eV) and adsorbed oxygen (binding energy = 530.9 eV). The increase in relative intensity of the peak corresponding to the latter species after reduction of PrCo0₃ to 3e^– per molecule is assigned to the formation of hydroxyl groups. Temperature-programmed reduction (TPR) results showed two reduction steps: to 1 e^– per molecule (Co^3.1 Co²⁺) at 475 to 635 K, and to 3e^– per molecule (Co²¹ Co⁰) at 725 to 815 K. Reduction in the first and second steps occurs according to the contracting sphere model and the nucleation mechanism, respectively. Reduction of Co³⁺ to Co²⁺ causes minimal structural changes in the perovskite. Reduction to 3e^– per molecule yielded Pr₂O₃ and metallic cobalt. After this reduction and reoxidation at 973 K, the perovskite structure was regained. By XPS and TPR it was shown that PrCo0₃ is more easily reducible than LaCo0₃. It is concluded that the cation in the A position of the structure plays a significant role in the bulk and surface properties of LnCo0₃ (Ln, lanthanide elements) oxides.     

Reliability Analysis Applied on Land Subsidence Effects of Groundwater Remediation: Probabilistic vs. Deterministic Approach

The quantification of soil variability is one of the most important aspects in the geo-engineering context. The uncertainty analysis is the main part of the reliability assessment for which a quantitative evaluation was performed in this study. The Reliability Index and the Probability of Failure using the First-Order Reliability Method (FORM) represents both, an effective method which is easy to implement at the same time. This work analyzes possible effects of compaction induced into the aquifer of the Scarlino Plain, caused by the extension of the hydraulic barrier for groundwater remediation. The currently implemented vertical barrier is composed of 12 wells which reach the depth of 10 m. The improvement of the project involves the construction of a further 40 clusters, each consisting of a doublet which intercepts different depths (10 and 18 m). The models of the subsoil stratigraphy and of the groundwater were built using a numerical model. The groundwater flow and the piezometric surface in the current configuration of the barrier were studied and the project configuration was evaluated. Using the Aquitard drainage model, the land subsidence was estimated to calculate the maximum admissible displacement related to exhibited goods, the so called territorial vulnerability. The evaluation analysis was performed using a traditional deterministic approach, followed by a reliability method based on probabilistic models. Finally, the respective results were reported in a soil mapping with overlapping layers.     

Crystallinity and thermal properties of ethylene-1-decene copolymers

Summary Three copolymers of ethylene and 1-decene, covering a wide range of compositions, have been synthesized with a MgCl₂-supported Ziegler-Natta catalyst. The analysis by DSC and X-ray shows a great degree of heterogeneity in these copolymers and appreciable levels of crystallinity, corresponding to the orthorhombic lattice of polyethylene, are present even for very high 1-decene contents.     

Optical–microphysical properties of smoke haze from Siberian forest fires in summer 2012

A comprehensive experiment on the study of dynamics of optical and microphysical characteristics of submicron aerosols in the near-ground air layer was carried out in June–August of 2012 under conditions of extremely strong smoke haze originating from vast forest fires in Siberia. Variations of the spectral angular scattering coefficients and the degree of linear polarization in the visible wavelength range are studied, as well as the mass concentrations of dry fractions of aerosol and black carbon, relative content of black carbon (BC fraction), single scattering albedo, particle size distribution function, complex refractive index of the particulate matter, and parameter of condensation activity of aerosol. Peculiarities of differences between optical and microphysical characteristics of near-ground aerosol in smoke haze and under smokeless conditions are revealed. This study is important for validation of results of remote sensing of the composition of smoke haze and background atmosphere obtained from satellite data and sun photometric measurements at the Aerosol Robotic Network (AERONET).     

Feature selection for k-means clustering stability: theoretical analysis and an algorithm

Stability of a learning algorithm with respect to small input perturbations is an important property, as it implies that the derived models are robust with respect to the presence of noisy features and/or data sample fluctuations. The qualitative nature of the stability property enhardens the development of practical, stability optimizing, data mining algorithms as several issues naturally arise, such as: how “much” stability is enough, or how can stability be effectively associated with intrinsic data properties. In the context of this work we take into account these issues and explore the effect of stability maximization in the continuous (PCA-based) k-means clustering problem. Our analysis is based on both mathematical optimization and statistical arguments that complement each other and allow for the solid interpretation of the algorithm’s stability properties. Interestingly, we derive that stability maximization naturally introduces a tradeoff between cluster separation and variance, leading to the selection of features that have a high cluster separation index that is not artificially inflated by the features variance. The proposed algorithmic setup is based on a Sparse PCA approach, that selects the features that maximize stability in a greedy fashion. In our study, we also analyze several properties of Sparse PCA relevant to stability that promote Sparse PCA as a viable feature selection mechanism for clustering. The practical relevance of the proposed method is demonstrated in the context of cancer research, where we consider the problem of detecting potential tumor biomarkers using microarray gene expression data. The application of our method to a leukemia dataset shows that the tradeoff between cluster separation and variance leads to the selection of features corresponding to important biomarker genes. Some of them have relative low variance and are not detected without the direct optimization of stability in Sparse PCA based k-means. Apart from the qualitative evaluation, we have also verified our approach as a feature selection method for $k$ -means clustering using four cancer research datasets. The quantitative empirical results illustrate the practical utility of our framework as a feature selection mechanism for clustering.     

Role of cognitive and functional performance in the interactions between elderly people with cognitive decline and an avatar on TV

The complexity of new information technologies (IT) may limit the access of elderly people to the information society, exacerbating what is known as “the digital divide,” as they appear to be too challenging for elderly citizens regardless of the integrity of their cognitive status. This study is an attempt to clarify how some cognitive functions (such as attention or verbal memory) may determine the interaction of cognitively impaired elderly people with technology. Twenty participants ranging from mild cognitive impairment to moderate Alzheimer’s disease were assessed by means of a neuropsychological and functional battery and were asked to follow simple commands from an avatar appearing on a TV by means of a remote control, such as asking the participant to confirm their presence or to respond Yes/No to a proposal to see a TV program. The number of correct answers and command repetitions required for the user to respond were registered. The results show that participants with a better cognitive and functional state in specific tests show a significantly better performance in the TV task. The derived conclusion is that neuropsychological assessment may be used as a useful complementary tool for assistive technology developers in the adaptation of IT to the elderly with different cognitive and functional profiles. Further studies with larger samples are required to determine to what extent cognitive functions can actually predict older users’ interaction with technology.     

Stay with the flow: How macroinvertebrate communities recover during the rewetting phase in Alpine streams affected by an exceptional drought

Droughts are affecting an increasing number of lotic ecosystems worldwide due to the combined effects of climatic and anthropogenic pressures. Unlike naturally intermittent rivers, where the drying phase is a part of the annual flow regime, water scarcity in Alpine rivers represents a relatively recent phenomenon and, therefore, a major threat for the biodiversity of these lotic ecosystems. However, Alpine stream community response to drought is still poorly investigated. Here, we assess the recovery of macroinvertebrates in two Alpine streams after a supraseasonal drought. As water returned, a total of 10 sampling sessions were carried out, and temporal patterns in diversity, density, and taxonomic composition of benthic communities, as well as in the percentage of functional feeding groups, were investigated. We found that the resistance of invertebrate communities in Alpine streams is generally low: drought markedly reduced the diversity and density of macroinvertebrates. Conversely, our results suggest that the passive dispersal by drift from the upstream river sections seems the most probable mechanism promoting the post‐drought recovery. Nevertheless, this resilience ability appears to be stream specific and influenced by intrinsic stream characteristics, including the flow permanence and distance from the nearest upstream perennial reach. This work sheds light on the ecological consequences of droughts on macroinvertebrate communities. As flow intermittency in Alpine areas is expected to intensify under current global change scenarios, results of this study provide important information to predict changes in the taxonomic composition and diversity of macroinvertebrate communities.     

Robustness of ISS systems to inputs with limited moving average: Application to spacecraft formations

We provide a theoretical framework that fits realistic challenges related to spacecraft formation with disturbances. We show that the input‐to‐state stability of such systems guarantees some robustness with respect to a class of signals with bounded average‐energy, which encompasses the typical disturbances acting on spacecraft formations. Solutions are shown to converge to the desired formation, up to an offset, which is somewhat proportional to the considered moving average of disturbances. In the presence of fast peaking perturbations, the approach provides a tighter evaluation of the disturbances' influence, which allows for the use of more parsimonious control gains. Copyright © 2015 John Wiley & Sons, Ltd.