Geometric quantum computation

Abstract

We describe in detail a general strategy for implementing a conditional geometric phase between two spins. Combined with single-spin operations, this simple operation is a universal gate for quantum computation, in that any unitary transformation can be implemented with arbitrary precision using only single-spin operations and conditional phase shifts. Thus quantum geometrical phases can form the basis of any quantum computation. Moreover, as the induced conditional phase depends only on the geometry of the paths executed by the spins it is resilient to certain types of errors and offers the potential of a naturally fault-tolerant way of performing quantum computation.     

Optimisation of a serine protease coupling to Eudragit S‐100 by experimental design techniques

A full factorial design was used to study the influence of four different variables, namely polymer concentration, carbodiimide concentration, time of reaction and blocking agent concentration, on the coupling of a serine protease into a soluble–insoluble polymer (Eudragit S‐100). All of the four factors studied have played a critical role in the protease coupling. Response surface methodology was used as an optimisation strategy to attain a conjugate with high activity yield and operational stability at 60 °C. Under optimised conditions (Eudragit, 2.5% w/v, carbodiimide, 0.2% w/v, coupling time, 1 h and blocking agent concentration, 0.05%), the conjugate activity yield was about 45% and its operational stability at 60 °C was increased by 1.7 times. After reusing the conjugate for five cycles, the remaining activity was still 72% of the initial value when compared with the native enzyme. Several tests confirmed that the enzyme was covalently crosslinked to Eudragit, which represents an improvement in the carbodiimide coupling of proteases into soluble–insoluble polymers. Copyright © 2005 Society of Chemical Industry     

Molecule–Graphene Hybrid Materials with Tunable Mechanoresponse: Highly Sensitive Pressure Sensors for Health Monitoring

The development of pressure sensors is crucial for the implementation of electronic skins and for health monitoring integrated into novel wearable devices. Tremendous effort is devoted toward improving their sensitivity, e.g., by employing microstructured electrodes or active materials through cumbersome processes. Here, a radically new type of piezoresistive pressure sensor based on a millefeuille‐like architecture of reduced graphene oxide (rGO) intercalated by covalently tethered molecular pillars holding on‐demand mechanical properties are fabricated. By applying a tiny pressure to the multilayer structure, the electron tunnelling ruling the charge transport between successive rGO sheets yields a colossal decrease in the material's electrical resistance. Significantly, the intrinsic rigidity of the molecular pillars employed enables the fine‐tuning of the sensor's sensitivity, reaching sensitivities as high as 0.82 kPa^?1 in the low pressure region (0–0.6 kPa), with short response times (≈24 ms) and detection limit (7 Pa). The pressure sensors enable efficient heartbeat monitoring and can be easily transformed into a matrix capable of providing a 3D map of the pressure exerted by different objects.     

Photomodulation of Charge Transport in All-Semiconducting 2D–1D van der Waals Heterostructures with Suppressed Persistent Photoconductivity Effect

Van der Waals heterostructures (VDWHs), obtained via the controlled assembly of 2D atomically thin crystals, exhibit unique physicochemical properties, rendering them prototypical building blocks to explore new physics and for applications in optoelectronics. As the emerging alternatives to graphene, monolayer transition metal dichalcogenides and bottom-up synthesized graphene nanoribbons (GNRs) are promising candidates for overcoming the shortcomings of graphene, such as the absence of a bandgap in its electronic structure, which is essential in optoelectronics. Herein, VDWHs comprising GNRs onto monolayer MoS₂ are fabricated. Field-effect transistors (FETs) based on such VDWHs show an efficient suppression of the persistent photoconductivity typical of MoS₂, resulting from the interfacial charge transfer process. The MoS₂-GNR FETs exhibit drastically reduced hysteresis and more stable behavior in the transfer characteristics, which is a prerequisite for the further photomodulation of charge transport behavior within the MoS₂-GNR VDWHs. The physisorption of photochromic molecules onto the MoS₂-GNR VDWHs enables reversible light-driven control over charge transport. In particular, the drain current of the MoS₂-GNR FET can be photomodulated by 52%, without displaying significant fatigue over at least 10 cycles. Moreover, four distinguishable output current levels can be achieved, demonstrating the great potential of MoS₂-GNR VDWHs for multilevel memory devices.     

LDPE/PET laminated films modified with FeO(OH) × H2O,Fe2O3, and ascorbic acid to develop oxygen scavenging system for food packaging

The iron compounds (iron(III) oxide‐hydroxide monohydrate FeO(OH) × H₂O, iron(III) oxide Fe₂O₃, and ascorbic acid) were used as oxygen scavengers modifiers in laminating of polymer films. This oxygen‐scavenging system was coated on preselected films (low density polyethylene [LDPE] and polyethylene terephthalate [PET]) from which the laminates were formed. It presents the new form of composite material packaging that has the function of oxygen scavenging, which could be suitable for food packaging. The scope of the research included studies of morphology of oxygen scavengers by scanning electron microscope and their average particle size distribution measure by particle size analyzer, the effect of type, and concentration of these substances on viscosity of adhesive and seal strength of laminates. The Fourier‐transform infrared spectroscopy (FTIR) of laminates was also performed to observe the potential interaction of functional groups of polyurethane adhesives with oxygen scavenger components. The most important ability of the developed system for oxygen scavenging was confirmed by measuring oxygen concentration (% vol) in a headspace with the prepared laminates. The concentrations of selected oxygen scavengers (4‐6 wt%) and their combinations were studied. The most effective oxygen scavenger system integrated within the PE/PET composite film consists of 6 wt% ascorbic acid and 1 wt% FeO(OH) × H₂O, where the oxygen concentration of 1.0 vol% (±0.20 vol%) was obtained after 15 days of storage. It was found that in this system the oxygen scavenging reaction occurs through ascorbate oxidation to dehydroascorbic acid, which is catalyzed by reduction of Fe³⁺ to Fe2⁺ ions.     

Representing Hyper-arithmetical Sets by Equations over Sets of Integers

Systems of equations with sets of integers as unknowns are considered. It is shown that the class of sets representable by unique solutions of equations using the operations of union and addition, defined as S+T={m+n?Om??S,n??T}, and with ultimately periodic constants is exactly the class of hyper-arithmetical sets. Equations using addition only can represent every hyper-arithmetical set under a simple encoding. All hyper-arithmetical sets can also be represented by equations over sets of natural numbers equipped with union, addition and subtraction $S \mathop {\mbox {$-^{\hspace {-.5em}\cdot }\,\,$}}T=\{m-n \mid m \in S, n \in T, m \geq n\}$ . Testing whether a given system has a solution is $\varSigma ^{1}_{1}$ -complete for each model. These results, in particular, settle the expressive power of the most general types of language equations, as well as equations over subsets of free groups.     

An unsupervised approach to feature discretization and selection

Many learning problems require handling high dimensional datasets with a relatively small number of instances. Learning algorithms are thus confronted with the curse of dimensionality, and need to address it in order to be effective. Examples of these types of data include the bag-of-words representation in text classification problems and gene expression data for tumor detection/classification. Usually, among the high number of features characterizing the instances, many may be irrelevant (or even detrimental) for the learning tasks. It is thus clear that there is a need for adequate techniques for feature representation, reduction, and selection, to improve both the classification accuracy and the memory requirements. In this paper, we propose combined unsupervised feature discretization and feature selection techniques, suitable for medium and high-dimensional datasets. The experimental results on several standard datasets, with both sparse and dense features, show the efficiency of the proposed techniques as well as improvements over previous related techniques.     

Time–HOBI: Index for optimizing star queries

One of the important research and technological problems in data warehouse query optimization concerns star queries. So far, most of the research focused on optimizing such queries by means of join indexes, bitmap join indexes, or various multidimensional indexes. These structures neither support navigation well along dimension hierarchies nor optimize joins with the Time dimension, which in practice is used in most of the star queries. In this paper we propose an index, called Time–HOBI, for optimizing the star queries that compute aggregates along dimension hierarchies. Time–HOBI, created on a dimension hierarchy, is composed of (1) a Hierarchically Organized Bitmap Index (HOBI), where one bitmap index is maintained for one dimension level, and (2) a Time Index (TI) that implicitly encodes time in every dimension. HOBI allows to quickly search for fact rows satisfying predicates defined on different levels of dimension hierarchies. With the support of TI joining a fact table with the Time dimension is avoided. Thus, Time–HOBI supports a broad class of star queries. In this paper we explain how query execution plans for star queries can profit from Time–HOBI. We show, based on experiments, the efficiency of Time–HOBI for different classes of queries, as compared to HOBI and a traditional bitmap index. Based on the experiments, we also demonstrate how sensitive Time–HOBI is to variable selectivity of queries. We also analyze the maintenance time of Time–HOBI as compared to HOBI and a traditional bitmap index. The experiments used in the paper have been conducted on a real dataset, coming from the biggest East-European Internet auction platform Allegro.pl. The experiments show that Time–HOBI can be successfully applied to the optimization of star queries as it offers promising performance improvement.     

Automatic contrast enhancement of low-light images based on local statistics of wavelet coefficients

This paper describes a new method for contrast enhancement in images and image sequences of low-light or unevenly illuminated scenes based on statistical modelling of wavelet coefficients of the image. A non-linear enhancement function has been designed based on the local dispersion of the wavelet coefficients modelled as a bivariate Cauchy distribution. Within the same statistical framework, a simultaneous noise reduction in the image is performed by means of a shrinkage function, thus preventing noise amplification. The proposed enhancement method has been shown to perform very well with insufficiently illuminated and noisy imagery, outperforming other conventional methods, in terms of contrast enhancement and noise reduction in the output data.