Quantum Singular Value Decomposer

We present a variational quantum circuit that produces the Singular Value Decomposition of a bipartite pure state. The proposed circuit, that we name Quantum Singular Value Decomposer or QSVD, is made of two unitaries respectively acting on each part of the system. The key idea of the algorithm is to train this circuit so that the final state displays exact output coincidence from both subsystems for every measurement in the computational basis. Such circuit preserves entanglement between the parties and acts as a diagonalizer that delivers the eigenvalues of the Schmidt decomposition. Our algorithm only requires measurements in one single setting, in striking contrast to the $3^n$ settings required by state tomography. Furthermore, the adjoints of the unitaries making the circuit are used to create the eigenvectors of the decomposition up to a global phase. Some further applications of QSVD are readily obtained. The proposed QSVD circuit allows to construct a SWAP between the two parties of the system without the need of any quantum gate communicating them. We also show that a circuit made with QSVD and CNOTs acts as an encoder of information of the original state onto one of its parties. This idea can be reversed and used to create random states with a precise entanglement structure.Comment: 6 + 1 pages, 5 figure

The temporal evolution of the energy flux across scales in homogeneous turbulence

A temporal study of energy transfer across length scales is performed in 3D numerical simulations of homogeneous shear flow and isotropic turbulence. The average time taken by perturbations in the energy flux to travel between scales is measured and shown to be additive. Our data suggests that the propagation of disturbances in the energy flux is independent of the forcing and that it defines a `velocity' that determines the energy flux itself. These results support that the cascade is, on average, a scale-local process where energy is continuously transmitted from one scale to the next in order of decreasing size.Comment: Accepted for publication as a Letter in Physics of Fluid

Types of carbon adsorbents and their production

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Pilas y acumuladores comerciales (y II). Sistemas secundarios y especiales

Con este segundo capítulo se completa esta pequeña serie dedicada a pilas y acumuladores comerciales. Se abordan aquí con cierta extensión los sistemas especiales, de gran interés y poco conocidos generalmente. El resto del capítulo se dedica a acumuladores

Molecular Characterization of Apricot Germplasm from an Old Stone Collection

Increasing germplasm erosion requires the recovery and conservation of traditional cultivars before they disappear. Here we present a particular case in Spain where a thorough prospection of local fruit tree species was performed in the 1950s with detailed data of the origin of each genotype but, unfortunately, the accessions are no longer conserved in ex situ germplasm collections. However, for most of those cultivars, an old stone collection is still preserved. In order to analyze the diversity present at the time when the prospection was made and to which extent variability has been eroded, we developed a protocol in apricot (Prunus armeniaca L.) to obtain DNA from maternal tissues of the stones of a sufficient quality to be amplified by PCR. The results obtained have been compared with the results from the profiles developed from apricot cultivars currently conserved in ex situ germplasm collections. The results highlight the fact that most of the old accessions are not conserved ex situ but provide a tool to prioritize the recovery of particular cultivars. The approach used in this work can also be applied to other plant species where seeds have been preserved

Discovering Rehabilitation trends in Spain: A bibliometric analysis

The main purpose of this study is to offer an overview of the rehabilitation research area in Spain from 1970 to 2018 through a bibliometric analysis. Analysis of performance and a co-word science mapping analysis were conducted to highlight the topics covered. The software tool SciMAT was used to analyse the themes concerning their performance and impact measures. A total of 3,564 documents from the Web of Science were retrieved. Univ Deusto, Univ Rey Juan Carlos and Basque Foundation for Science are the institutions with highest relative priority. The most important research themes are IntellectualDisability, Neck-Pain and Pain

A Decision Tree and S-Transform Based Approach for Power Quality Disturbances Classification

In this paper, it is presented an automated classification based on S-transform as feature extraction tool and Decision Tree as algorithm classifier. The signals generated according to mathematical models, including complex disturbances, have been used to design and test this approach, where noise is added to the signals from 40dB to 20dB. Finally, several disturbances, simple and complex, have been considered to test the implemented system. Evaluation results verifying the accuracy of the proposed method are presented.IEE

Double-Weighting for Covariate Shift Adaptation

Supervised learning is often affected by a covariate shift in which the marginal distributions of instances (covariates $x$) of training and testing samples $\mathrm{p}_\text{tr}(x)$ and $\mathrm{p}_\text{te}(x)$ are different but the label conditionals coincide. Existing approaches address such covariate shift by either using the ratio $\mathrm{p}_\text{te}(x)/\mathrm{p}_\text{tr}(x)$ to weight training samples (reweighted methods) or using the ratio $\mathrm{p}_\text{tr}(x)/\mathrm{p}_\text{te}(x)$ to weight testing samples (robust methods). However, the performance of such approaches can be poor under support mismatch or when the above ratios take large values. We propose a minimax risk classification (MRC) approach for covariate shift adaptation that avoids such limitations by weighting both training and testing samples. In addition, we develop effective techniques that obtain both sets of weights and generalize the conventional kernel mean matching method. We provide novel generalization bounds for our method that show a significant increase in the effective sample size compared with reweighted methods. The proposed method also achieves enhanced classification performance in both synthetic and empirical experiments

Evolucion y perspectivas del sector vitivinicola

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