A nanoflare based cellular automaton model and the observed properties of the coronal plasma

We use the cellular automaton model described in L\'opez Fuentes \& Klimchuk (2015, ApJ, 799, 128) to study the evolution of coronal loop plasmas. The model, based on the idea of a critical misalignment angle in tangled magnetic fields, produces nanoflares of varying frequency with respect to the plasma cooling time. We compare the results of the model with active region (AR) observations obtained with the Hinode/XRT and SDO/AIA instruments. The comparison is based on the statistical properties of synthetic and observed loop lightcurves. Our results show that the model reproduces the main observational characteristics of the evolution of the plasma in AR coronal loops. The typical intensity fluctuations have an amplitude of 10 to 15\% both for the model and the observations. The sign of the skewness of the intensity distributions indicates the presence of cooling plasma in the loops. We also study the emission measure (EM) distribution predicted by the model and obtain slopes in log(EM) versus log(T) between 2.7 and 4.3, in agreement with published observational values.Comment: Paper 2 of 2: Model comparison with observations. Accepted for publication in Ap

Optimal conclusive teleportation of quantum states

Quantum teleportation of qudits is revisited. In particular, we analyze the case where the quantum channel corresponds to a non-maximally entangled state and show that the success of the protocol is directly related to the problem of distinguishing non-orthogonal quantum states. The teleportation channel can be seen as a coherent superposition of two channels, one of them being a maximally entangled state thus, leading to perfect teleportation and the other, corresponding to a non-maximally entangled state living in a subspace of the d-dimensional Hilbert space. The second channel leads to a teleported state with reduced fidelity. We calculate the average fidelity of the process and show its optimality.Comment: 8 pages, revtex, no figure

Comparison of different repetitive control architectures: synthesis and comparison. Application to VSI Converters

Repetitive control is one of the most used control approaches to deal with periodic references/disturbances. It owes its properties to the inclusion of an internal model in the controller that corresponds to a periodic signal generator. However, there exist many different ways to include this internal model. This work presents a description of the different schemes by means of which repetitive control can be implemented. A complete analytic analysis and comparison is performed together with controller synthesis guidance. The voltage source inverter controller experimental results are included to illustrative conceptual developmentsPeer ReviewedPostprint (published version

A simple model for the evolution of multi-stranded coronal loops

We develop and analyze a simple cellular automaton (CA) model that reproduces the main properties of the evolution of soft X-ray coronal loops. We are motivated by the observation that these loops evolve in three distinguishable phases that suggest the development, maintainance, and decay of a self-organized system. The model is based on the idea that loops are made of elemental strands that are heated by the relaxation of magnetic stress in the form of nanoflares. In this vision, usually called "the Parker conjecture" (Parker 1988), the origin of stress is the displacement of the strand footpoints due to photospheric convective motions. Modeling the response and evolution of the plasma we obtain synthetic light curves that have the same characteristic properties (intensity, fluctuations, and timescales) as the observed cases. We study the dependence of these properties on the model parameters and find scaling laws that can be used as observational predictions of the model. We discuss the implications of our results for the interpretation of recent loop observations in different wavelengths.Comment: 2010, accepted for publication in Ap

On the determinants of the Chilean Economic Growth

This paper presents several methodologies for understanding the Chilean growth process. By using univariate time series representations, we find that the Chilean data is more consistent with exogenous than with endogenous growth models. Growth accounting exercises show that the mild growth rates of the sixties are mainly due to the accumulation of human and physical capital, while the booms of the mid seventies and the one from 1985 until 1998 are mainly due to TFP growth. We also find that among the most important determinants of the evolution of TFP are the evolution of terms of trade, improvements on the quality of capital, and the presence of distortions. In fact, distortions do not only eliminate the positive effects of improvements on the quality of capital, but also precede the evolution of technology shocks and increase their volatility. A dynamic stochastic general equilibrium model that explicitly incorporates the relative price of investment with respect to consumption goods, terms of tra de, and distortionary taxes is able to successfully replicate the impulse-response functions found on the data. This exercise suggests that distortions play a key role in explaining the growth dynamics of the Chilean experience.

THE ECONOMICS OF INCREASING SPEED IN SEA TRANSPORTATION: THE CASE FOR THE SOUTHERN U.S., MEXICO, CENTRAL AMERICA AND THE CARIBBEAN

Public Economics,

Universal Behavior of Extreme Price Movements in Stock Markets

Many studies assume stock prices follow a random process known as geometric Brownian motion. Although approximately correct, this model fails to explain the frequent occurrence of extreme price movements, such as stock market crashes. Using a large collection of data from three different stock markets, we present evidence that a modification to the random model -- adding a slow, but significant, fluctuation to the standard deviation of the process -- accurately explains the probability of different-sized price changes, including the relative high frequency of extreme movements. Furthermore, we show that this process is similar across stocks so that their price fluctuations can be characterized by a single curve. Because the behavior of price fluctuations is rooted in the characteristics of volatility, we expect our results to bring increased interest to stochastic volatility models, and especially to those that can produce the properties of volatility reported here.Comment: 4 pages, 3 figure

A minimalistic approach for fast computation of geodesic distances on triangular meshes

The computation of geodesic distances is an important research topic in Geometry Processing and 3D Shape Analysis as it is a basic component of many methods used in these areas. In this work, we present a minimalistic parallel algorithm based on front propagation to compute approximate geodesic distances on meshes. Our method is practical and simple to implement and does not require any heavy pre-processing. The convergence of our algorithm depends on the number of discrete level sets around the source points from which distance information propagates. To appropriately implement our method on GPUs taking into account memory coalescence problems, we take advantage of a graph representation based on a breadth-first search traversal that works harmoniously with our parallel front propagation approach. We report experiments that show how our method scales with the size of the problem. We compare the mean error and processing time obtained by our method with such measures computed using other methods. Our method produces results in competitive times with almost the same accuracy, especially for large meshes. We also demonstrate its use for solving two classical geometry processing problems: the regular sampling problem and the Voronoi tessellation on meshes.Comment: Preprint submitted to Computers & Graphic