A statistical superfield and its observable consequences

A new kind of fundamental superfield is proposed, with an Ising-like Euclidean action. Near the Planck energy it undergoes its first stage of symmetry-breaking, and the ordered phase is assumed to support specific kinds of topological defects. This picture leads to a low-energy Lagrangian which is similar to that of standard physics, but there are interesting and observable differences. For example, the cosmological constant vanishes, fermions have an extra coupling to gravity, the gravitational interaction of W-bosons is modified, and Higgs bosons have an unconventional equation of motion.Comment: 35 pages, LaTe

EPR Steering Inequalities from Entropic Uncertainty Relations

We use entropic uncertainty relations to formulate inequalities that witness Einstein-Podolsky-Rosen (EPR) steering correlations in diverse quantum systems. We then use these inequalities to formulate symmetric EPR-steering inequalities using the mutual information. We explore the differing natures of the correlations captured by one-way and symmetric steering inequalities, and examine the possibility of exclusive one-way steerability in two-qubit states. Furthermore, we show that steering inequalities can be extended to generalized positive operator valued measures (POVMs), and we also derive hybrid-steering inequalities between alternate degrees of freedom.Comment: 10 pages, 2 figure

Structural graph matching using the EM algorithm and singular value decomposition

This paper describes an efficient algorithm for inexact graph matching. The method is purely structural, that is, it uses only the edge or connectivity structure of the graph and does not draw on node or edge attributes. We make two contributions: 1) commencing from a probability distribution for matching errors, we show how the problem of graph matching can be posed as maximum-likelihood estimation using the apparatus of the EM algorithm; and 2) we cast the recovery of correspondence matches between the graph nodes in a matrix framework. This allows one to efficiently recover correspondence matches using the singular value decomposition. We experiment with the method on both real-world and synthetic data. Here, we demonstrate that the method offers comparable performance to more computationally demanding method

Redistribution, capital income taxation and tax evasion

Factor mobility and tax evasión are two phenomena that constraint the effectiveness of redistributive policies now used by the member countries of the European Union. In this paper, a normative analysis of this fact is undertaken using a simple model with two countries and two social classes, where capital is perfectly mobile and labour is immobile. Each country complements the income of its workers, assumed to be poor, with transfers. The latter are financed with two taxes on capital income. The first one, following the origin principie, alters the retum and intemational allocation of capital. The second one, following the residence principie, induces the evasión of capitalists' incomes. Each government chooses the optimal mix of capital taxes that maximizes the welfare of its citizens with no regard on the repercussions on its neighbour country. A numerical exercise is built to examine the sensitivity of the resulting non cooperative equilibrium to the aversión to inequality exhibited by the different governments as well as to the factor endowments of their respective countries

Complexity Characterization in a Probabilistic Approach to Dynamical Systems Through Information Geometry and Inductive Inference

Information geometric techniques and inductive inference methods hold great promise for solving computational problems of interest in classical and quantum physics, especially with regard to complexity characterization of dynamical systems in terms of their probabilistic description on curved statistical manifolds. In this article, we investigate the possibility of describing the macroscopic behavior of complex systems in terms of the underlying statistical structure of their microscopic degrees of freedom by use of statistical inductive inference and information geometry. We review the Maximum Relative Entropy (MrE) formalism and the theoretical structure of the information geometrodynamical approach to chaos (IGAC) on statistical manifolds. Special focus is devoted to the description of the roles played by the sectional curvature, the Jacobi field intensity and the information geometrodynamical entropy (IGE). These quantities serve as powerful information geometric complexity measures of information-constrained dynamics associated with arbitrary chaotic and regular systems defined on the statistical manifold. Finally, the application of such information geometric techniques to several theoretical models are presented.Comment: 29 page

Lipid Ion Channels

The interpretation electrical phenomena in biomembranes is usually based on the assumption that the experimentally found discrete ion conduction events are due to a particular class of proteins called ion channels while the lipid membrane is considered being an inert electrical insulator. The particular protein structure is thought to be related to ion specificity, specific recognition of drugs by receptors and to macroscopic phenomena as nerve pulse propagation. However, lipid membranes in their chain melting regime are known to be highly permeable to ions, water and small molecules, and are therefore not always inert. In voltage-clamp experiments one finds quantized conduction events through protein-free membranes in their melting regime similar to or even undistinguishable from those attributed to proteins. This constitutes a conceptual problem for the interpretation of electrophysiological data obtained from biological membrane preparations. Here, we review the experimental evidence for lipid ion channels, their properties and the physical chemistry underlying their creation. We introduce into the thermodynamic theory of membrane fluctuations from which the lipid channels originate. Furthermore, we demonstrate how the appearance of lipid channels can be influenced by the alteration of the thermodynamic variables (temperature, pressure, tension, chemical potentials) in a coherent description that is free of parameters. This description leads to pores that display dwell times closely coupled to the fluctuation lifetime via the fluctuation-dissipation theorem. Drugs as anesthetics and neurotransmitters are shown to influence the channel likelihood and their lifetimes in a predictable manner. We also discuss the role of proteins in influencing the likelihood of lipid channel formation.Comment: Revie