Understanding as integration of heterogeneous representations

The search for understanding is a major aim of science. Traditionally, understanding has been undervalued in the philosophy of science because of its psychological underpinnings; nowadays, however, it is widely recognized that epistemology cannot be divorced from psychology as sharp as traditional epistemology required. This eliminates the main obstacle to give scientific understanding due attention in philosophy of science. My aim in this paper is to describe an account of scientific understanding as an emergent feature of our mastering of different (causal) explanatory frameworks that takes place through the mastering of scientific practices. Different practices lead to different kinds of representations. Such representations are often heterogeneous. The integration of such representations constitute understanding

Asymptotically Exact Approximations for the Symmetric Difference of Generalized Marcum-Q Functions

(c) 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. DOI: 10.1109/TVT.2014.2337263In this paper, we derive two simple and asymptotically exact approximations for the function defined as ΔQm(a, b) =Δ Qm(a, b) - Qm(b, a). The generalized Marcum Q-function Qm(a, b) appears in many scenarios in communications in this particular form and is referred to as the symmetric difference of generalized Marcum Q-functions or the difference of generalized Marcum Q-functions with reversed arguments. We show that the symmetric difference of Marcum Q-functions can be expressed in terms of a single Gaussian Q-function for large and even moderate values of the arguments a and b. A second approximation for ΔQm(a, b) is also given in terms of the exponential function. We illustrate the applicability of these new approximations in different scenarios: 1) statistical characterization of Hoyt fading; 2) performance analysis of communication systems; 3) level crossing statistics of a sampled Rayleigh envelope; and 4) asymptotic approximation of the Rice Ie-function.Universidad de Málaga. Campus de Excelencia Internacional. Andalucía Tech

Diphoton decay for a 750750 GeV scalar boson in an U(1)XU(1)_{X} model

In the context of a nonuniversal and anomaly free $U(1)_{X}$ extension of the standard model, we examine the decay of a $750$GeV scalar singlet state, $\xi_{\chi}$, as a possible explanation of the observed diphoton excess announced by the ATLAS and CMS collaborations at CERN-LHC collider. One-loop decay to photons is allowed through three heavy singlet quarks and one charged Higgs boson into the loop. We obtain, for different width approximations and for masses of the exotic singlet quarks in the region $[900,\,3000]$ GeV, a production cross section $\sigma(pp\to\xi_{\chi}\to\gamma\gamma)$ compatible with ATLAS and CMS collaborations data. We also include another scalar singlet, $\sigma$, as a dark matter candidate that may couple with the 750 GeV scalar at tree level with production cross sections in agreement with ATLAS and CMS.Comment: 5 figures, discussion extended, 2 new figure

Conserved quantities for a charged rotating black holes in 5D Einstein-Maxwell-Chern-Simons theory

Indexación: Scopus.In this work, we compute the conserved quantities of a charged rotating black hole which appears as the solution of Einstein-Maxwell action in five dimensions coupled to a Chern-Simons term for U(1) field. The addition of the Chern-Simons term will modify the Maxwell equations and the definition of charge but not the Einstein field equations. Upon the addition of suitable boundary terms for the pure gravity sector of the theory, which depend on the extrinsic and intrinsic curvatures (Kounterterms), we obtain the correct conserved quantities of the solution. © Published under licence by IOP Publishing Ltd.We thank Giorgos Anastasiou and David Rivera-Betancour for insightful discussions. This work was funded in part by FONDECYT Grant 1131075, UNAB Grant DI-1336-16/RG and CONICYT Grant DPI 20140115.https://iopscience.iop.org/article/10.1088/1742-6596/1043/1/01202

Automatic Generation of Cognitive Theories using Genetic Programming

Cognitive neuroscience is the branch of neuroscience that studies the neural mechanisms underpinning cognition and develops theories explaining them. Within cognitive neuroscience, computational neuroscience focuses on modeling behavior, using theories expressed as computer programs. Up to now, computational theories have been formulated by neuroscientists. In this paper, we present a new approach to theory development in neuroscience: the automatic generation and testing of cognitive theories using genetic programming. Our approach evolves from experimental data cognitive theories that explain “the mental program” that subjects use to solve a specific task. As an example, we have focused on a typical neuroscience experiment, the delayed-match-to-sample (DMTS) task. The main goal of our approach is to develop a tool that neuroscientists can use to develop better cognitive theories