5,819 research outputs found

    Analytic Torsion on Hyperbolic Manifolds and the Semiclassical Approximation for Chern-Simons Theory

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    The invariant integration method for Chern-Simons theory for gauge group SU(2) and manifold \Gamma\H^3 is verified in the semiclassical approximation. The semiclassical limit for the partition function associated with a connected sum of hyperbolic 3-manifolds is presented. We discuss briefly L^2 - analytical and topological torsions of a manifold with boundary.Comment: 12 pages, LaTeX fil

    Manejo do nitrogênio para o arroz Irrigado: doses e parcelamento da adubação em cobertura.

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    bitstream/item/30961/1/Circular-86.pd

    Strong curvature singularities in quasispherical asymptotically de Sitter dust collapse

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    We study the occurrence, visibility, and curvature strength of singularities in dust-containing Szekeres spacetimes (which possess no Killing vectors) with a positive cosmological constant. We find that such singularities can be locally naked, Tipler strong, and develop from a non-zero-measure set of regular initial data. When examined along timelike geodesics, the singularity's curvature strength is found to be independent of the initial data.Comment: 16 pages, LaTeX, uses IOP package, 2 eps figures; accepted for publication in Class. Quantum Gra

    Radion production in exclusive processes at CERN LHC

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    In the Randall-Sundrum (RS) scenario the compactification radius of the extra dimension is stabilized by the radion, which is a scalar field lighter than the graviton Kaluza-Klein states. It implies that the detection of the radion will be the first signature of the stabilized RS model. In this paper we study the exclusive production of the radion in electromagnetic and diffractive hadron - hadron collisions at the LHC. Our results demonstrate that the diffractive production of radion is dominant and should be feasible of study at CERN LHC.Comment: 6 pages, 3 figures, 1 tabl

    Phases of massive scalar field collapse

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    We study critical behavior in the collapse of massive spherically symmetric scalar fields. We observe two distinct types of phase transition at the threshold of black hole formation. Type II phase transitions occur when the radial extent (λ)(\lambda) of the initial pulse is less than the Compton wavelength (μ−1\mu^{-1}) of the scalar field. The critical solution is that found by Choptuik in the collapse of massless scalar fields. Type I phase transitions, where the black hole formation turns on at finite mass, occur when λμ≫1\lambda \mu \gg 1. The critical solutions are unstable soliton stars with masses \alt 0.6 \mu^{-1}. Our results in combination with those obtained for the collapse of a Yang-Mills field~{[M.~W. Choptuik, T. Chmaj, and P. Bizon, Phys. Rev. Lett. 77, 424 (1996)]} suggest that unstable, confined solutions to the Einstein-matter equations may be relevant to the critical point of other matter models.Comment: 5 pages, RevTex, 4 postscript figures included using psfi

    Physico-chemical spectroscopic mapping of the planetary nebula NGC 40 and the 2D_NEB, a new 2D algorithm to study ionised nebulae

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    In this paper we present an analysis of the physical and chemical conditions of the planetary nebula NGC 40 through spatially-resolved spectroscopic maps. We also introduce a new algorithm --2D_NEB-- based on the well-established IRAF nebular package, which was developed to enable the use of the spectroscopic maps to easily estimate the astrophysical quantities of ionised nebulae. The 2D_NEB was benchmarked, and we clearly show that it works properly, since it compares nicely with the IRAF nebular software. Using this software, we derive the maps of several physical parameters of NGC 40. From these maps, we conclude that Te[NII] shows only a slight temperature variation from region to region, with its values constrained between ~8,000 K and ~9,500 K. Electron densities, on the other hand, have a much more prominent spatial variation, as Ne[SII] values vary from ~1,000 cm^(-3) to ~3,000 cm^(-3). Maps of the chemical abundances also show significant variations. From the big picture of our work, we strongly suggest that analysis with spatial resolution be mandatory for more complete study of the physical and chemical properties of planetary nebulae.Comment: 15 pages, 10 figures, 8 tables; Accepted for publication in MNRA

    First-principles study of structure and magnetism in copper(Ii)-containing hybrid perovskites

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    We report a first-principles study of hybrid organic–inorganic perovskites with formula [A]Cu(H2 POO)3 (A = triazolium (Trz) and guanidinium (Gua), and H2 POO− = hypophosphite), and [HIm]Cu(HCO2)3 (HIm = imidazolium cation, HCO−2 = formate). The triazolium hypophosphite and the formate have been suggested as possible ferroelectrics. We study the fully relaxed structures with different magnetic orderings and possible phonon instabilities. For the [Trz]Cu hypophosphite, the Trz cation is shown to induce large octahedral distortions due to the Jahn-Teller effect, with Cu-O long-bond ordering along two perpendicular directions, which is correlated with antiferromagnetic ordering and strongly one-dimensional. We find that the structure is dynamically stable with respect to zone-center distortions, but instabilities appear along high symmetry lines in the Brillouin zone. On the other hand, for the [HIm]Cu formate, large octahedral distortions are found, with large Cu-O bonds present in half of the octahedra, in this case along a single direction, and correspondingly, the magnetism is almost two-dimensional

    Training deep neural density estimators to identify mechanistic models of neural dynamics

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    Mechanistic modeling in neuroscience aims to explain observed phenomena in terms of underlying causes. However, determining which model parameters agree with complex and stochastic neural data presents a significant challenge. We address this challenge with a machine learning tool which uses deep neural density estimators-- trained using model simulations-- to carry out Bayesian inference and retrieve the full space of parameters compatible with raw data or selected data features. Our method is scalable in parameters and data features, and can rapidly analyze new data after initial training. We demonstrate the power and flexibility of our approach on receptive fields, ion channels, and Hodgkin-Huxley models. We also characterize the space of circuit configurations giving rise to rhythmic activity in the crustacean stomatogastric ganglion, and use these results to derive hypotheses for underlying compensation mechanisms. Our approach will help close the gap between data-driven and theory-driven models of neural dynamics
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