250 research outputs found

    Friedmann-like universes with torsion

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    We consider spatially homogeneous and isotropic cosmologies with non-zero torsion. Given the high symmetry of these universes, we adopt a specific form for the torsion tensor that preserves the homogeneity and isotropy of the spatial surfaces. Employing both covariant and metric-based techniques, we derive the torsional versions of the continuity, the Friedmann and the Raychaudhuri equations. These formulae demonstrate how, by playing the role of the spatial curvature, or that of the cosmological constant, torsion can drastically change the evolution of the classic homogeneous and isotropic Friedmann universes. In particular, torsion alone can lead to exponential expansion. For instance, in the presence of torsion, the Milne and the Einstein-de Sitter universes evolve like the de Sitter model. We also show that, by changing the expansion rate of the early universe, torsion can affect the primordial nucleosynthesis of helium-4. We use this sensitivity to impose strong cosmological bounds on the relative strength of the associated torsion field, requiring that its ratio to the Hubble expansion rate lies in the narrow interval (−0.005813, +0.019370-0.005813,\,+0.019370) around zero. Interestingly, the introduction of torsion can \textit{reduce} the production of primordial helium-4, unlike other changes to the standard thermal history of an isotropic universe. Finally, turning to static spacetimes, we find that there exist torsional analogues of the classic Einstein static universe, with all three types of spatial geometry. These models can be stable when the torsion field and the universe's spatial curvature have the appropriate profiles.Comment: Revised article. Section on BBN limits on torsion added. References added and update

    Exploiting Caching and Multicast for 5G Wireless Networks

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    The landscape toward 5G wireless communication is currently unclear, and, despite the efforts of academia and industry in evolving traditional cellular networks, the enabling technology for 5G is still obscure. This paper puts forward a network paradigm toward next-generation cellular networks, targeting to satisfy the explosive demand for mobile data while minimizing energy expenditures. The paradigm builds on two principles; namely caching and multicast. On one hand, caching policies disperse popular content files at the wireless edge, e.g., pico-cells and femto-cells, hence shortening the distance between content and requester. On other hand, due to the broadcast nature of wireless medium, requests for identical files occurring at nearby times are aggregated and served through a common multicast stream. To better exploit the available cache space, caching policies are optimized based on multicast transmissions. We show that the multicast-aware caching problem is NP-hard and develop solutions with performance guarantees using randomized-rounding techniques. Trace-driven numerical results show that in the presence of massive demand for delay tolerant content, combining caching and multicast can indeed reduce energy costs. The gains over existing caching schemes are 19% when users tolerate delay of three minutes, increasing further with the steepness of content access pattern

    Metric-Affine Vector-Tensor correspondence and implications in F(R, T, Q, T, D) gravity

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    We extend the results of antecedent literature on quadratic Metric-Affine Gravity by studying a new quadratic gravity action in vacuum which, besides the usual (non-Riemannian) Einstein-Hilbert contri-bution, involves all the parity even quadratic terms in torsion and non-metricity plus a Lagrangian that is quadratic in the field-strengths of the torsion and non-metricity vector traces. The theory results to be equivalent, on-shell, to a Vector-Tensor theory. We also discuss the sub-cases in which the contribution to the Lagrangian quadratic in the field-strengths of the torsion and non-metricity vectors just exhibits one of the aforementioned quadratic terms. We then report on cosmological aspects of the general quadratic theory in the presence of a perfect cosmological hyperfluid and on implications of our findings in the context of F(R, T, Q, T, D) gravity.(c) 2022 Elsevier B.V. All rights reserved

    Predicting the state of synchronization of financial time series using cross recurrence plots

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    Cross-correlation analysis is a powerful tool for understanding the mutual dynamics of time series. This study introduces a new method for predicting the future state of synchronization of the dynamics of two financial time series. To this end, we use the cross recurrence plot analysis as a nonlinear method for quantifying the multidimensional coupling in the time domain of two time series and for determining their state of synchronization. We adopt a deep learning framework for methodologically addressing the prediction of the synchronization state based on features extracted from dynamically sub-sampled cross recurrence plots. We provide extensive experiments on several stocks, major constituents of the S &P100 index, to empirically validate our approach. We find that the task of predicting the state of synchronization of two time series is in general rather difficult, but for certain pairs of stocks attainable with very satisfactory performance (84% F1-score, on average)

    Application of Market Models to Network Equilibrium Problems

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    We present a general two-side market model with divisible commodities and price functions of participants. A general existence result on unbounded sets is obtained from its variational inequality re-formulation. We describe an extension of the network flow equilibrium problem with elastic demands and a new equilibrium type model for resource allocation problems in wireless communication networks, which appear to be particular cases of the general market model. This enables us to obtain new existence results for these models as some adjustments of that for the market model. Under certain additional conditions the general market model can be reduced to a decomposable optimization problem where the goal function is the sum of two functions and one of them is convex separable, whereas the feasible set is the corresponding Cartesian product. We discuss some versions of the partial linearization method, which can be applied to these network equilibrium problems.Comment: 18 pages, 3 table
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