Brans-Dicke theory in the local potential approximation

We study the Brans-Dicke theory with arbitrary potential within a functional renormalization group framework. Motivated by the asymptotic safety scenario of quantum gravity and by the well-known relation between f(R) gravity and Brans-Dicke theory at the classical level, we concentrate our analysis on the fixed-point equation for the potential in four dimensions and with Brans-Dicke parameter omega equal to zero. For two different choices of gauge, we study the resulting equations by examining both local and global properties of the solutions, by means of analytical and numerical methods. As a result of our analysis we do not find any nontrivial fixed point in one gauge, but we find a continuum of fixed points in the other one. We interpret such inconsistency as a result of the restriction to omega equal to zero, and thus we suggest that it indicates a failure of the equivalence between f(R) gravity and Brans-Dicke theory at the quantum level.Comment: 34 pages, 8 figures; v2: corrected some misprints, added a new figure, four new references and some clarifying comment

One-loop renormalization in a toy model of Horava-Lifshitz gravity

We present a one loop calculation in the context of Horava-Lifshitz gravity. Due to the complexity of the calculation in the full theory we focus here on the study of a toy model, namely the conformal reduction of the z=2 projectable theory in 2+1 dimensions. For this value of the dimension there are no gravitons, hence the conformal mode is the only physical degree of freedom, and thus we expect our toy model to lead to qualitatively correct answers regarding the perturbative renormalization of the full theory. We find that Newton's constant (dimensionless in Horava-Lifshitz gravity) is asymptotically free. However, the DeWitt supermetric approaches its Weyl invariant form with the same speed and the effective interaction coupling remains constant along the flow. In other words, the would-be asymptotic freedom associated to the running Newton's constant is exactly balanced by the strong coupling of the scalar mode as the Weyl invariant limit is approached. We conclude that in such model the UV limit is singular at one loop order, and we argue that a similar phenomenon can be expected in the full theory, even in higher dimensions.Comment: 18 pages. v2: corrected some misprints, added 3 references, some clarifying comments and a new appendi

Visible quantum plasmonics from metallic nanodimers

We report theoretical evidence that bulk nonlinear materials weakly interacting with highly localized plasmonic modes in ultra-sub-wavelength metallic nanostructures can lead to nonlinear effects at the single plasmon level in the visible range. In particular, the two-plasmon interaction energy in such systems is numerically estimated to be comparable with the typical plasmon linewidths. Localized surface plasmons are thus predicted to exhibit a purely nonclassical behavior, which can be clearly identified by a sub-Poissonian second-order correlation in the signal scattered from the quantized plasmonic field under coherent electromagnetic excitation. We explicitly show that systems sensitive to single-plasmon scattering can be experimentally realized by combining electromagnetic confinement in the interstitial region of gold nanodimers with local infiltration or deposition of ordinary nonlinear materials. We also propose configurations that could allow to realistically detect such an effect with state-of-the-art technology, overcoming the limitations imposed by the short plasmonic lifetime

Stock market firm-level information and real economic activity

We provide evidence that changes in the equity price and volatility of individual firms (measures that approximate the definition of 'granular shock' given in Gabaix, 2010) are key to improve the predictability of aggregate business cycle fluctuations in a number of countries. Specifically, adding the return and the volatility of firm-level equity prices to aggregate financial information leads to a significant improvement in forecasting business cycle developments in four economic areas, at various horizons. Importantly, not only domestic firms but also foreign firms improve business cycle predictability for a given economic area. This is not immediately visible when one takes an unconditional standpoint (i.e. an average across the sample). However, conditioning on the business cycle position of the domestic economy, the relative importance of the two sets of firms - foreign and domestic - exhibits noticeable swings across time. Analogously, the sectoral classification of the firms that in a given month retain the highest predictive power for future IP changes also varies significantly over time as a function of the business cycle position of the domestic economy. Limited to the United States, predictive ability is found to be related to selected balance sheet items, suggesting that structural features differentiate the firms that can anticipate aggregate fluctuations from those that do not help to this aim. Beyond the purely forecasting application, this finding may enhance our understanding of the underlying origins of aggregate fluctuations. We also propose to use the cross sectional stock market information to macro-prudential aims through an economic Value at Risk. JEL Classification: C53, C58, F37, G15Business cycle forecasting, granular shock, international linkages

One or more Higgs bosons?

Now that one has been found, the search for signs of more scalars is a primary task of current and future experiments. In the motivated hypothesis that the extra Higgs bosons of the next-to-minimal supersymmetric Standard Model (NMSSM) be the lightest new particles around, we outline a possible overall strategy to search for signs of the CP-even states. This work complements Ref. arXiv:1304.3670.Comment: 14 pages, 7 figures. v2: references added, published in PR

A neural network approach to human posture classification and fall detection using RGB-D camera

In this paper, we describe a human posture classification and a falling detector module suitable for smart homes and assisted living solutions. The system uses a neural network that processes the human joints produced by a skeleton tracker using the depth streams of an RGB-D sensor. The neural network is able to recognize standing, sitting and lying postures. Using only the depth maps from the sensor, the system can work in poor light conditions and guarantees the privacy of the person. The neural network is trained with a dataset produced with the Kinect tracker, but it is also tested with a different human tracker (NiTE). In particular, the aim of this work is to analyse the behaviour of the neural network even when the position of the extracted joints is not reliable and the provided skeleton is confused. Real-time tests have been carried out covering the whole operative range of the sensor (up to 3.5 m). Experimental results have shown an overall accuracy of 98.3% using the NiTE tracker for the falling tests, with the worst accuracy of 97.5%