Probing Fuzzballs with Particles, Waves and Strings

We probe D1D5 micro-state geometries with massless particles, waves and strings. To this end, we study geodetic motion, Klein-Gordon equation and string scattering in the resulting gravitational background. Due to the reduced rotational symmetry, even in the simple case of a circular fuzzball, the system cannot be integrated elementarily. Yet, for motion in the plane of the string profile or in the orthogonal plane to it, one can compute the deflection angle or the phase shift and identify the critical impact parameter, at which even a massless probe is captured by the fuzzball if its internal momentum is properly tuned. We find agreement among the three approaches, thus giving further support to the fuzzball proposal at the dynamical level.Comment: 35 pages. Extended and improved discussions on the integrability of the geodetic equations and on the critical impact parameter

Renormalization-Group flow for the field strength in scalar self-interacting theories

We consider the Renormalization-Group coupled equations for the effective potential V(\phi) and the field strength Z(\phi) in the spontaneously broken phase as a function of the infrared cutoff momentum k. In the k \to 0 limit, the numerical solution of the coupled equations, while consistent with the expected convexity property of V(\phi), indicates a sharp peaking of Z(\phi) close to the end points of the flatness region that define the physical realization of the broken phase. This might represent further evidence in favor of the non-trivial vacuum field renormalization effect already discovered with variational methods.Comment: 10 pages, 3 Figures, version accepted for publication in Phys. Lett.

First lattice evidence for a non-trivial renormalization of the Higgs condensate

General arguments related to ``triviality'' predict that, in the broken phase of $(\lambda\Phi^4)_4$ theory, the condensate re-scales by a factor $Z_{\phi}$ different from the conventional wavefunction-renormalization factor, $Z_{prop}$. Using a lattice simulation in the Ising limit we measure $Z_{\phi}=m^2 \chi$ from the physical mass and susceptibility and $Z_{prop}$ from the residue of the shifted-field propagator. We find that the two $Z$'s differ, with the difference increasing rapidly as the continuum limit is approached. Since $Z_{\phi}$ affects the relation of to the Fermi constant it can sizeably affect the present bounds on the Higgs mass.Comment: 10 pages, 3 figures, 1 table, Latex2

An alternative heavy Higgs mass limit

After commenting on the present value of the Higgs particle mass from radiative corrections, we explore the phenomenological implications of an alternative, non-perturbative renormalization of the scalar sector where the mass of the Higgs particle does not represent a measure of observable interactions at the Higgs mass scale. In this approach the Higgs particle could be very heavy, even heavier than 1 TeV, and remain nevertheless a relatively narrow resonance.Comment: 17 pages. Version accepted for publication in Journal of Physics

A survey on tidal analysis and forecasting methods for Tsunami detection

Accurate analysis and forecasting of tidal level are very important tasks for human activities in oceanic and coastal areas. They can be crucial in catastrophic situations like occurrences of Tsunamis in order to provide a rapid alerting to the human population involved and to save lives. Conventional tidal forecasting methods are based on harmonic analysis using the least squares method to determine harmonic parameters. However, a large number of parameters and long-term measured data are required for precise tidal level predictions with harmonic analysis. Furthermore, traditional harmonic methods rely on models based on the analysis of astronomical components and they can be inadequate when the contribution of non-astronomical components, such as the weather, is significant. Other alternative approaches have been developed in the literature in order to deal with these situations and provide predictions with the desired accuracy, with respect also to the length of the available tidal record. These methods include standard high or band pass filtering techniques, although the relatively deterministic character and large amplitude of tidal signals make special techniques, like artificial neural networks and wavelets transform analysis methods, more effective. This paper is intended to provide the communities of both researchers and practitioners with a broadly applicable, up to date coverage of tidal analysis and forecasting methodologies that have proven to be successful in a variety of circumstances, and that hold particular promise for success in the future. Classical and novel methods are reviewed in a systematic and consistent way, outlining their main concepts and components, similarities and differences, advantages and disadvantages

A Fast Quasi-Conformal Mapping Preconditioner for Electromagnetic Integral Equations

Boundary Element Methods (BEMs) are efficient strategies to numerically solve electromagnetic radiation and scattering problems. Unfortunately, however, classical BEM formulations suffer from ill-conditioning when the frequency is low, or the discretization density is high. In the past, several remedies have been presented for these ill-conditioning problems including preconditioners based on Calderón identities, hierarchical bases, and current decompositions. While effective, these strategies however require ad-hoc procedures including mesh-refinements, new basis function definitions, and adapted fast methods that, if not implemented properly, can become computationally cumbersome

Precision tests with a new class of dedicated ether-drift experiments

In principle, by accepting the idea of a non-zero vacuum energy, the physical vacuum of present particle physics might represent a preferred reference frame. By treating this quantum vacuum as a relativistic medium, the non-zero energy-momentum flow expected in a moving frame should effectively behave as a small thermal gradient and could, in principle, induce a measurable anisotropy of the speed of light in a loosely bound system as a gas. We explore the phenomenological implications of this scenario by considering a new class of dedicated ether-drift experiments where arbitrary gaseous media fill the resonating optical cavities. Our predictions cover most experimental set up and should motivate precise experimental tests of these fundamental issues.Comment: Accepted for publication in Eur. Phys. Journ.

Use and effectiveness of dapagliflozin in routine clinical practice. An Italian multicenter retrospective study

In randomized controlled trials (RCTs), sodium-glucose co-transporter-2 (SGLT2) inhibitors have been shown to confer glycaemic and extra-glycaemic benefits. The DARWIN-T2D (DApagliflozin Real World evIdeNce in Type 2 Diabetes) study was a multicentre retrospective study designed to evaluate the baseline characteristics of patients receiving dapagliflozin vs those receiving selected comparators (dipeptidyl peptidase-4 inhibitors, gliclazide, or glucagon-like peptide-1 receptor agonists), and drug effectiveness in routine clinical practice. From a population of 281 217, the analysis included 17 285 patients initiating dapagliflozin or comparator glucose-lowering medications (GLMs), 6751 of whom had a follow-up examination. At baseline, participants starting dapagliflozin were younger, had a longer disease duration, higher glycated haemoglobin (HbA1c) concentration, and a more complex history of previous GLM use, but the clinical profile of patients receiving dapagliflozin changed during the study period. Dapagliflozin reduced HbA1c by 0.7%, body weight by 2.7 kg, and systolic blood pressure by 3.0 mm Hg. Effects of comparator GLMs were also within the expected range, based on RCTs. This real-world study shows an initial channelling of dapagliflozin to difficult-to-treat patients. Nonetheless, dapagliflozin provided significant benefits with regard to glucose control, body weight and blood pressure that were in line with findings from RCTs

Monitoring and modelling of soil–plant interactions: the joint use of ERT, sap flow and eddy covariance data to characterize the volume of an orange tree root zone

Abstract. Mass and energy exchanges between soil, plants and atmosphere control a number of key environmental processes involving hydrology, biota and climate. The understanding of these exchanges also play a critical role for practical purposes e.g. in precision agriculture. In this paper we present a methodology based on coupling innovative data collection and models in order to obtain quantitative estimates of the key parameters of such complex flow system. In particular we propose the use of hydro-geophysical monitoring via "time-lapse" electrical resistivity tomography (ERT) in conjunction with measurements of plant transpiration via sap flow and evapotranspiration (ET) from eddy covariance (EC). This abundance of data is fed to spatially distributed soil models in order to characterize the distribution of active roots. We conducted experiments in an orange orchard in eastern Sicily (Italy), characterized by the typical Mediterranean semi-arid climate. The subsoil dynamics, particularly influenced by irrigation and root uptake, were characterized mainly by the ERT set-up, consisting of 48 buried electrodes on 4 instrumented micro-boreholes (about 1.2 m deep) placed at the corners of a square (with about 1.3 m long sides) surrounding the orange tree, plus 24 mini-electrodes on the surface spaced 0.1 m on a square grid. During the monitoring, we collected repeated ERT and time domain reflectometry (TDR) soil moisture measurements, soil water sampling, sap flow measurements from the orange tree and EC data. We conducted a laboratory calibration of the soil electrical properties as a function of moisture content and porewater electrical conductivity. Irrigation, precipitation, sap flow and ET data are available allowing for knowledge of the system's long-term forcing conditions on the system. This information was used to calibrate a 1-D Richards' equation model representing the dynamics of the volume monitored via 3-D ERT. Information on the soil hydraulic properties was collected from laboratory and field experiments. The successful results of the calibrated modelling exercise allow for the quantification of the soil volume interested by root water uptake (RWU). This volume is much smaller (with a surface area less than 2 m2, and about 40 cm thick) than expected and assumed in the design of classical drip irrigation schemes that prove to be losing at least half of the irrigated water which is not taken up by the plants

Statistical arbitrage powered by Explainable Artificial Intelligence

Machine learning techniques have recently become the norm for detecting patterns in financial markets. However, relying solely on machine learning algorithms for decision-making can have negative consequences, especially in a critical domain such as the financial one. On the other hand, it is well-known that transforming data into actionable insights can pose a challenge even for seasoned practitioners, particularly in the financial world. Given these compelling reasons, this work proposes a machine learning approach powered by eXplainable Artificial Intelligence techniques integrated into a statistical arbitrage trading pipeline. Specifically, we propose three methods to discard irrelevant features for the prediction task. We evaluate the approaches on historical data of component stocks of the S&P500 index and aim at improving not only the prediction performance at the stock level but also overall at the stock set level. Our analysis shows that our trading strategies that include such feature selection methods improve the portfolio performances by providing predictive signals whose information content suffices and is less noisy than the one embedded in the whole feature set. By performing an in-depth risk-return analysis, we show that the proposed trading strategies powered by explainable AI outperform highly competitive trading strategies considered as baselines