Levy-Student Distributions for Halos in Accelerator Beams

We describe the transverse beam distribution in particle accelerators within the controlled, stochastic dynamical scheme of the Stochastic Mechanics (SM) which produces time reversal invariant diffusion processes. This leads to a linearized theory summarized in a Shchr\"odinger--like (\Sl) equation. The space charge effects have been introduced in a recent paper~\cite{prstab} by coupling this \Sl equation with the Maxwell equations. We analyze the space charge effects to understand how the dynamics produces the actual beam distributions, and in particular we show how the stationary, self--consistent solutions are related to the (external, and space--charge) potentials both when we suppose that the external field is harmonic (\emph{constant focusing}), and when we \emph{a priori} prescribe the shape of the stationary solution. We then proceed to discuss a few new ideas~\cite{epac04} by introducing the generalized Student distributions, namely non--Gaussian, L\'evy \emph{infinitely divisible} (but not \emph{stable}) distributions. We will discuss this idea from two different standpoints: (a) first by supposing that the stationary distribution of our (Wiener powered) SM model is a Student distribution; (b) by supposing that our model is based on a (non--Gaussian) L\'evy process whose increments are Student distributed. We show that in the case (a) the longer tails of the power decay of the Student laws, and in the case (b) the discontinuities of the L\'evy--Student process can well account for the rare escape of particles from the beam core, and hence for the formation of a halo in intense beams.Comment: revtex4, 18 pages, 12 figure

Statistical Dynamics of Religions and Adherents

Religiosity is one of the most important sociological aspects of populations. All religions may evolve in their beliefs and adapt to the society developments. A religion is a social variable, like a language or wealth, to be studied like any other organizational parameter. Several questions can be raised, as considered in this study: e.g. (i) from a ``macroscopic'' point of view : How many religions exist at a given time? (ii) from a ``microscopic'' view point: How many adherents belong to one religion? Does the number of adherents increase or not, and how? No need to say that if quantitative answers and mathematical laws are found, agent based models can be imagined to describe such non-equilibrium processes. It is found that empirical laws can be deduced and related to preferential attachment processes, like on evolving network; we propose two different algorithmic models reproducing as well the data. Moreover, a population growth-death equation is shown to be a plausible modeling of evolution dynamics in a continuous time framework. Differences with language dynamic competition is emphasized.Comment: submitted to EP

L\'evy-Schr\"odinger wave packets

We analyze the time--dependent solutions of the pseudo--differential L\'evy--Schr\"odinger wave equation in the free case, and we compare them with the associated L\'evy processes. We list the principal laws used to describe the time evolutions of both the L\'evy process densities, and the L\'evy--Schr\"odinger wave packets. To have self--adjoint generators and unitary evolutions we will consider only absolutely continuous, infinitely divisible L\'evy noises with laws symmetric under change of sign of the independent variable. We then show several examples of the characteristic behavior of the L\'evy--Schr\"odinger wave packets, and in particular of the bi-modality arising in their evolutions: a feature at variance with the typical diffusive uni--modality of both the L\'evy process densities, and the usual Schr\"odinger wave functions.Comment: 41 pages, 13 figures; paper substantially shortened, while keeping intact examples and results; changed format from "report" to "article"; eliminated Appendices B, C, F (old names); shifted Chapters 4 and 5 (old numbers) from text to Appendices C, D (new names); introduced connection between Relativistic q.m. laws and Generalized Hyperbolic law

Stochastic collective dynamics of charged--particle beams in the stability regime

We introduce a description of the collective transverse dynamics of charged (proton) beams in the stability regime by suitable classical stochastic fluctuations. In this scheme, the collective beam dynamics is described by time--reversal invariant diffusion processes deduced by stochastic variational principles (Nelson processes). By general arguments, we show that the diffusion coefficient, expressed in units of length, is given by $\lambda_c\sqrt{N}$, where $N$ is the number of particles in the beam and $\lambda_c$ the Compton wavelength of a single constituent. This diffusion coefficient represents an effective unit of beam emittance. The hydrodynamic equations of the stochastic dynamics can be easily recast in the form of a Schr\"odinger equation, with the unit of emittance replacing the Planck action constant. This fact provides a natural connection to the so--called ``quantum--like approaches'' to beam dynamics. The transition probabilities associated to Nelson processes can be exploited to model evolutions suitable to control the transverse beam dynamics. In particular we show how to control, in the quadrupole approximation to the beam--field interaction, both the focusing and the transverse oscillations of the beam, either together or independently.Comment: 15 pages, 9 figure

Price leadership and volatility linkages between oil and renewable energy firms during the covid-19 pandemic

The COVID-19 pandemic is shaving a strong influence in all areas of society, like wealth, economy, travel, lifestyle habits, and, amongst many others, financial and energy markets. The influence in standard energies, like crude oil, and renewable energies markets has been twofold: from one side, the predictability of volatility has strongly decreased; secondly, the linkages of the price time series have been modified. In this paper, by using DCC-GARCH and Price Leadership Share method-ology, we can investigate the changes in the influences between standard energies and renewable energies markets by analyzing one-minute time series of West Texas Intermediate crude oil futures contract (WTI), the Brent crude oil futures contract (BRENT), the STOXX Europe 600 oil & gas index (SXEV), and the European renewable energy index (ERIX). Our results confirm volatility spillover between the time series. However, when assessing the accuracy of the predictability of the DCC-GARCH model, the results show that the model fails its prediction in the period of higher instability. Besides, we found that price leadership has been strongly influenced by the virus spreading stages. These results have been obtained by dividing the period between September 2019 and January 2021 into 6 subperiods according to the pandemic stages

Mass spectrum from stochastic Levy-Schroedinger relativistic equations: possible qualitative predictions in QCD

Starting from the relation between the kinetic energy of a free Levy-Schroedinger particle and the logarithmic characteristic of the underlying stochastic process, we show that it is possible to get a precise relation between renormalizable field theories and a specific Levy process. This subsequently leads to a particular cut-off in the perturbative diagrams and can produce a phenomenological mass spectrum that allows an interpretation of quarks and leptons distributed in the three families of the standard model.Comment: 8 pages, no figures. arXiv admin note: substantial text overlap with arXiv:1008.425

Lexical evolution rates by automated stability measure

Phylogenetic trees can be reconstructed from the matrix which contains the distances between all pairs of languages in a family. Recently, we proposed a new method which uses normalized Levenshtein distances among words with same meaning and averages on all the items of a given list. Decisions about the number of items in the input lists for language comparison have been debated since the beginning of glottochronology. The point is that words associated to some of the meanings have a rapid lexical evolution. Therefore, a large vocabulary comparison is only apparently more accurate then a smaller one since many of the words do not carry any useful information. In principle, one should find the optimal length of the input lists studying the stability of the different items. In this paper we tackle the problem with an automated methodology only based on our normalized Levenshtein distance. With this approach, the program of an automated reconstruction of languages relationships is completed

On the Effect of Channel Knowledge in Underwater Acoustic Communications: Estimation, Prediction and Protocol

Underwater acoustic communications are limited by the following channel impairments: time variability, narrow bandwidth, multipath, frequency selective fading and the Doppler effect. Orthogonal Frequency Division Modulation (OFDM) is recognized as an effective solution to such impairments, especially when optimally designed according to the propagation conditions. On the other hand, OFDM implementation requires accurate channel knowledge atboth transmitter and receiver sides. Long propagation delay may lead to outdated channel information. In this work, we present an adaptive OFDM scheme where channel state information is predicted through a Kalman-like filter so as to optimize communication parameters, including the cyclic prefix length. This mechanism aims to mitigate the variability of channel delay spread. This is cast in a protocol where channel estimation/prediction are jointly considered, so as to allow efficiency. The performance obtained through extensive simulations using real channels and interference show the effectiveness of the proposed scheme, both in terms of rate and reliability, at the expense of an increasing complexity. However, this solution is significantly preferable to the conventional mechanism, where channel estimation is performed only at the receiver, with channel coefficients sent back to the transmit node by means of frequent overhead signaling

A multivariate high-order markov model for the income estimation of a wind farm

The energy produced by a wind farm in a given location and its associated income depends both on the wind characteristics in that location—i.e., speed and direction—and the dynamics of the electricity spot price. Because of the evidence of cross-correlations between wind speed, direction and price series and their lagged series, we aim to assess the income of a hypothetical wind farm located in central Italy when all interactions are considered. To model these cross and auto-correlations efficiently, we apply a high-order multivariate Markov model which includes dependencies from each time series and from a certain level of past values. Besides this, we used the Raftery Mixture Transition Distribution model (MTD) to reduce the number of parameters to get a more parsimonious model. Using data from the MERRA-2 project and from the electricity market in Italy, we estimate the model parameters and validate them through a Monte Carlo simulation. The results show that the simulated income faithfully reproduces the empirical income and that the multivariate model also closely reproduces the cross-correlations between the variables. Therefore, the model can be used to predict the income generated by a wind farm

Blind fractionally spaced channel equalization for shallow water PPM digital communications links

Underwater acoustic digital communications suffer from inter-symbol interference deriving from signal distortions caused by the channel propagation. Facing such kind of impairment becomes particularly challenging when dealing with shallow water scenarios characterized by short channel coherence time and large delay spread caused by time-varying multipath effects. Channel equalization operated on the received signal represents a crucial issue in order to mitigate the effect of inter-symbol interference and improve the link reliability. In this direction, this contribution presents a preliminary performance analysis of acoustic digital links adopting pulse position modulation in severe multipath scenarios. First, we show how the spectral redundancy offered by pulse position modulated signals can be fruitfully exploited when using fractional sampling at the receiver side, which is an interesting approach rarely addressed by the current literature. In this context, a novel blind equalization scheme is devised. Specifically, the equalizer is blindly designed according to a suitably modified Bussgang scheme in which the zero-memory nonlinearity is replaced by a M-memory nonlinearity, M being the pulse position modulation order. Numerical results not only confirm the feasibility of the technique described here, but also assess the quality of its performance. An extension to a very interesting complex case is also provided