Radiative Corrections to Chargino Production in Electron-Positron Collisions

The results of a complete one-loop calculation for the production of chargino pairs in electron-positron collisions, including the option of polarized beams, are presented. The calculation has been performed in the on-shell renormalization scheme. Applications to the integrated cross section, to the forward-backward asymmetry for unpolarized beams, and to the left-right asymmetry show that the higher-order effects have a sizeable influence on the theoretical predictions and therefore should be properly taken into account for detailed studies in the MSSM.Comment: 12 pages, including 5 figure

Long range action in networks of chaotic elements

We show that under certain simple assumptions on the topology (structure) of networks of strongly interacting chaotic elements a phenomenon of long range action takes place, namely that the asymptotic (as time goes to infinity) dynamics of an arbitrary large network is completely determined by its boundary conditions. This phenomenon takes place under very mild and robust assumptions on local dynamics with short range interactions. However, we show that it is unstable with respect to arbitrarily weak local random perturbations.Comment: 15 page

The Clinton Legacy for America's Poor

This paper examines the impact of Clinton era social policy changes on the poor. It explores shifts in incentives, behavior, and incomes and discusses the role Clinton did or did not play in influencing the policy mix and the nature of the political debate surrounding poverty. Policy changes included a radical shift in welfare policy, a sizable expansion in supports for low income workers with children, new child support enforcement measures, more restricted support for immigrants, and altered housing policies. Partly as a result of these policies, but also in part due to the strong economy, welfare use plummeted, work rose dramatically among single parents, and poverty was reduced. At the same time, there are indications that some families are doing worse than before and that some working families are not getting health and food benefits to which they are entitled. Significant questions remain about what will happen to poor families in the next recession.

Stochastic stability versus localization in chaotic dynamical systems

We prove stochastic stability of chaotic maps for a general class of Markov random perturbations (including singular ones) satisfying some kind of mixing conditions. One of the consequences of this statement is the proof of Ulam's conjecture about the approximation of the dynamics of a chaotic system by a finite state Markov chain. Conditions under which the localization phenomenon (i.e. stabilization of singular invariant measures) takes place are also considered. Our main tools are the so called bounded variation approach combined with the ergodic theorem of Ionescu-Tulcea and Marinescu, and a random walk argument that we apply to prove the absence of ``traps'' under the action of random perturbations.Comment: 27 pages, LaTe

Secure short-term load forecasting for smart grids with transformer-based federated learning

Electricity load forecasting is an essential task within smart grids to assist demand and supply balance. While advanced deep learning models require large amounts of high-resolution data for accurate short-term load predictions, fine-grained load profiles can expose users\u27 electricity consumption behaviors, which raises privacy and security concerns. One solution to improve data privacy is federated learning, where models are trained locally on private data, and only the trained model parameters are merged and updated on a global server. Therefore, this paper presents a novel transformer-based deep learning approach with federated learning for short-term electricity load prediction. To evaluate our results, we benchmark our federated learning architecture against central and local learning and compare the performance of our model to long short-term memory models and convolutional neural networks. Our simulations are based on a dataset from a German university campus and show that transformer-based forecasting is a promising alternative to state-of-the-art models within federated learning

Hysteresis phenomenon in deterministic traffic flows

We study phase transitions of a system of particles on the one-dimensional integer lattice moving with constant acceleration, with a collision law respecting slower particles. This simple deterministic ``particle-hopping'' traffic flow model being a straightforward generalization to the well known Nagel-Schreckenberg model covers also a more recent slow-to-start model as a special case. The model has two distinct ergodic (unmixed) phases with two critical values. When traffic density is below the lowest critical value, the steady state of the model corresponds to the ``free-flowing'' (or ``gaseous'') phase. When the density exceeds the second critical value the model produces large, persistent, well-defined traffic jams, which correspond to the ``jammed'' (or ``liquid'') phase. Between the two critical values each of these phases may take place, which can be interpreted as an ``overcooled gas'' phase when a small perturbation can change drastically gas into liquid. Mathematical analysis is accomplished in part by the exact derivation of the life-time of individual traffic jams for a given configuration of particles.Comment: 22 pages, 6 figures, corrected and improved version, to appear in the Journal of Statistical Physic