New Dimensions at a Millimeter to a Fermi and Superstrings at a TeV

Recently, a new framework for solving the hierarchy problem has been proposed which does not rely on low energy supersymmetry or technicolor. The gravitational and gauge interactions unite at the electroweak scale, and the observed weakness of gravity at long distances is due the existence of large new spatial dimensions. In this letter, we show that this framework can be embedded in string theory. These models have a perturbative description in the context of type I string theory. The gravitational sector consists of closed strings propagating in the higher-dimensional bulk, while ordinary matter consists of open strings living on D3-branes. This scenario raises the exciting possibility that the LHC and NLC will experimentally study both ordinary aspects of string physics such as the production of narrow Regge-excitations of all standard model particles, as well more exotic phenomena involving strong gravity such as the production of black holes. The new dimensions can be probed by events with large missing energy carried off by gravitons escaping into the bulk. We finally discuss some important issues of model building, such as proton stability, gauge coupling unification and supersymmetry breaking.Comment: 12 pages, late

Missing Doublet Multiplet as the Origin of the Doublet-Triplet Splitting in SUSY SU(6)

In a $SU(6)$ gauge theory we found the irreducible representation (175-plet) which does not contain the Higgs doublet. Using this representation we construct two SUSY $SU(6)$ models in which the doublet-triplet splitting occurs naturally, without fine tuning. The crucial role is played by the ``custodial" global $SU(2)_H$ in combination with discrete or continuous $R$ symmetries.Comment: 11 pages, LaTe

Quantum Restoration of the U(1)_Y Symmetry in Dynamically Broken SUSY-GUT's

We propose a supersymmetric hypercolor SU(3)_H gauge theory interacting strongly at the grand unification scale, in which the hyperquark condensation breaks SU(5)_GUT down to SU(3)_C x SU(2)_L without unbroken U(1)_Y at the classical level. However, we show that the broken U(1)_Y symmetry is restored by quantum mechanical effects and hence there remains the standard-model gauge symmetry at the electroweak scale. The dynamics of the strong interactions also produces naturally a pair of massless Higgs doublets. In addition to these Higgs doublets, we have a pair of massless singlets which contributes to the renormalization-group equations of gauge coupling constants and hence affects the GUT unification. We discuss a simple solution to this problem.Comment: 12 pages, LaTeX, 1 Postscript figur

Discovering New Physics in the Decays of Black Holes

If the scale of quantum gravity is near a TeV, the LHC will be producing one black hole (BH) about every second, thus qualifying as a BH factory. With the Hawking temperature of a few hundred GeV, these rapidly evaporating BHs may produce new, undiscovered particles with masses ~100 GeV. The probability of producing a heavy particle in the decay depends on its mass only weakly, in contrast with the exponentially suppressed direct production. Furthemore, BH decays with at least one prompt charged lepton or photon correspond to the final states with low background. Using the Higgs boson as an example, we show that it may be found at the LHC on the first day of its operation, even with incomplete detectors.Comment: 4 pages, 3 figure

Comment on ``Neutrino masses and mixing angles in a predictive theory of fermion masses''

In the extension of the Dimopoulos--Hall--Raby model of the fermion mass matrices to the neutrino sector, there is an entry in the up-quark and neutrino Dirac mass matrices which can be assumed to arise from the Yukawa coupling of a {\bf 120}, instead of a {\bf 10} or a {\bf 126}, of SO(10). Although this assumption leads to an extra undetermined complex parameter in the model, the resulting lepton mixing matrix exhibits the remarkable feature that the $\nu_{\tau}$ does not mix with the other two neutrinos. Making a reasonable assumption about the extra parameter, we are able to fit the large-mixing-angle MSW solution of the solar-neutrino problem, and we obtain $m_{\nu_{\tau}} \sim 10$ eV, the right mass range to close the Universe. Other possibilities for explaining the solar-neutrino deficit are also discussed.Comment: standard LATEX, 6 pages, 2 figures available from the authors, report No. CMU-HEP93-20 and DOE-ER/40682-4

Soft Masses in Theories with Supersymmetry Breaking by TeV-Compactification

We study the sparticle spectroscopy and electroweak breaking of theories where supersymmetry is broken by compactification (Scherk-Schwarz mechanism) at a TeV. The evolution of the soft terms above the compactification scale and the resulting sparticle spectrum are very different from those of the usual MSSM and gauge mediated theories. This is traced to the softness of the Scherk-Schwarz mechanism which leads to scalar sparticle masses that are only logarithmically sensitive to the cutoff starting at two loops. As a result, squarks and sleptons are naturally an order of magnitude lighter than gauginos. In addition, the mechanism is very predictive and the sparticle spectrum depends on just two new parameters. A significant advantage of this mechanism relative to gauge mediation is that a Higgsino mass $\mu\sim M_susy$ is automatically generated when supersymmetry is broken. Our analysis applies equally well to theories where the cutoff is near a TeV or $M_{Pl}$ or some intermediate scale. We also use these observations to show how we may obtain compactification radii which are hierarchically larger than the fundamental cutoff scale.Comment: 26 pages, 1 figure, Late

Right-handed-neutrino Majorana mass at the SUSY GUT scale and the solution of the solar-neutrino problem

In the SUSY GUT scenario, it is natural to assume the right-handed-neutrino Majorana-mass scale to be $10^{16}$ GeV. This will in principle lead, by the seesaw mechanism, to a $\nu_{\tau}$ mass of order $m_t^2 / (10^{16}\, {\rm GeV}) \sim 3 \times 10^{-3}\, {\rm eV}$. This suggests that the solution of the solar-neutrino puzzle should be either the MSW effect in $\nu_e$--$\nu_{\tau}$ oscillations, with $m_{\nu_{\tau}}^2 \sim 10^{-5}\, {\rm eV}^2$, or long-wavelength $\nu_e$--$\nu_{\mu}$ oscillations, with $m_{\nu_{\mu}}^2 \sim 10^{-10}\, {\rm eV}^2$. These solutions require unexpectedly large mixings of $\nu_e$ with $\nu_{\tau}$ and $\nu_{\mu}$, respectively. I suggest a variation of the Dimopoulos--Hall--Raby model for the fermion mass matrices which can accomodate such large mixings.Comment: 10 pages, standard LATEX, no figures, Carnegie-Mellon University Report CMU-HEP93-27 and DOE-ER/40682-5

Modélisation de la relation pluie-débit à l'aide des réseaux de neurones artificiels

Identifier tous les processus physiques élémentaires du cycle hydrologique qui peuvent avoir lieu dans un bassin versant et attribuer à chacun d'eux une description analytique permettant la prévision conduisent à des structures complexes employant un nombre élevé de paramètres difficilement accessibles. En outre, ces processus, même simplifiés, sont généralement non linéaires. Le recours à des modèles à faible nombre de variables, capables de traiter la non-linéarité, s'avère nécessaire.C'est dans cette optique que nous proposons une méthode de modélisation de la relation pluie et débit basée sur l'utilisation de réseaux neuronaux. Les performances de ces derniers dans la modélisation non linéaire ont été déjà prouvées dans plusieurs domaines scientifiques (biologie, géologie, chimie, physique). Dans ce travail, nous utilisons l'algorithme de la rétropropagation des erreurs avec un réseau à 3 couches de neurones. La fonction de transfert appliquée est de type sigmoïde. Pour prédire le débit à un moment donné, on présente à l'entrée du réseau des valeurs de pluies et de débits observés à des instants précédents. La structure du réseau est optimisée pour obtenir une bonne capacité prévisionnelle sur des données n'ayant pas participé au calage.L'application du réseau à des données pluviométriques et débimétriques du bassin de l'oued Beth permet d'obtenir de bonnes prévisions d'un ou plusieurs pas de temps, aussi bien journalières qu'hebdomadaires. Pour les données n'ayant pas participé au calage, les coefficients de corrélation entre les valeurs observées et les valeurs estimées par les différents modèles sont élevés. Ils varient de 0.72 à 0.91 pour les coefficients de corrélation de Pearson et de 0.73 à 0.95 pour les coefficients de Spearman.Identification of the elementary processes of the hydrological cycle in a drainage basin, and the comprehensive description of each of them, lead to hydrological models with a complex structure including a high number of relatively inaccessible parameters. Moreover these processes, even when simplified, are generally non-linear. Using models with a smaller number of parameters, in order to cope with non-linearity, is therefore necessary.In this perspective, we propose an artificial neural network for rainfall-runoff modeling. Performances of this method in non-linear modeling have been already demonstrated in several scientific fields (biology, geology, chemistry, physics). In the present work, we use the error back-propagation algorithm with a three-layer neural network. The transfer functions belong to the sigmoidal type at each layer. To predict the runoff at a given moment, the input variables are the rainfall and the runoff values observed for the previous time period. The structure of the network (number of hidden nodes, learning coefficient and momentum values) is optimized to guarantee a good prediction of the runoff, using a set of test data (validation set) not used in the training phase.Data compiled in our model are a ten year set of rainfall-runoff values collected by the Rabat hydraulic administration (September 1983 to April 1993) in the Beth Wadi catchment. In this study, we develop two types of models according to two different time steps (daily and weekly). The data are subdivided into two sets: a first set to train the model (training set) and a second set to test the model (validation set). For the daily timestep model, we used data of the last two years: April 1991 to April 1993. The initial 365 data (April 1991- April 1992) constitute the training set and the 365 remaining data constitute the validation set. For the weekly data (Monday to Sunday averages), we have 502 pairs of values. We worked by preserving the last 120 values as the validation set and trained the neural network with the remaining data, i.e. 382 pairs of values of weekly rainfall-runoff.Three types of estimation have been carried out:1. at instant prediction: prediction of runoff at time t taking into account rainfall values at time t, as well as runoff and rainfall values at preceding times (until t-1); 2. one step ahead prediction: prediction of runoff at time t from rainfall and runoff values at the preceding times (until t-1); 3. multistep prediction: prediction of runoff values for a period from t-jh until t, given that values of the runoff for the period 1 to t-jh-1 and values of the rainfall at times 1 to t are available (h is the timestep). The step time is daily for the at instant prediction and weekly for one step ahead and multistep predictions. The choice of input variables is determined by autocorrelation function (ACF) and partial autocorrelation function (PACF) analyses on runoff values, and cross-correlation function (CCF) analysis between rainfall and runoff values. For the at instant prediction, the input vector is composed by runoff values of the four days preceding day t, and rainfall values for the three last preceding days as well as its value on day t. For the one step ahead prediction, the input vector is composed of runoff values of the five weeks preceding week t, and rainfall values for the three preceding weeks (without considering the rainfall at time t). Finally, for the multistep prediction, the input vector is the same as for the one step ahead prediction but rainfall values include time t. The runoff values for the week t-jh+1, as well as for the following weeks, are computed by feed backing to the input vector the runoff value predicted for the preceding week.The rainfall-runoff models allow a good estimation for one or several timesteps, daily as well as weekly. In the validation set, correlation coefficients between observed and estimated values are high. In the at instant prediction, we obtain the Pearson correlation coefficient R=0.772 and the Spearman correlation coefficient CR=0.958. The weak value of R as compared to CR is explained by a few extremely high values of error of prediction. In the one step ahead prediction (R=0.887 and CR=0.782) and multistep prediction (R=0.908 and CR=0.727), the R coefficients are higher that CR. This confirms that predicted values are in good agreement with the peaks of observed values (absence of large exceptional errors). In all cases, the results obtained are better than those obtained with linear methods. The neural network models can thus be recommended for time series studies in environmental sciences

EC8-based seismic design and assessment of self-centering post-tensioned steel frames with viscous dampers

This paper focuses on seismic design and assessment of steel self-centering moment-resisting frames (SC-MRFs) with viscous dampers within the framework of Eurocode 8 (EC8). Performance levels are defined with respect to drifts, residual drifts and limit states in the post-tensioned (PT) connections. A preliminary pushover analysis is conducted at the early phase of the design process to estimate rotations and axial forces in post-tensioned (PT) connections instead of using approximate formulae. Different designs of an SC-MRF with viscous dampers are considered to investigate all possible scenarios, i.e. use of dampers to achieve drifts significantly lower than the EC8 drift limit; to significantly reduce steel weight without exceeding the EC8 drift limit; or to reduce steel weight and achieve drifts lower than the EC8 drift limit. Nonlinear dynamic analyses using models capable of simulating all structural limit states up to collapse confirm the minimal-damage performance of the SC-MRFs. It is shown that the use of the preliminary pushover analysis makes the design procedure very accurate in predicting structural and non-structural limit states. Supplemental damping along with strict design criteria for the post-tensioned connections are found to significantly improve the seismic performance of the SC-MRFs. Moreover, the paper shows that SC-MRFs with viscous dampers have superior collapse resistance compared to conventional steel MRFs even when the SC-MRF is significantly lighter than the conventional MRF

Stabilization of Sub-Millimeter Dimensions: The New Guise of the Hierarchy Problem

A new framework for solving the hierarchy problem was recently proposed which does not rely on low energy supersymmetry or technicolor. The fundamental Planck mass is at a \tev and the observed weakness of gravity at long distances is due the existence of new sub-millimeter spatial dimensions. In this picture the standard model fields are localized to a $(3+1)$-dimensional wall or ``3-brane''. The hierarchy problem becomes isomorphic to the problem of the largeness of the extra dimensions. This is in turn inextricably linked to the cosmological constant problem, suggesting the possibility of a common solution. The radii of the extra dimensions must be prevented from both expanding to too great a size, and collapsing to the fundamental Planck length \tev^{-1}. In this paper we propose a number of mechanisms addressing this question. We argue that a positive bulk cosmological constant $\bar\Lambda$ can stabilize the internal manifold against expansion, and that the value of $\bar\Lambda$ is not unstable to radiative corrections provided that the supersymmetries of string theory are broken by dynamics on our 3-brane. We further argue that the extra dimensions can be stabilized against collapse in a phenomenologically successful way by either of two methods: 1) Large, topologically conserved quantum numbers associated with higher-form bulk U(1) gauge fields, such as the naturally occurring Ramond-Ramond gauge fields, or the winding number of bulk scalar fields. 2) The brane-lattice-crystallization of a large number of 3-branes in the bulk. These mechanisms are consistent with theoretical, laboratory, and cosmological considerations such as the absence of large time variations in Newton's constant during and after primordial nucleosynthesis, and millimeter-scale tests of gravity.Comment: Corrected referencing to important earlier work by Sundrum, errors fixed, additional discussion on radion phenomenology, conclusions unchanged, 23 pages, LaTe