Four Dimensional Supergravity from String Theory

A derivation of N=1 supergravity action from string theory is presented. Starting from a Nambu-Goto bosonic string, matter field is introduced to obtain a superstring in four dimension. The excitation quanta of this string contain graviton and the gravitino. Using the principle of equivalence, the action in curved space time are found and the sum of them is the Deser-Zumino N=1 supergravity action. The energy tensor is Lorentz invariant due to supersymmetry.Comment: 9 page

Parity Effects in Eigenvalue Correlators, Parametric and Crossover Correlators in Random Matrix Models: Application to Mesoscopic systems

This paper summarizes some work I've been doing on eigenvalue correlators of Random Matrix Models which show some interesting behaviour. First we consider matrix models with gaps in there spectrum or density of eigenvalues. The density-density correlators of these models depend on whether N, where N is the size of the matrix, takes even or odd values. The fact that this dependence persists in the large N thermodynamic limit is an unusual property and may have consequences in the study of one electron effects in mesoscopic systems. Secondly, we study the parametric and cross correlators of the Harish Chandra-Itzykson-Zuber matrix model. The analytic expressions determine how the correlators change as a parameter (e.g. the strength of a perturbation in the hamiltonian of the chaotic system or external magnetic field on a sample of material) is varied. The results are relevant for the conductance fluctuations in disordered mesoscopic systems.Comment: 12 pages, Latex, 2 Figure

Reduced-order modeling and dynamics of nonlinear acoustic waves in a combustion chamber

For understanding the fundamental properties of unsteady motions in combustion chambers, and for applications of active feedback control, reduced-order models occupy a uniquely important position. A framework exists for transforming the representation of general behavior by a set of infinite-dimensional partial differential equations to a finite set of nonlinear second-order ordinary differential equations in time. The procedure rests on an expansion of the pressure and velocity fields in modal or basis functions, followed by spatial averaging to give the set of second-order equations in time. Nonlinear gasdynamics is accounted for explicitly, but all other contributing processes require modeling. Reduced-order models of the global behavior of the chamber dynamics, most importantly of the pressure, are obtained simply by truncating the modal expansion to the desired number of terms. Central to the procedures is a criterion for deciding how many modes must be retained to give accurate results. Addressing that problem is the principal purpose of this paper. Our analysis shows that, in case of longitudinal modes, a first mode instability problem requires a minimum of four modes in the modal truncation whereas, for a second mode instability, one needs to retain at least the first eight modes. A second important problem concerns the conditions under which a linearly stable system becomes unstable to sufficiently large disturbances. Previous work has given a partial answer, suggesting that nonlinear gasdynamics alone cannot produce pulsed or 'triggered' true nonlinear instabilities; that suggestion is now theoretically established. Also, a certain form of the nonlinear energy addition by combustion processes is known to lead to stable limit cycles in a linearly stable system. A second form of nonlinear combustion dynamics with a new velocity coupling function that naturally displays a threshold character is shown here also to produce triggered limit cycle behavior

Aharonov-Bohm effect in the presence of evanescent modes

It is known that differential magnetoconductance of a normal metal loop connected to reservoirs by ideal wires is always negative when an electron travels as an evanescent modes in the loop. This is in contrast to the fact that the magnetoconductance for propagating modes is very sensitive to small changes in geometric details and the Fermi energy and moreover it can be positive as well as negative. Here we explore the role of impurities in the leads in determining the magnetoconductance of the loop. We find that the change in magnetoconductance is negative and can be made large provided the impurities do not create resonant states in the systems. This theoretical finding may play an useful role in quantum switch operations.Comment: 9 figures available on reques

Smooth flexible models of nonhomogeneous Poisson processes fit to one or more process realizations

Simulation is a technique of creating representations or models of real world systems or processes and conducting experiments to predict behavior of actual systems. Input modeling is a critical aspect of simulation modeling. Stochastic input models are used to model various aspects of the system under uncertainty including process times and interarrival times. This research focuses on input models for nonstationary arrival processes that can be represented as nonhomogeneous Poisson processes (NHPPs). In particular, a smooth flexible model for the mean-value function (or integrated rate function) of a general NHPP is estimated. To represent the mean-value function, the method utilizes a specially formulated polynomial that is constrained in least-squares estimation to be nondecreasing so the corresponding rate function is nonnegative and continuously differentiable. The degree of the polynomial is determined by applying a modified likelihood ratio test to a set of transformed arrival times resulting from a variance stabilizing transformation of the observed data. Given the degree of polynomial, final estimates of the polynomial coefficients are obtained from original arrival times using least-squares estimation. The method is extended to fit an NHPP model to multiple observed realizations of a process. In addition, the method is adapted to a multiresolution procedure that effectively models NHPPs with long term trend and cyclic behavior given multiple process realizations. An experimental performance evaluation is conducted to determine the capabilities and limitations of the NHPP fitting procedure for single and multiple realizations of test processes. The method is implemented in a Java-based programming environment along with a web interface that allows user to upload observed data, fit an NHPP, and generate realizations of the fitted NHPP for use in simulation experiments

Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery

The electrocardiogram or ECG has been in use for over 100 years and remains the most widely performed diagnostic test to characterize cardiac structure and electrical activity. We hypothesized that parallel advances in computing power, innovations in machine learning algorithms, and availability of large-scale digitized ECG data would enable extending the utility of the ECG beyond its current limitations, while at the same time preserving interpretability, which is fundamental to medical decision-making. We identified 36,186 ECGs from the UCSF database that were 1) in normal sinus rhythm and 2) would enable training of specific models for estimation of cardiac structure or function or detection of disease. We derived a novel model for ECG segmentation using convolutional neural networks (CNN) and Hidden Markov Models (HMM) and evaluated its output by comparing electrical interval estimates to 141,864 measurements from the clinical workflow. We built a 725-element patient-level ECG profile using downsampled segmentation data and trained machine learning models to estimate left ventricular mass, left atrial volume, mitral annulus e' and to detect and track four diseases: pulmonary arterial hypertension (PAH), hypertrophic cardiomyopathy (HCM), cardiac amyloid (CA), and mitral valve prolapse (MVP). CNN-HMM derived ECG segmentation agreed with clinical estimates, with median absolute deviations (MAD) as a fraction of observed value of 0.6% for heart rate and 4% for QT interval. Patient-level ECG profiles enabled quantitative estimates of left ventricular and mitral annulus e' velocity with good discrimination in binary classification models of left ventricular hypertrophy and diastolic function. Models for disease detection ranged from AUROC of 0.94 to 0.77 for MVP. Top-ranked variables for all models included known ECG characteristics along with novel predictors of these traits/diseases.Comment: 13 pages, 6 figures, 1 Table + Supplemen

Submillimeter sources for radiometry using high power Indium Phosphide Gunn diode oscillators

A study aimed at developing high frequency millimeter wave and submillimeter wave local oscillator sources in the 60-600 GHz range was conducted. Sources involved both fundamental and harmonic-extraction type Indium Phosphide Gunn diode oscillators as well as varactor multipliers. In particular, a high power balanced-doubler using varactor diodes was developed for 166 GHz. It is capable of handling 100 mW input power, and typically produced 25 mW output power. A high frequency tripler operating at 500 GHz output frequency was also developed and cascaded with the balanced-doubler. A dual-diode InP Gunn diode combiner was used to pump this cascaded multiplier to produce on the order of 0.5 mW at 500 GHz. In addition, considerable development and characterization work on InP Gunn diode oscillators was carried out. Design data and operating characteristics were documented for a very wide range of oscillators. The reliability of InP devices was examined, and packaging techniques to enhance the performance were analyzed. A theoretical study of a new class of high power multipliers was conducted for future applications. The sources developed here find many commercial applications for radio astronomy and remote sensing

Derivation of Design Wind and Wave Parameters Considering Climate Change

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv