Two-Dimensional Higher-Derivative Supergravity and a New Mechanism for Supersymmetry Breaking

We discuss the general form of quadratic (1,1) supergravity in two dimensions, and show that this theory is equivalent to two scalar supermultiplets coupled to non-trivial supergravity. It is demonstrated that the theory possesses stable vacua with vanishing cosmological constant which spontaneously break supersymmetry.Comment: 22 pages, LaTeX2e and AMS-LaTeX 1.

Four-Dimensional Higher-Derivative Supergravity and Spontaneous Supersymmetry Breaking

We construct two classes of higher-derivative supergravity theories generalizing Einstein supergravity. We explore their dynamical content as well as their vacuum structure. The first class is found to be equivalent to Einstein supergravity coupled to a single chiral superfield. It has a unique stable vacuum solution except in a special case, when it becomes identical to a simple no-scale theory. The second class is found to be equivalent to Einstein supergravity coupled to two chiral superfields and has a richer vacuum structure. It is demonstrated that theories of the second class can possess a stable vacuum with vanishing cosmological constant that spontaneously breaks supersymmetry. We present an explicit example of this phenomenon and compare the result with the Polonyi model.Comment: 26 pages, LaTeX2e and AMS-LaTeX 1.2, 1 eps figur

Higher-Derivative Gravitation in Bosonic and Superstring Theories

A discussion of the number of degrees of freedom, and their dynamical properties, in higher-derivative gravitational theories is presented. The complete non-linear sigma model for these degrees of freedom is exhibited using the method of auxiliary fields. As a by-product we present a consistent non-linear coupling of a spin-2 tensor to gravitation. It is shown that non-vanishing $(C_{\mu\nu\alpha\beta})^{2}$ terms arise in $N=1$, $D=4$ superstring Lagrangians due to one-loop radiative corrections with light field internal lines.Comment: 8 pages, LaTeX2e and AMS-LaTeX 1.2, Talk presented at SUSY'95, Ecole Polytechnique in Palaiseau, Palaiseau, France, May 15-19, 199

Soft Supersymmetry Breaking Induced by Higher-Derivative Supergravitation in the Electroweak Standard Model

We show how spontaneous supersymmetry breaking in the vacuum state of higher-derivative supergravity is transmitted, as explicit soft supersymmetry-breaking terms, to the effective Lagrangian of the standard electroweak model. The general structure of the soft supersymmetry breaking terms is presented and a new scenario for understanding the gauge hierarchy problem, based on the functional form of these terms, is discussed.Comment: LaTeX2e with AMS-LaTeX 1.2, 13 page

Non-Trivial Vacua in Higher-Derivative Gravitation

A discussion of an extended class of higher-derivative classical theories of gravity is presented. A procedure is given for exhibiting the new propagating degrees of freedom, at the full non-linear level, by transforming the higher-derivative action to a canonical second-order form. For general fourth-order theories, described by actions which are general functions of the scalar curvature, the Ricci tensor and the full Riemann tensor, it is shown that the higher-derivative theories may have multiple stable vacua. The vacua are shown to be, in general, non-trivial, corresponding to deSitter or anti-deSitter solutions of the original theory. It is also shown that around any vacuum the elementary excitations remain the massless graviton, a massive scalar field and a massive ghost-like spin-two field. The analysis is extended to actions which are arbitrary functions of terms of the form $\nabla^{2k}R$, and it is shown that such theories also have a non-trivial vacuum structure.Comment: 25 pages, LaTeX2e with AMS-LaTeX 1.2, 7 eps figure

Vector-Tensor multiplet in N=2 superspace with central charge

We use the four-dimensional N=2 central charge superspace to give a geometrical construction of the Abelian vector-tensor multiplet consisting, under N=1 supersymmetry, of one vector and one linear multiplet. We derive the component field supersymmetry and central charge transformations, and show that there is a super-Lagrangian, the higher components of which are all total derivatives, allowing us to construct superfield and component actions.Comment: LaTeX2e with AMS-LaTeX, 12 page

Double-Staged Syndrome Coding Scheme for Improving Information Transmission Security over the Wiretap Channel

This paper presents a study of a syndrome coding scheme for different binary linear error correcting codes that refer to the code families such as BCH, BKLC, Golay, and Hamming. The study is implemented on Wyner’s wiretap channel model when the main channel is error-free and the eavesdropper channel is a binary symmetric channel with crossover error probability (0 < Pe ≤ 0.5) to show the security performance of error correcting codes while used in the single-staged syndrome coding scheme in terms of equivocation rate. Generally, these codes are not designed for secure information transmission, and they have low equivocation rates when they are used in the syndrome coding scheme. Therefore, to improve the transmission security when using these codes, a modified encoder which consists of a double-staged syndrome coding scheme, is proposed. Two models are implemented in this paper: the first model utilizes one encoding stage of the conventional syndrome coding scheme. In contrast, the second model utilizes two encoding stages of the syndrome coding scheme to improve the results obtained from the first model. The C++ programming language, in conjunction with the NTL library, is used for obtaining simulation results for the implemented models. The equivocation rate results from the second model were compared to both the results of the first model and of the unsecured transmission (transmission of data without encryption). The comparison revealed that the security performance of the second model is better than the first model and the insecure system, as the equivocation for all the simulated codes over the proposed model reaches at least %97 at the Pe = 0.1.

COVID-19 Prognostic Models: A Pro-con Debate for Machine Learning vs. Traditional Statistics.

The SARS-CoV-2 virus, which causes the COVID-19 pandemic, has had an unprecedented impact on healthcare requiring multidisciplinary innovation and novel thinking to minimize impact and improve outcomes. Wide-ranging disciplines have collaborated including diverse clinicians (radiology, microbiology, and critical care), who are working increasingly closely with data-science. This has been leveraged through the democratization of data-science with the increasing availability of easy to access open datasets, tutorials, programming languages, and hardware which makes it significantly easier to create mathematical models. To address the COVID-19 pandemic, such data-science has enabled modeling of the impact of the virus on the population and individuals for diagnostic, prognostic, and epidemiological ends. This has led to two large systematic reviews on this topic that have highlighted the two different ways in which this feat has been attempted: one using classical statistics and the other using more novel machine learning techniques. In this review, we debate the relative strengths and weaknesses of each method toward the specific task of predicting COVID-19 outcomes