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Related papers: Connecting String Theory and Phenomenology

200 papers

Recently, a number of authors have challenged the conventional assumption that the string scale, Planck mass, and unification scale are roughly comparable. It has been suggested that the string scale could be as low as a TeV. The greatest…

High Energy Physics - Theory · Physics 2008-11-26 Michael Dine

In an effort to promote communication between the formal and phenomenological branches of the high-energy theory community, we provide a description of some important issues in supersymmetric and string phenomenology. We describe each…

High Energy Physics - Theory · Physics 2016-09-06 Pierre Binetruy , G. L. Kane , Joseph Lykken , Brent D. Nelson

Data science offers a powerful tool to understand objects in multiple sciences. In this paper we utilize concept of data science, most notably topological data analysis, to extend our understanding of knot theory. This approach provides a…

Geometric Topology · Mathematics 2025-03-20 Pawel Dlotko , Davide Gurnari , Radmila Sazdanovic

Most of modern neural machine translation (NMT) models are based on an encoder-decoder framework with an attention mechanism. While they perform well on standard datasets, they can have trouble in translation of long inputs that are rare or…

Computation and Language · Computer Science 2026-03-31 Shuhei Kondo , Katsuhito Sudoh , Yuji Matsumoto

Many optimization, inference and learning tasks can be accomplished efficiently by means of decentralized processing algorithms where the network topology (i.e., the graph) plays a critical role in enabling the interactions among…

Multiagent Systems · Computer Science 2020-08-06 Vincenzo Matta , Augusto Santos , Ali H. Sayed

If the results of the first LHC run are not betraying us, many decades of particle physics are culminating in a complete and consistent theory for all non-gravitational physics: the Standard Model. But despite this monumental achievement…

High Energy Physics - Phenomenology · Physics 2014-01-08 A. N. Schellekens

Data analysis is a powerful tool in all experimental sciences. Statistical methods, such as sampling theory, computer technologies necessary for handling large amounts of data, skill in analysing information contained in different types of…

Physics Education · Physics 2012-06-20 Vera Montalbano

We consider a social learning problem, where a network of agents is interested in selecting one among a finite number of hypotheses. We focus on weakly-connected graphs where the network is partitioned into a sending part and a receiving…

Multiagent Systems · Computer Science 2019-10-31 Vincenzo Matta , Virginia Bordignon , Augusto Santos , Ali H. Sayed

We consider the statistical mechanics of a system of topologically linked polymers, such as for instance a dense solution of polymer rings. If the possible topological states of the system are distinguished using the Gauss linking number as…

Statistical Mechanics · Physics 2010-01-05 Franco Ferrari

We consider two questions in string ``phenomenology.'' First, are there any generic string predictions? Second, are there any general lessons which string theory suggests for thinking about low energy models, particularly in the framework…

High Energy Physics - Phenomenology · Physics 2007-05-23 Michael Dine

Category theory has foundational importance because it provides conceptual lenses to characterize what is important in mathematics. Originally the main lenses were universal mapping properties and natural transformations. In recent decades,…

Category Theory · Mathematics 2007-05-23 David Ellerman

In some theory development tasks, a problem is satisfactorily solved once it is shown that a theorem (conjecture) is derivable from the background theory (premises). Depending on one's motivations, the details of the derivation of the…

Logic · Mathematics 2012-04-16 Jesse Alama

Recent developments involving strongly coupled superstrings are discussed from a phenomenological point of view. In particular, strongly coupled $E_8\times E'_8$ is described as an appropriate long-wavelength limit of M-theory, and some…

High Energy Physics - Theory · Physics 2007-05-23 D. V. Nanopoulos

After preamble about Darwin, my talk described the conformality approach to extending the standard model of particle phenomenology using an assumption of no conformal anomaly at high energy. Topics included quiver gauge theory, the…

High Energy Physics - Phenomenology · Physics 2007-05-23 Paul H. Frampton

Complex prediction models such as deep learning are the output from fitting machine learning, neural networks, or AI models to a set of training data. These are now standard tools in science. A key challenge with the current generation of…

Machine Learning · Computer Science 2022-10-21 Meng Liu , Tamal K. Dey , David F. Gleich

String theory and supersymmetry are theoretical ideas that go beyond the standard model of particle physics and show promise for unifying all forces. After a brief introduction to supersymmetry, we discuss the prospects for its experimental…

High Energy Physics - Theory · Physics 2008-11-26 John H. Schwarz , Nathan Seiberg

String theory, if it describes nature, is probably strongly coupled. As a result, one might despair of making any statements about the theory. In the framework of a set of clearly spelled out assumptions, we show that this is not…

High Energy Physics - Theory · Physics 2013-11-13 T. Banks , M. Dine

We introduce and develop the theory of metaparticles. At the classical level, this is a world-line theory with the usual reparameterization invariance and two additional features. The theory is motivated by string theory on compact targets,…

High Energy Physics - Theory · Physics 2019-04-03 Laurent Freidel , Jerzy Kowalski-Glikman , Robert G. Leigh , Djordje Minic

Chromomagnetic and chromoelectric dipole interactions of the top quark are studied in a model independent framework. Limits are set on the scale of new physics that might lead to such contributions using available Tevatron data. Prospects…

High Energy Physics - Phenomenology · Physics 2012-02-21 Debajyoti Choudhury , Pratishruti Saha

Seeking effective neural networks is a critical and practical field in deep learning. Besides designing the depth, type of convolution, normalization, and nonlinearities, the topological connectivity of neural networks is also important.…

Computer Vision and Pattern Recognition · Computer Science 2020-08-20 Kun Yuan , Quanquan Li , Jing Shao , Junjie Yan