Evolving neural networks with genetic algorithms to study the string landscape

A bstract We study possible applications of artificial neural networks to examine the string landscape. Since the field of application is rather versatile, we propose to dynamically evolve these networks via genetic algorithms. This means that we start from basic building blocks and combine them suc...

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Vydáno v:	The journal of high energy physics Ročník 2017; číslo 8; s. 1 - 20
Hlavní autor:	Ruehle, Fabian
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2017 Springer Nature B.V SpringerOpen
Témata:	Artificial neural networks Classical and Quantum Gravitation Computation Elementary Particles Evolution Genetic algorithms High energy physics Neural networks Phenomenology Physics Physics and Astronomy Quantum Field Theories Quantum Field Theory Quantum Physics Regular Article - Theoretical Physics Relativity Theory String Theory Strings Superstring Vacua Superstrings and Heterotic Strings Superstring Vacua Superstrings and Heterotic Strings
ISSN:	1029-8479, 1029-8479
On-line přístup:	Získat plný text
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