Connecting String/M Theory to the Electroweak Scale and to LHC Data

TL;DR

This paper explores connecting string/M theory to the electroweak scale and LHC data, aiming to solve the inverse problem of deducing underlying theories from experimental results.

Contribution

It proposes a systematic approach combining top-down string theory models with bottom-up data analysis to identify observable patterns and distinguish between theoretical constructions.

Findings

Identifies patterns of experimental observables sensitive to underlying theories

Develops methods to connect string/M theory models to low-energy physics

Provides insights into qualitative features of models from data

Abstract

The Standard Model of particle physics explains (almost) all observed non-gravitational microscopic phenomena but has many open theoretical questions. We are on the threshold of unraveling the mysteries of the Standard Model and discovering its extension. This could be achieved in the near future with the help of many experiments in particle physics and cosmology, the LHC in particular. Assuming that data confirming the existence of new physics beyond the Standard Model is obtained, one is left with the very important and challenging task of solving the "Inverse Problem", \emph{viz.} "How can one deduce the nature of the underlying (perhaps microscopic) theory from data?" This thesis explores this question in detail, and also proposes an approach to address the problem in a meaningful way which could prove crucial to the possible solution to this problem in the future. The proposed approach has three aspects - a) To systematically study classes of microscopic (string/$M$ theory) constructions to the extent that they could be connected to low energy physics (electroweak scale), b) To find patterns of experimental observables which are sensitive to the properties of the underlying theoretical constructions thereby allowing us to distinguish among different constructions, and c) To try to get insights about the qualitative features of the theoretical model from data in a bottom-up approach which complements the top-down approach and strengthens it as well. This thesis studies all the above aspects in detail. The methods used and results obtained in this thesis will hopefully be of great importance in solving the Inverse Problem.