2006/10/31 by Gordon L. Kane, Gordon L Kane, Piyush Kumar +1
Computer Science · Physics and Astronomy · #Computational Physics and Python Applications #High-Energy Particle Collisions Research #Particle physics theoretical and experimental studies #hep-ex #hep-ph #hep-th
paper · pdf · doi:10.1088/0954-3899/34/9/011
published as J.Phys.G34:1993-2036,2007 · 50 Pages, 13 Figures, 3 Tables, v2: minor changes, references added
arxiv created 2007/06/05 · openalex publication_date 2007/07/31 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/04
We argue that it is possible to address the deeper LHC inverse problem, to gain insight into the underlying theory from LHC signatures of new physics. We propose a technique which may allow us to distinguish among, and favor or disfavor, various classes of underlying theoretical constructions using (assumed) new physics signals at the LHC. We think that this can be done with limited data (5–10 fb −1 ), and improved with more data. This is because of two reasons: (a) it is possible in many cases to reliably go from (semi)realistic microscopic string constructions to the space of experimental observables, say, LHC signatures, and (b) the patterns of signatures at the LHC are sensitive to the structure of the underlying theoretical constructions. We illustrate our approach by analyzing two promising classes of string compactifications along with six other string-motivated constructions. Even though these constructions are not complete, they illustrate the point we want to emphasize. We think that using this technique effectively over time can eventually help us to meaningfully connect experimental data to microscopic theory.