Landscape Higgs and sparticle mass predictions from a logarithmic soft term distribution

TL;DR

This paper investigates how different statistical distributions of soft terms in string theory landscapes affect predictions for Higgs and sparticle masses, finding a logarithmic distribution still predicts a Higgs mass around 125 GeV with sparticles beyond current collider reach.

Contribution

It introduces a new analysis of landscape predictions using a logarithmic soft term distribution, contrasting previous power-law assumptions, and assesses implications for Higgs and sparticle mass spectra.

Findings

Higgs mass peaks around 125 GeV with a log soft term distribution.

Sparticles are predicted to be beyond LHC reach.

Logarithmic distribution yields softer mass spectra than power-law.

Abstract

Recent work on calculating string theory landscape statistical predictions for the Higgs and sparticle mass spectrum from an assumed power-law soft term distribution yields an expectation for m(h)~ 125 GeV with sparticles (save light higgsinos) somewhat beyond reach of high-luminosity LHC. A recent examination of statistics of SUSY breaking in IIB string models with stabilized moduli suggests a power-law for models based on KKLT stabilization and uplifting while models based on large-volume scenario (LVS) instead yield an expected logarithmic soft term distribution. We evaluate statistical distributions for Higgs and sparticle masses from the landscape with a log soft term distribution and find the Higgs mass still peaks around ~125 GeV with sparticles beyond LHC reach, albeit with somewhat softer distributions than those arising from a power-law.