English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

A scan of soft SUSY breaking parameters within the string theory landscapewith the MSSM assumed as the low energy effective field theory -- using apower-law draw to large soft terms coupled with an anthropic selection of aderived weak scale to be within a factor four of our measured value -- predictsa peak probability of m_h~125 GeV with sparticles masses typically beyond thereach of LHC Run 2. Such multiverse simulations usually assume a fixed value ofthe SUSY conserving superpotential mu parameter to be within the assumedanthropic range, mu<~ 350 GeV. However, depending on the assumed solution tothe SUSY mu problem, the expected mu term distribution can actually be derived.In this paper, we examine two solutions to the SUSY mu problem. The first isthe gravity-safe-Peccei-Quinn (GSPQ) model based on an assumed Z_{24}^Rdiscrete R-symmetry which allows a gravity-safe accidental, approximatePeccei-Quinn global symmetry to emerge which also solves the strong CP problem.The second case is the Giudice-Masiero solution wherein the mu term effectivelyacts as a soft term and has a linear draw to large values. For the first case,we also present the expected landscape distribution for the PQ scale f_a; inthis case, weak scale anthropics limits its range to the cosmological sweetzone of around f_a~ 10^{11} GeV.

Distribution of supersymmetry mu parameter and Peccei-Quinn scale f_a from the landscape