High-scale SUSY from an R-invariant New Inflation in the Landscape
Masahiro Kawasaki; Masaki Yamada; Tsutomu T. Yanagida; Norimi Yokozaki · 2015 · arXiv
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
The finding, in one line
“We provide an anthropic reason that the supersymmetry breaking scale is much higher than the electroweak scale as indicated by the null result of collider experiments and observed 125 GeV Higgs boson.”
Abstract (excerpt)
We provide an anthropic reason that the supersymmetry breaking scale is much higher than the electroweak scale as indicated by the null result of collider experiments and observed 125 GeV Higgs boson. We focus on a new inflation model as a typical low-scale inflation model that may be expected in the string landscape. In this model, the R-symmetry is broken at the minimum of the inflaton potential and its breaking scale is related to the reheating temperature. Once we admit that the anthropic principle requires thermal leptogenesis, we obtain a lower bound on gravitino mass, which is related t
Excerpt shown for reference under fair use — read the full paper at the publisher.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
Leakage and the reproducibility crisis in machine-learning-based science
Negative / Null Result ReportDefining and detecting quantum speedup
Negative / Null Result ReportService robots in hotels: understanding the service quality perceptions of human-robot interaction
Negative / Null Result ReportBoosting methods for multi-class imbalanced data classification: an experimental review
Negative / Null Result ReportFINANCIAL DEVELOPMENT AND ECONOMIC GROWTH: A META‐ANALYSIS
Negative / Null Result ReportThe impact of site-specific digital histology signatures on deep learning model accuracy and bias
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: arXiv