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Low fine tuning in the MSSM with higgsino dark matter and unification constraints

High Energy Physics - Phenomenology · Submitted 6 Feb 2014

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim There, we find that the fine tuning can be reduced to the level of a few percent.

how it is stated · asserted 0.90 read the record →

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arXiv ID1402.1328 (version 3)
Pith IDSAVV3UHH, Pith's permanent record of this paper and its review
CitationEnrico Maria Sessolo, Kamila Kowalska, Leszek Roszkowski, Sebastian Trojanowski. "Low fine tuning in the MSSM with higgsino dark matter and unification constraints." arXiv:1402.1328 (2014). https://pith.science/paper/SAVV3UHH
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 5,040 input tokens, $0.0002 reported.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.89 · human participants 0.01 · controlled comparison 0.29 · randomized assignment 0.01 · states quantitative result 0.97 · compares with prior results 0.69 · mentions code or data availability 0.01.

The abstract, sentence by sentence

arXiv listing abstract v3. Results and the main claim are underlined; .

We examine the issue of fine tuning in the MSSM with GUT-scale boundary conditions. We identify specific unification patterns and mass relations that can lead to a significant lowering of the fine tuning due to gauginos, scalars, and the \mu\ parameter, relative to the simplest unification conditions. We focus on a phenomenologically interesting region that is favored by the Higgs mass and the relic density where the dark matter is a nearly pure higgsino with mass given by \mu~1 TeV while the scalars and gauginos have masses in the multi-TeV regime. There, we find that the fine tuning can be reduced to the level of a few percent. Despite the gluino mass in the ballpark of 2 TeV, resulting mass spectra will be hard to explore at the LHC, but good prospects for detection come from dark matter direct detection experiments. Finally, we demonstrate with a specific example how the conditions and mass relations giving low fine tuning can originate in the context of supergravity and Grand Unified Theories.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 We examine the issue of fine tuning in the MSSM with GUT-scale boundary conditions. contribution 0.56 0.82 0.03 unclear 0.70
s1 We identify specific unification patterns and mass relations that can lead to a significant lowering of the fine tuning due to gauginos, scalars, and the \mu\ parameter, relative to the simplest unification conditions. contribution 0.88 0.92 0.36 asserted 0.61
s2 We focus on a phenomenologically interesting region that is favored by the Higgs mass and the relic density where the dark matter is a nearly pure higgsino with mass given by \mu~1 TeV while the scalars and gauginos have masses in the multi-TeV regime. contribution 0.82 0.48 0.10 asserted 0.95
s3 There, we find that the fine tuning can be reduced to the level of a few percent. result 1.00 0.95 0.58 asserted 0.90
s4 Despite the gluino mass in the ballpark of 2 TeV, resulting mass spectra will be hard to explore at the LHC, but good prospects for detection come from dark matter direct detection experiments. interpretation 0.74 0.77 0.09 asserted 0.87
s5 Finally, we demonstrate with a specific example how the conditions and mass relations giving low fine tuning can originate in the context of supergravity and Grand Unified Theories. contribution 0.90 0.93 0.11 asserted 1.00

What kind of paper the classifier reports this is: theoretical result 0.98 · evidence from simulation or computation 0.70.

What was examined, and what was not

sources read
  • arXiv listing abstract v3
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

We examine the issue of fine tuning in the MSSM with GUT-scale boundary conditions. We identify specific unification patterns and mass relations that can lead to a significant lowering of the fine tuning due to gauginos, scalars, and the \mu\ parameter, relative to the simplest unification conditions. We focus on a phenomenologically interesting region that is favored by the Higgs mass and the relic density where the dark matter is a nearly pure higgsino with mass given by \mu~1 TeV while the scalars and gauginos have masses in the multi-TeV regime. There, we find that the fine tuning can be reduced to the level of a few percent. Despite the gluino mass in the ballpark of 2 TeV, resulting mass spectra will be hard to explore at the LHC, but good prospects for detection come from dark matter direct detection experiments. Finally, we demonstrate with a specific example how the conditions and mass relations giving low fine tuning can originate in the context of supergravity and Grand Unified Theories.

Human review
References
How the literature uses it

25 arXiv papers cite this in 33 sentences

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

Papers citing it · 25 sentences without a confident label

Uses its method or tool 1 paper
Cites it as support 1 paper
Cites it as background 5 papers

What it cites · 67 sentences without a confident label

Uses the method or tool of 10 papers
Uses data or values from 2 papers
Cites as support 1 paper
Cites as background 26 papers

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