The ILC as a natural SUSY discovery machine and precision microscope: From light higgsinos to tests of unification
Bibliographic record
Abstract
The requirement of electroweak naturalness in simple supersymmetric models motivates the existence of a cluster of four light higgsinos with mass $100 - 300$ GeV, the lighter the better. While such light compressed spectra may be challenging to observe at the LHC, future $e^+e^-$ colliders with $\sqrt{s} > 2$m(higgsino) would serve as both a SUSY discovery machine and a precision microscope. We study signatures of higgsino pair production at the ILC based on full, Geant4-based simulation of the ILD detector concept. We examine several benchmark scenarios that may or may not be accessible to HL-LHC searches, with mass differences between the higgsino states between 4 and 20 GeV. Assuming $\sqrt{s}\geq$ 500 GeV and $1000$ fb$^{-1}$ of integrated luminosity, the individual higgsino masses can be measured to $1 - 2\%$ precision in case of the larger mass differences, and at the level of 5$\%$ for the smallest mass difference case. The higgsino mass splittings are sensitive to the electroweak gaugino masses and can allow extraction of gaugino masses to $3 - 20\%$ (depending on the model).Extrapolation of gaugino masses via renormalization group running can test the hypothesis of gaugino mass unification. We also examine a case with natural generalized mirage mediation where the unification of gaugino masses at an intermediate scale apparently gives rise to a natural SUSY spectrum somewhat beyond the reach of the HL-LHC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".