Direct detection of mirror matter in Twin Higgs models
Bibliographic record
Abstract
Abstract We explore the possibility of discovering the mirror baryons and electrons of the Mirror Twin Higgs model in direct detection experiments, in a scenario in which these particles constitute a subcomponent of the observed DM. We consider a framework in which the mirror fermions are sub-nano-charged, as a consequence of kinetic mixing between the photon and its mirror counterpart. We consider both nuclear recoil and electron recoil experiments. The event rates depend on the fraction of mirror DM that is ionized, and also on its distribution in the galaxy. Since mirror DM is dissipative, at the location of the Earth it may be in the form of a halo or may have collapsed into a disk, depending on the cooling rate. For a given mirror DM abundance we determine the expected event rates in direct detection experiments for the limiting cases of an ionized halo, an ionized disk, an atomic halo and an atomic disk. We find that by taking advantage of the complementarity of the different experiments, it may be possible to establish not just the multi-component nature of mirror dark matter, but also its distribution in the galaxy. In addition, a study of the recoil energies may be able to determine the masses and charges of the constituents of the mirror sector. By showing that the mass and charge of mirror helium are integer multiples of those of mirror hydrogen, these experiments have the potential to distinguish the mirror nature of the theory. We also carefully consider mirror plasma screening effects, showing that the capture of mirror dark matter particles in the Earth has at most a modest effect on direct detection signals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".