Axio-Chameleons: a novel string-friendly multi-field screening mechanism
Bibliographic record
Abstract
Abstract Scalar-tensor theories with the shift symmetries required by light scalars are well-explored modifications to GR. For these, two-derivative scalar self-interactions usually dominate at low energies and interestingly compete with the two-derivative metric interactions of GR itself. Although much effort has been invested in single scalars (on grounds of simplicity) these happen to have no two-derivative interactions, requiring such models to explore higher-derivative interactions (that usually would be less important at low-energies). This suggests multiple-scalar sigma models as well-motivated candidates for finding new phenomena in tests of gravity. We identify a new multi-field screening mechanism appropriate for two light scalar fields (an axion and a Brans-Dicke style dilaton) that relies on their mutual two-derivative interactions. We show how very weak axion-matter couplings can introduce axion gradients that can reduce the apparent coupling of the Brans-Dicke scalar to macroscopic matter sources. We further identify a relaxation mechanism that allows this reduction to be amplified to a suppression by the ratio of the axion gradient's length scale to the source's radius (similar in size to the suppression found in Chameleon models). Unlike some screening mechanisms our proposal is technically natural and works deep within the regime of control of the low-energy EFT. It uses only ingredients that commonly appear in the low-energy limit of string vacua and so is likely to have wider applications to models that admit UV completions. We briefly discuss phenomenological implications and challenges for this scenario, which suggests re-examination of decay loss bounds and the value of equivalence-principle tests for different-sized objects.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".