Superfluid helium ultralight dark matter detector
Bibliographic record
Abstract
The absence of a breakthrough in directly observing dark matter (DM) through prominent large-scale detectors motivates the development of novel tabletop experiments probing more exotic regions of the parameter space. If DM contains ultralight bosonic particles, they would behave as a classical wave and could manifest through an oscillating force on baryonic matter that is coherent over $\ensuremath{\sim}{10}^{6}$ periods. Our Helium ultraLIght dark matter Optomechanical Sensor (HeLIOS) uses the high-$Q$ acoustic modes of superfluid helium-4 to resonantly amplify this signal. A superconducting reentrant microwave cavity enables sensitive optomechanical readout ultimately limited by thermal motion at millikelvin temperatures. Pressurizing the helium allows for the unique possibility of tuning the mechanical frequency to effectively broaden the DM detection bandwidth. We demonstrate the working principle of our prototype HeLIOS detector and show that future generations of HeLIOS could explore unconstrained parameter space for both scalar and vector ultralight DM after just an hour of integration time.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".