Bibliographic record
Abstract
We present a novel theory of a unified dark sector, where late-time cosmic acceleration emerges from the dark matter superfluid framework. The system is described by a superfluid mixture consisting of two distinguishable states with a small energy gap, such as the ground state and an excited state of dark matter. Given their contact in the superfluid, interaction between those states can happen, converting one state into the other. This long range interaction within the superfluid couples the two superfluid phonon species through a cosine potential motivated by Josephson/Rabi interactions. As a consequence of this potential, a new dynamics of late-time accelerated expansion emerges in this system, without the need of dark energy, coming from a universe containing only this two-state DM superfluid. Because the superfluid species are non-relativistic, their sound speeds remain suitably small throughout the evolution. We calculate the expansion history and growth of linear perturbations, and compare the results to ΛCDM cosmology. For the fiducial parameters studied here, the predicted expansion and growth function are close to those of ΛCDM, but the difference in the predicted growth rate is significant at late times. The present theory nicely complements the recent proposal of dark matter superfluidity to explain the empirical success of MOdified Newtonian Dynamics (MOND) on galactic scales, thus offering a unified framework for dark matter, dark energy, and MOND phenomenology.
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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 | 0.001 |
| 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 | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".