A new probe of the small-scale primordial power spectrum: Astrometric microlensing by ultracompact minihalos
Bibliographic record
Abstract
The dark matter enclosed in a density perturbation with a large initial amplitude ($\ensuremath{\delta}\ensuremath{\rho}/\ensuremath{\rho}\ensuremath{\gtrsim}{10}^{\ensuremath{-}3}$) collapses shortly after recombination and forms an ultracompact minihalo (UCMH). Their high central densities make UCMHs especially suitable for detection via astrometric microlensing: as the UCMH moves, it changes the apparent position of background stars. An UCMH with a mass larger than a few solar masses can produce a distinctive astrometric microlensing signal that is detectable by the space astrometry mission Gaia. If Gaia does not detect gravitational lensing by any UCMHs, then it establishes an upper limit on their abundance and constrains the amplitude of the primordial power spectrum for $k\ensuremath{\sim}2700\text{ }\text{ }{\mathrm{Mpc}}^{\ensuremath{-}1}$. These constraints complement the upper bound on the amplitude of the primordial power spectrum derived from limits on gamma-ray emission from UCMHs because the astrometric microlensing signal produced by an UCMH is maximized if the dark matter annihilation rate is too low to affect the UCMH's density profile. If dark matter annihilation within UCMHs is not detectable, a search for UCMHs by Gaia could constrain the amplitude of the primordial power spectrum to be less than ${10}^{\ensuremath{-}5}$; this bound is 3 orders of magnitude stronger than the bound derived from the absence of primordial black holes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".