Constraints on millicharged dark matter and axionlike particles from timing of radio waves
Bibliographic record
Abstract
We derive constraints on millicharged dark matter and axionlike particles using pulsar timing and fast radio burst observations. For dark matter particles of charge $\ensuremath{\epsilon}e$, the constraint from time of arrival (TOA) of waves is $\ensuremath{\epsilon}/{m}_{\mathrm{milli}}\ensuremath{\lesssim}{10}^{\ensuremath{-}8}\text{ }\text{ }{\mathrm{eV}}^{\ensuremath{-}1}$, for masses ${m}_{\mathrm{milli}}\ensuremath{\gtrsim}{10}^{\ensuremath{-}6}\text{ }\text{ }\mathrm{eV}$. For axionlike particles, the polarization of the signals from pulsars yields a bound in the axial coupling $g/{m}_{a}\ensuremath{\lesssim}{10}^{\ensuremath{-}13}\text{ }\text{ }{\mathrm{GeV}}^{\ensuremath{-}1}/({10}^{\ensuremath{-}22}\text{ }\text{ }\mathrm{eV})$, for ${m}_{a}\ensuremath{\lesssim}{10}^{\ensuremath{-}19}\text{ }\text{ }\mathrm{eV}$. Both bounds scale as $(\ensuremath{\rho}/{\ensuremath{\rho}}_{\mathrm{dm}}{)}^{1/2}$ for fractions of the total dark matter energy density ${\ensuremath{\rho}}_{\mathrm{dm}}$. We make a precise study of these bounds using TOA from several pulsars, FRB 121102, and polarization measurements of PSR $\mathrm{J}0437\ensuremath{-}4715$. Our results rule out a new region of the parameter space for these dark matter models.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".