pith:5DIPMS73
Bayesian analysis of density profile of light dark matter elucidating the properties of dark matter admixed neutron stars in the presence of hyperons
Bayesian inference shows that the mass and density-profile parameter of sub-GeV dark matter in neutron stars are nearly independent of the hadronic model for moderate symmetry-energy slopes.
arxiv:2605.14447 v1 · 2026-05-14 · nucl-th · hep-ph · hep-th
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Claims
Employing models of DMANSs that satisfy several observational data, we infer with Bayesian analysis, the likely ranges of m_χ and α are almost independent of the underlying hadronic model within 40 MeV ≲ L0 < 58 MeV.
The assumption that the dark-matter density profile inside the star can be written as an exponential function of baryon density controlled by a single free parameter α, together with the requirement that dark matter contributes less than 10 percent to the total mass.
Bayesian analysis finds that the likely ranges of light dark-matter fermion mass and exponential density-profile parameter in hyperon-containing neutron stars are nearly independent of the hadronic model for symmetry-energy slopes between 40 and 58 MeV, with HESS J1731-347 and GW170817 data playing,
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| First computed | 2026-05-17T23:39:06.943717Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
e8d0f64bfbc7ba70f4c71699db0a14e0c7163ef1d52dd4cb3e04a766a011e014
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/5DIPMS73Y65HB5GHC2M5WCQU4D \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
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Canonical record JSON
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