pith:R4QU4CHX
Dark siren cross-correlations and the sensitivity of $H_0$ to methodological choices
Dark siren cross-correlations allow systematic biases in H0 to be mitigated through appropriate methodological choices and large precise samples.
arxiv:2605.06783 v2 · 2026-05-07 · astro-ph.CO
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\pithnumber{R4QU4CHXJT5PH7YKKACM564CGR}
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Claims
Our results indicate that, with appropriate modelling choices and a sufficiently large sample of precise gravitational wave events, the systematic biases considered here can be effectively mitigated.
That selection effects from catalog incompleteness can be fully absorbed into the theoretical prediction without needing an explicit model of the missing population, and that future gravitational wave samples will be both large and precise enough for the mitigation to hold.
Methodological choices in dark siren cross-correlations can mitigate biases in H0 inference when selection effects are built into the model and samples of precise events are sufficiently large.
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| First computed | 2026-07-09T01:20:05.345229Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
8f214e08f74cfaf3ff0a5004cefb82345f3e9ab7fdf0b6efee26d97a7cdb7286
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/R4QU4CHXJT5PH7YKKACM564CGR \
| 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())"
# expect: 8f214e08f74cfaf3ff0a5004cefb82345f3e9ab7fdf0b6efee26d97a7cdb7286
Canonical record JSON
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