Pith. sign in

REVIEW 1 cited by

Signal-to-noise Ratio Analytic Formulae of the Inspiral Binary Black Holes in TianQin

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2410.19401 v3 pith:65SN26ZK submitted 2024-10-25 astro-ph.GA astro-ph.IMgr-qc

Signal-to-noise Ratio Analytic Formulae of the Inspiral Binary Black Holes in TianQin

classification astro-ph.GA astro-ph.IMgr-qc
keywords blackholesbinaryratiosignal-to-noisetianqinanalyticallyaverage
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

Binary black holes are one of the important sources for the TianQin gravitational wave project. Our research has revealed that, for TianQin, the signal-to-noise ratio of inspiral binary black holes can be computed analytically. This finding is expected to greatly simplify the estimation of detection capabilities for binary black holes. In this paper, we demonstrated the signal-to-noise ratio relationships from stellar-mass black holes to massive black holes. With the all-sky average condition, the signal-to-noise ratio for most binary black hole signals can be determined with a relative error of $\lesssim10\%$, with notable deviations only for chirp masses near $1000~M_\odot$. In contrast, the signal-to-noise ratio without the average includes an additional term, which we refer to as the response factor. Although this term is not easily calculated analytically, we provide a straightforward estimation method with an error margin of $1\sigma$ within 2\%.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Pre-localization of Massive Black Hole Binaries in the Millihertz Band

    gr-qc 2026-04 unverdicted novelty 5.0

    A neural spline flow pipeline performs amortized inference on millihertz MBHB signals, delivering ~20 deg² pre-merger sky localizations in ~1 minute while matching PTMCMC sky modes and parameter uncertainties.