Pith. sign in

REVIEW 1 cited by

Tensor spectrum of turbulence-sourced gravitational waves as a constraint on graviton mass

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 2104.03192 v2 pith:36ZSJT5W submitted 2021-04-07 gr-qc astro-ph.CO

classification gr-qcastro-ph.CO
keywords spectragravitationalrangewavesduringgravitonmassmodifications
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
abstract

We consider a generic dispersive massive gravity theory and numerically study its resulting modified energy and strain spectra of tensor gravitational waves (GWs) sourced by (i) fully developed turbulence during the electroweak phase transition (EWPT) and (ii) forced hydromagnetic turbulence during the QCD phase transition (QCDPT). The GW spectra are then computed in both spatial and temporal Fourier domains. We find, from the spatial spectra, that the slope modifications are weakly dependent on the eddy size at QCDPT, and, from the temporal spectra, that the modifications are pronounced in the $1$--$10{\rm nHz}$ range -- the sensitivity range of the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) -- for a graviton mass $m_{\rm g}$ in the range $2\times10^{-23}{\rm eV}\lesssim m_{\rm g}c^2\lesssim7\times10^{-22}{\rm eV}$.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

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

  1. Do Pulsar Timing Datasets Favor Massive Gravity?

    astro-ph.CO 2025-07 reject novelty 5.0 of 10

    A one-parameter massive-gravity correlation curve gives lower chi-square than the Hellings-Downs curve for current pulsar-timing data, but the parameter is fitted to the data, so the result is not a prediction.

Pith tools