REVIEW 3 cited by
Dark Matter Spike surrounding Supermassive Black Holes Binary and the Nanohertz Stochastic Gravitational Wave Background
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
Signed reviews
abstract
The NANOGrav, PPTA, EPTA, CPTA and MPTA collaborations have reported compelling evidence for the existence of the Stochastic Gravitational-Wave Background (SGWB). This inferred background's amplitude and frequency spectrum align closely with the astrophysical predictions for a signal originating from the population of supermassive black hole (SMBH) binaries. Considering these findings, we explore the possibility of detecting dark matter (DM) spikes surrounding SMBHs, which could alter the gravitational-wave waveform and influence the SGWB. We show that the evolution of SMBH binaries, driven by both gravitational radiation and the dynamic friction of the surrounding DM spike, presents observable effects in the nHz frequency domain of the SGWB. We also employ the Bayesian inference method to fit the SGWB spectra from the NANOGrav, EPTA, and PPTA. The model with DM spike improves the fittings to the former two data sets. The spike slope $\gamma_{\rm sp}$ is slightly smaller than 1, which may suggest that the spike is flattened during the inspiral of the SMBHBs.
Forward citations
Cited by 3 Pith papers
-
The power of SKA to Constrain cosmological gravitational-wave backgrounds below the astrophysical foreground noise
Cosmological gravitational wave backgrounds from phase transitions, domain walls, and condensate fragmentation are capped far below the astrophysical foreground by requiring that compact dark matter subhalos, which SK...
-
Probing Self-Interacting Dark Matter via Gravitational-Wave Background from Eccentric Supermassive Black Hole Mergers
Eccentric supermassive black hole binaries embedded in self-interacting dark matter produce a suppressed nanohertz gravitational-wave background, and current PTA data bound the cross section at sigma/mchi less than ab...
-
In-Context Learning for Label-Efficient Cancer Image Classification in Oncology
Few-shot in-context prompting improves frozen vision-language model F1 scores on three cancer image datasets, with GPT-4o reaching 0.81 binary and 0.60 multi-class.
Discussion (0). Continue with ORCID to comment.