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The NANOGrav 15 Yr Data Set: Removing Pulsars One by One from the Pulsar Timing Array
Journal article   Open access   Peer reviewed

The NANOGrav 15 Yr Data Set: Removing Pulsars One by One from the Pulsar Timing Array

Gabriella Agazie, Akash Anumarlapudi, Anne Archibald, Zaven Arzoumanian, Jeremy Baier, Paul Baker, Bence Bécsy, Laura Blecha, Adam Brazier, Paul Brook, …
The Astrophysical journal, Vol.978(2), p.168
01/01/2025

Abstract

Arrays Background noise Data analysis Datasets Gravitational waves Noise measurement Pulsars Signal strength Synthetic data Systematics
Evidence has emerged for a stochastic signal correlated among 67 pulsars within the 15 yr pulsar-timing data set compiled by the NANOGrav collaboration. Similar signals have been found in data from the European, Indian, Parkes, and Chinese pulsar timing arrays. This signal has been interpreted as indicative of the presence of a nanohertz stochastic gravitational-wave background (GWB). To explore the internal consistency of this result, we investigate how the recovered signal strength changes as we remove the pulsars one by one from the data set. We calculate the signal strength using the (noise-marginalized) optimal statistic, a frequentist metric designed to measure the correlated excess power in the residuals of the arrival times of the radio pulses. We identify several features emerging from this analysis that were initially unexpected. The significance of these features, however, can only be assessed by comparing the real data to synthetic data sets. After conducting identical analyses on simulated data sets, we do not find anything inconsistent with the presence of a stochastic GWB in the NANOGrav 15 yr data. The methodologies developed here can offer additional tools for application to future, more sensitive data sets. While this analysis provides an internal consistency check of the NANOGrav results, it does not eliminate the necessity for additional investigations that could identify potential systematics or uncover unmodeled physical phenomena in the data.
url
https://doi.org/10.3847/1538-4357/ad93aaView
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