A Pulsar Timing Array (PTA), such as the one that NANOGrav has constructed, is designed to detect and study long-wavelength gravitational waves. The LIGO detector, which detected gravitational waves from merging black holes in 2015, has similarities and differences with the NANOGrav PTA. In both experiments, however, it is vital to characterize the detector noise that could give rise to a false signal. This is even more important for the NANOGrav PTA because our expected signal is similar to some features of the detector noise. In this paper, we detail how NANOGrav characterizes the detector noise – both its likely causes and its properties – and spell out how we account for that in our search for a gravitational-wave signal in the data.
The NANOGrav PTA consists of 68 arms, each one of which extends from the Earth to a pulsar situated hundreds to thousands of light years distant in our Milky Way Galaxy. As sketched in enclosed Figure, radio waves from each of the 68 pulsars travel a distinct path through the interstellar medium (ISM). Radio waves are slowed down slightly by the ionized gas in the ISM, by an amount that depends on the radio frequency, as is shown by the increasingly delayed signal at lower radio frequencies in Figure 1. The motion of the pulsars through the ISM at hundreds of kilometers per second (and, to a lesser extent, the motion of the Earth and the ISM), causes this dispersion delay to change with time, an effect that we carefully correct for by observing each pulsar at multiple radio frequencies at each epoch. This is but one of more than a dozen such subtle effects that we need to carefully monitor and, where possible, mitigate their effect on the pulse arrival times, which are the essential measurements for our experiment. To achieve the necessary precision, we must predict the arrival of a pulse to within about 1 microsecond over a period of 15 years. This is a fractional precision of 2 parts in 1015, comparable to measuring the distance to the Moon to within a thousandth of a millimeter!
Agazie et al., 2023, The NANOGrav 15-Year Data Set: Detector Characterization and Noise Budget. DOI: 10.3847/2041-8213/acda88
Dr. Jeffrey Hazboun
Lead for the Detector Characterization Paper