Optimising the MeerKAT Pulsar Timing Array and towards precision pulsar timing with SKA-mid

TL;DR

The paper analyzes limiting noise sources in pulsar timing arrays, focusing on MeerKAT data to quantify jitter and DM variations, and uses Gaussian-process DM modelling to forecast sensitivity. It demonstrates that jitter will dominate timing precision for many high-precision MSPs with SKA-mid, motivating sub-array strategies, while GP DM modelling can improve SGWB sensitivity by about 44% over DMX. It also evaluates multi-frequency observing plans, showing Ultra-High Frequency (UHF) observations can boost GW sensitivity, though decorrelated chromatic noise can diminish this gain. The work provides practical optimization pathways for the MeerKAT timing array and informs IPTA and SKA-mid planning for robust detection and characterization of nHz GW signals.

Abstract

Pulsar timing arrays (PTAs) are Galactic-scale nanohertz-frequency gravitational wave (GW) detectors. Recently, several PTAs have found evidence for the presence of GWs in their datasets, but none of them have achieved a community-defined definitive (> 5$σ$) detection. Here, we identify limiting noise sources for PTAs and quantify their impact on sensitivity to GWs under different observing and noise modelling strategies. First, we search for intrinsic pulse jitter in a sample of 89 MSPs observed by the MeerKAT Pulsar Timing Array and obtain new jitter measurements for 20 MSPs. We then forecast jitter noise in pulsars for the future SKA-Mid telescope, finding that the timing precision of many of the best-timed MSPs would be dominated by jitter noise. We then consider dispersion measure variations from the interstellar medium and find that their effects are best mitigated by modelling them as a stationary Gaussian process with a power-law spectrum. Improving upon the established hasasia code for PTA sensitivity analysis, we assess the timing potential of the lower frequency UHF-band (544$-$1088\,MHz) of MeerKAT and find a potential increase in GW background sensitivity by $\approx 8$\%, relative to observing at L-band. We show that this improvement relies on assumptions on the propagation through the interstellar medium, and highlight that if observing frequency-dependent propagation effects, such as scattering noise, are present, where noise is not completely correlated across observing frequency, then the improvement is significantly diminished. Using the multi-frequency receivers and sub-arraying flexibility of MeerKAT, we find that focussed, high-cadence observations of the best MSPs can enhance the sensitivity of the array for both the continuous GWs and stochastic GWB. These results highlight the role of MeerKAT and the MPTA in the context of international GW search efforts.

Figures (11)

• Figure 1: Fraction of jitter-limited observations ($F_{\rm J}$) per pulsar in MPTA. Out of the 41 MSPs, 15 pulsars are not included in this analysis as none of the observations were jitter-limited according to our definition. The pulsars are sorted by the fraction, and PSR J0437$-$4715 has 100% observations that are jitter-limited.
• Figure 2: Comparison of $W_{\rm eff}$ and $\sigma_{\rm J} (\rm hr)$ for the MPTA pulsars. The median relationship is $36.9(8.1) \times (W_{\rm eff}/10^{-4} ) + 4.2(2.7)$ and the 2$\sigma$ uncertainty regions for the likelihood fit are plotted.
• Figure 3: Comparison of ECORR parameters derived in MPTA noise analysis and jitter values estimated in this work. The blue points and green points denote direct measurements of jitter noise and upper limits, respectively. Jitter measurements are systematically lower than the ECORR values. The red dashed line corresponds to a 1:1 relationship between $\sigma_{\rm J} (\rm hr)$ and ECORR.
• Figure 4: Fraction of jitter-limited observations ($F_{\rm J}$) for each pulsar with a telescope with SKA-Mid sensitivity. Jitter noise is measured in this work for 41 MSPs. For the MSPs without jitter measurements, we have used the relation between $W_{\rm eff}$ and $\sigma_{\rm J}(\rm hr)$ derived from Figure \ref{['fig:weff_jit']} to estimate the jitter. Hence, three fractions are shown: one using the median relation, and the other two showing the 2$\sigma$ region to define optimistic (green) and pessimistic (blue) scenarios for the jitter noise in these pulsars. The fractional values are sorted by the median method. Many high-precision MSPs in SKA-Mid will be completely jitter-limited if observed with the entire array.
• Figure 5: Comparison of sensitivity curves for the MPTA with alternate DM noise modelling methods. The cyan curve corresponds to white noise, red noise and chromatic noise, the purple curve additionally includes DM as a GP, whereas the crimson curve includes DMX. The DMX implementation reduces the sensitivity by 44% compared with the DM GP model.