Orateur
Description
The EPTA+InPTA DR2new+ dataset has recently been combined with low-frequency measurements from LOFAR and NenuFAR (Iraci et al., 2025), with the aim of generating a dataset capable of disentangling the DM variation noise from achromatic red noise and the stochastic background. Simulations have shown that better distinguishing between these components is expected to improve sensitivity to the GWB signal and lead to more accurate and precise GWB parameter estimation (Ferranti et al., 2025). This talk presents and discusses the first results from a GWB search performed on this dataset. A key challenge in this analysis is addressing noise sources mostly neglected in EPTA DR2, such as solar wind and scattering variations noise. The very low frequency backends of LOFAR and NenuFAR make the new dataset extremely sensitive to these two sources of chromatic noise. Furthermore, the DR2low dataset has been employed to evaluate the performance of an analysis pipeline based on the Discovery package, coupled with an efficient sampling strategy exploiting variational inference. The ability of this new pipeline to accurately reproduce the posterior distribution of single pulsar noise analyses and GWB joint searches has been carefully tested to determine how much we can trust this pipeline for analysing future datasets such as EPTA DR3.