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Analysis of the first IPTA Mock Data Challenge by the EPTA timing data analysis working group

This is a summary of the methods we used to analyse the first IPTA Mock Data Challenge (MDC), and the obtained results. We have used a Bayesian analysis in the time domain, accelerated using the recently developed ABC-method which consists of a form of lossy linear data compression. The TOAs were first processed with Tempo2, where the design matrix was extracted for use in a subsequent Bayesian analysis. We used different noise models to analyse the datasets: no red noise, red noise the same for all pulsars, and individual red noise per pulsar. We sampled from the likelihood with four different samplers: &#34;emcee&#34;, &#34;t-walk&#34;, &#34;Metropolis-Hastings&#34;, and &#34;pyMultiNest&#34;. All but emcee agreed on the final result, with emcee failing due to artefacts of the high-dimensionality of the problem. An interesting issue we ran into was that the prior of all the 36 (red) noise amplitudes strongly affects the results. A flat prior in the noise amplitude biases the inferred GWB amplitude, whereas a flat prior in log-amplitude seems to work well. This issue is only apparent when using a noise model with individually modelled red noise for all pulsars. Our results for the blind challenges are in good agreement with the injected values. For the GWB amplitudes we found h_c = 1.03 +/- 0.11 [10^{-14}], h_c = 5.70 +/- 0.35 [10^{-14}], and h_c = 6.91 +/- 1.72 [10^{-15}], and for the GWB spectral index we found gamma = 4.28 +/- 0.20, gamma = 4.35 +/- 0.09, and gamma = 3.75 +/- 0.40. We note that for closed challenge 3 there was quite some covariance between the signal and the red noise: if we constrain the GWB spectral index to the usual choice of gamma = 13/3, we obtain the estimates: h_c = 10.0 +/- 0.64 [10^{-15}], h_c = 56.3 +/- 2.42 [10^{-15}], and h_c = 4.83 +/- 0.50 [10^{-15}], with one-sided 2 sigma upper-limits of: h_c <= 10.98 [10^{-15}], h_c <= 60.29 [10^{-15}], and h_c <= 5.65 [10^{-15}].