Stochastic propagators for multi-pion correlation functions in lattice   QCD with GPUs
  Motivated by the application of L\"uscher's finite volume method to the study of the lightest scalar resonance in the $\pi\pi \to \pi\pi$ isoscalar channel, in this article we describe our studies of multi-pion correlation functions computed using stochastic propagators in quenched lattice QCD, harnessing GPUs for acceleration. We consider two methods for constructing the correlation functions. One "outer product" approach becomes quite expensive at large lattice extent $L$, having an ${\cal O}(L^7)$ scaling. The other "stochastic operator" approach scales as ${\cal O}(N_r^2 L^4)$, where $N_r$ is the number of random sources. It would become more efficient if variance reduction techniques are used and the volume is fairly large. It is also found that correlations between stochastic propagators appearing in the same diagram, when a single set of random source vectors is used, lead to much larger errors than if separate random sources are used for each propagator. The calculations involve states with quantum numbers of the vacuum, so all-to-all propagators must be computed. For this reason, GPUs are ideally suited to accelerating the calculation. For this work we have integrated the Columbia Physics System (CPS) and QUDA GPU inversion library, in the case of clover fermions. Finally, we show that the completely quark disconnected diagram is crucial to the results, and that neglecting it would lead to answers which are far from the true value for the effective mass in this channel. This is unfortunate, because as we also show, this diagram has very large errors, and in fact dominates the error budget. 
Joel Giedt, Dean Howarth
hep-lat