Abstract
Excited state contamination remains one of the most challenging sources of systematic uncertainty to control in lattice QCD calculations of nucleon matrix elements and form factors: early time separations are contaminated by excited states and late times suffer from an exponentially bad signal-to-noise problem. High-statistics calculations at large time separations 1 fm are commonly used to combat these issues. In this work, focusing on gA, we explore the alternative strategy of utilizing a large number of relatively low-statistics calculations at short to medium time separations (0.2-1 fm), combined with a multistate analysis. On an ensemble with a pion mass of approximately 310 MeV and a lattice spacing of approximately 0.09 fm, we find this provides a more robust and economical method of quantifying and controlling the excited state systematic uncertainty. A quantitative separation of various types of excited states enables the identification of the transition matrix elements as the dominant contamination. The excited state contamination of the Feynman-Hellmann correlation function is found to reduce to the 1% level at approximately 1 fm while, for the more standard three-point functions, this does not occur until after 2 fm. Critical to our findings is the use of a global minimization, rather than fixing the spectrum from the two-point functions and using them as input to the three-point analysis. We find that the ground state parameters determined in such a global analysis are stable against variations in the excited state model, the number of excited states, and the truncation of early-time or late-time numerical data.
| Original language | English |
|---|---|
| Article number | 065203 |
| Journal | Physical Review C |
| Volume | 105 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 2022 |
| Externally published | Yes |
Funding
We thank O. Bär, R. Briceño, R. Gupta, M. Hansen and A. Jackura for enlightening conversations and correspondence. We thank B. Hörz for help cross-checking the three-point code in lalibe and generating some of the results. We thank the MILC Collaboration for use of their HISQ gauge ensembles. Computing time for this work was provided through the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program and the LLNL Multiprogrammatic and Institutional Computing program for Grand Challenge allocations on the LLNL supercomputers. This research utilized the NVIDIA GPU-accelerated Summit supercomputer at Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725 as well as the Lassen supercomputer at Lawrence Livermore National Laboratory, which is operated by the National Nuclear Security Administration of the U.S. Department of Energy under Contract No. DE-AC52-07NA27344. This work was supported in part by the Berkeley Physics International Education Program (J.H.); the Berkeley Laboratory Undergraduate Research Program (I.C.); the NVIDIA Corporation (M.A.C.); the Alexander von Humboldt Foundation through a Feodor Lynen Research Fellowship (C.K.); the U.S. Department of Energy, Office of Science, Office of Nuclear Physics under Awards No. DE-AC02-05CH11231 (C.C.C., C.K., A.W.L.), No. DE-AC52-07NA27344 (D.A.B., D.H., A.S.G., P.V.), No. DE-FG02-93ER-40762 (E.B.), No. DE-AC05-06OR23177 (C.J.M.), and No. DE-SC00046548 (A.S.M.); the DOE Early Career Award Program (A.W.L.); and the U.K. Science and Technology Facilities Council Grants No. ST/S005781/1 and No. ST/T000945/1 (C.B.).