26 July 2026 to 1 August 2026
University of Maryland, College Park
US/Eastern timezone

Leveraging Existing HISQ Eigenvectors for Improved Statistical Precision in the HVP Contribution to muon g-2

31 Jul 2026, 16:10
20m
Pyon Su (Adele H. Stamp Student Union)

Pyon Su

Adele H. Stamp Student Union

3972 Campus Dr, College Park, MD 20742
Contributed talk Quark and lepton flavor physics Quark and lepton flavor physics

Speaker

Vaishakhi Moningi (University of Connecticut)

Description

The low-mode contribution to the hadronic vacuum polarization dominates the total statistical error, making its efficient computation a critical bottleneck in lattice QCD determinations of the muon anomalous magnetic moment. We present and validate a strategy that leverages already available Fermilab Lattice/HPQCD/MILC HISQ eigenvectors to improve the statistics of our existing fat link calculation without generating new eigenvectors (except a small number for bias correction). Using the decomposition $D_{HISQ} = D_{Fat} + D_{Naik}$ for the HISQ Dirac operator, fat-link correlators are reconstructed from the known HISQ eigensystem at negligible, or no additional cost. We use an AMA-style bias correction computed on a small set of configurations to eliminate the systematic difference between the two actions. We demonstrate the method on a $48^3$, a=0.12 fm ensemble and then turn to the application of the method to a larger $144^3$, a=0.042 fm ensemble. Both ensembles are from the MILC collaboration.

Authors

Vaishakhi Moningi (University of Connecticut) thomas blum (University of Connecticut)

Co-authors

Prof. Christopher Aubin (Fordham University) Luchang Jin (Univeristy of Connecticut) Maarten Golterman (San Francisco State University) Santi Peris

Presentation materials

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