134 citations · 202 across the 7 of their papers we have counts for
7 papers
Hadronic contributions to and from spectral reconstruction of lattice-QCD data
Adrián del Pino, David A. Clarke, Carleton DeTar +17
We present preliminary results from a lattice-QCD study of the hadronic contributions to the running of the electromagnetic coupling, , and the electroweak mixing angle, $…
High-Precision Scale Setting with the Omega-Baryon Mass and Gradient Flow
Alexei Bazavov, Claude W. Bernard, David A. Clarke +23
The gradient-flow scale in lattice QCD is determined using the mass of the baryon to set the physical scale. Nine ensembles using the highly improved staggered quark (H…
The anomalous magnetic moment of the muon in the Standard Model: an update
R. Aliberti, T. Aoyama, E. Balzani +232
We present the current Standard Model (SM) prediction for the muon anomalous magnetic moment, , updating the first White Paper (WP20) [1]. The pure QED and electroweak contrib…
Hadronic vacuum polarization for the muon from lattice QCD: Long-distance and full light-quark connected contribution
Alexei Bazavov, Claude W. Bernard, David A. Clarke +22
We present results for the dominant light-quark connected contribution to the long-distance window (LD) of the hadronic vacuum polarization contribution (HVP) to the muon fro…
Hadronic vacuum polarization for the muon from lattice QCD: Complete short and intermediate windows
Alexei Bazavov, David A. Clarke, Christine Davies +21
We present complete results for the hadronic vacuum polarization (HVP) contribution to the muon anomalous magnetic moment in the short- and intermediate-distance window regio…
Model averaging approaches to data subset selection
Ethan T. Neil, Jacob W. Sitison
Model averaging is a useful and robust method for dealing with model uncertainty in statistical analysis. Often, it is useful to consider data subset selection at the same time, in…
Improved information criteria for Bayesian model averaging in lattice field theory
Ethan T. Neil, Jacob W. Sitison
Bayesian model averaging is a practical method for dealing with uncertainty due to model specification. Use of this technique requires the estimation of model probability weights.…