Automatic differentiation for error analysis
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We present ADerrors.jl, a software for linear error propagation and analysis of Monte Carlo data. Although the focus is in data analysis in Lattice QCD, where estimates of the observables have to be computed from Monte Carlo samples, the software also deals with variables with uncertainties, either correlated or uncorrelated. Thanks to automatic differentiation techniques linear error propagation is performed exactly, even in iterative algorithms (i.e. errors in parameters of non-linear fits). In this contribution we present an overview of the capabilities of the software, including access to uncertainties in fit parameters and dealing with correlated data. The software, written in julia, is available for download and use in https://gitlab.ift.uam-csic.es/alberto/aderrors.jl
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Precision renormalisation and improvement of $N_{\rm f}=3$ lattice QCD with Wilson fermions
New non-perturbative renormalization and improvement results for currents and masses in Nf=3 O(a)-improved Wilson QCD at small a using Schrödinger functional boundary conditions and gradient flow tuning.
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