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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
Forward citations
Cited by 2 Pith papers
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Hybrid static potentials and gluelumps on $N_f=3+1$ ensembles
New lattice QCD measurements of hybrid static potentials, static-light thresholds, and gluelump masses on N_f=3+1 ensembles with pions near 420 MeV, using Laplace trial states.
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Parallel Tempered Metadynamics for full QCD
In N_f=2 staggered QCD at beta=1.15, PT-MetaD tunnels between topological sectors while RHMC remains frozen, yielding chi_top V = 0.127(33).
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