11,011 research outputs found
Regression with strongly correlated data
This paper discusses linear regression of strongly correlated data that
arises, for example, in magnetohydrodynamic equilibrium reconstructions. We
have proved that, generically, the covariance matrix of the estimated
regression parameters for fixed sample size goes to zero as the correlations
become unity. That is, in this limit the estimated parameters are known with
perfect accuracy. Simple examples are shown to illustrate this effect and the
nature of the exceptional cases in which the estimate covariance does not go to
zero
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Argentina's recovery and "excess" capital shallowing of the 1990s
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Parity-expanded variational analysis for non-zero momentum
In recent years, the use of variational analysis techniques in lattice QCD
has been demonstrated to be successful in the investigation of the rest-mass
spectrum of many hadrons. However, due to parity-mixing, more care must be
taken for investigations of boosted states to ensure that the projected
correlation functions provided by the variational analysis correspond to the
same states at zero momentum. In this paper we present the Parity-Expanded
Variational Analysis (PEVA) technique, a novel method for ensuring the
successful and consistent isolation of boosted baryons through a parity
expansion of the operator basis used to construct the correlation matrix.Comment: 9 pages, 3 figures, 1 tabl
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