Abstract

Finite temperature Euclidean two-point functions in quantum mechanics or quantum field theory are characterized by a discrete set of Fourier coefficients GkG_{k}, k∈Zk\in\mathbb Z, associated with the Matsubara frequencies νk=2πk/βν_{k}=2πk/β. We show that analyticity implies that the coefficients GkG_{k} must satisfy an infinite number of model-independent linear equations that we write down explicitly. In particular, we construct "Analytic Renormalization Group" linear maps Aμ\mathsf A_μ which, for any choice of cut-off μμ, allow to express the low energy Fourier coefficients for ∣νk∣<μ|ν_{k}|<μ (with the possible exception of the zero mode G0G_{0}), together with the real-time correlators and spectral functions, in terms of the high energy Fourier coefficients for ∣νk∣≥μ|ν_{k}|\geqμ. Operating a simple numerical algorithm, we show that the exact universal linear constraints on GkG_{k} can be used to systematically improve any random approximate data set obtained, for example, from Monte-Carlo simulations. Our results are illustrated on several explicit examples.

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