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Stochastic reconstructions of spectral functions: Application to lattice QCD

H.-T. Ding, O. Kaczmarek, Swagato Mukherjee, H. Ohno, and H.-T. Shu
Phys. Rev. D 97, 094503 – Published 10 May 2018

Abstract

We present a detailed study of the applications of two stochastic approaches, stochastic optimization method (SOM) and stochastic analytical inference (SAI), to extract spectral functions from Euclidean correlation functions. SOM has the advantage that it does not require prior information. On the other hand, SAI is a more generalized method based on Bayesian inference. Under mean field approximation SAI reduces to the often-used maximum entropy method (MEM) and for a specific choice of the prior SAI becomes equivalent to SOM. To test the applicability of these two stochastic methods to lattice QCD, firstly, we apply these methods to various reasonably chosen model correlation functions and present detailed comparisons of the reconstructed spectral functions obtained from SOM, SAI and MEM. Next, we present similar studies for charmonia correlation functions obtained from lattice QCD computations using clover-improved Wilson fermions on large, fine, isotropic lattices at 0.75 and 1.5Tc, Tc being the deconfinement transition temperature of a pure gluon plasma. We find that SAI and SOM give consistent results to MEM at these two temperatures.

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  • Received 22 December 2017

DOI:https://doi.org/10.1103/PhysRevD.97.094503

© 2018 American Physical Society

Physics Subject Headings (PhySH)

Particles & Fields

Authors & Affiliations

H.-T. Ding1, O. Kaczmarek1,2, Swagato Mukherjee3, H. Ohno3,4, and H.-T. Shu1

  • 1Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics, Central China Normal University, Wuhan 430079, China
  • 2Fakultät für Physik, Universität Bielefeld, D-33615 Bielefeld, Germany
  • 3Physics Department, Brookhaven National Laboratory, Upton, New York 11973, USA
  • 4Center for Computational Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8577, Japan

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Issue

Vol. 97, Iss. 9 — 1 May 2018

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