The reconstruction of spectral functions from Euclidean correlation functions
is a well-known, yet ill-posed inverse problem in the fields of many-body and
high-energy physics. In this paper, we present a comprehensive investigation of
two recently developed analytic continuation methods, namely stochastic pole
expansion and Nevanlinna analytic continuation, for extracting spectral
functions from mock lattice QCD data. We examine a range of Euclidean
correlation functions generated by representative models, including the
Breit-Wigner model, the Gaussian mixture model, the resonance-continuum model,
and the bottomonium model. Our findings demonstrate that the stochastic pole
expansion method, when combined with the constrained sampling algorithm and the
self-adaptive sampling algorithm, successfully recovers the essential features
of the spectral functions and exhibits excellent resilience to noise of input
data. In contrast, the Nevanlinna analytic continuation method suffers from
numerical instability, often resulting in the emergence of spurious peaks and
significant oscillations in the high-energy regions of the spectral functions,
even with the application of the Hardy basis function optimization algorithm.Comment: 14 pages, 8 figure