English

Estimating energy levels from lattice QCD correlation functions using a transfer matrix formalism

High Energy Physics - Lattice 2025-06-25 v2 High Energy Physics - Phenomenology High Energy Physics - Theory Nuclear Theory

Abstract

We present an efficient method for extracting energy levels from lattice QCD correlation functions by computing the eigenvalues of the transfer matrix associated with the lattice QCD Hamiltonian. While mathematically and numerically equivalent to the recently introduced Lanczos procedure, our approach introduces a novel prescription for removing spurious eigenvalues using a kernel density estimator (KDE) and Gaussian-convoluted histogram method. This strategy yields a robust and stable estimate of the energy spectrum, outperforming the Cullum-Willoughby filtering technique in efficiency. In addition, we detail how this method can be applied to extract overlap factors from two-point correlation functions, as well as matrix elements from three-point functions with a current insertion. Furthermore, we extend the methodology to accommodate correlation matrices constructed from a variational basis of operators, with its Block formulation. We demonstrate the efficacy of this framework by computing the two lowest energy levels for a broad range of hadrons, including several nuclei. Although the signal-to-noise ratio is not significantly improved, the extracted energy levels are found to be more reliable than those obtained with conventional techniques. Within a given statistical ensemble, the proposed method effectively captures both statistical uncertainties and systematic errors, including those arising from the choice of fitting window, making it a robust and practical tool for lattice QCD analysis.

Keywords

Cite

@article{arxiv.2412.01900,
  title  = {Estimating energy levels from lattice QCD correlation functions using a transfer matrix formalism},
  author = {Debsubhra Chakraborty and Dhruv Sood and Archana Radhakrishnan and Nilmani Mathur},
  journal= {arXiv preprint arXiv:2412.01900},
  year   = {2025}
}

Comments

27 pages, 24 figures, Adaptive KDE method is introduced for filtration of spurious eigenvalues

R2 v1 2026-06-28T20:20:23.687Z