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Tackling the Sign Problem in the Doped Hubbard Model with Normalizing Flows

Dominic Schuh, Lena Funcke, Janik Kreit, Thomas Luu, Simran Singh

Abstract

The Hubbard model at finite chemical potential is a cornerstone for understanding doped correlated systems, but simulations are severely limited by the sign problem. In the auxiliary-field formulation, the spin basis mitigates the sign problem, yet severe ergodicity issues have limited its use. We extend recent advances with normalizing flows at half-filling to finite chemical potential by introducing an annealing scheme enabling ergodic sampling. Compared to state-of-the-art hybrid Monte Carlo in the charge basis, our approach accurately reproduces exact diagonalization results while reducing statistical uncertainties by an order of magnitude, opening a new path for simulations of doped correlated systems.

Tackling the Sign Problem in the Doped Hubbard Model with Normalizing Flows

Abstract

The Hubbard model at finite chemical potential is a cornerstone for understanding doped correlated systems, but simulations are severely limited by the sign problem. In the auxiliary-field formulation, the spin basis mitigates the sign problem, yet severe ergodicity issues have limited its use. We extend recent advances with normalizing flows at half-filling to finite chemical potential by introducing an annealing scheme enabling ergodic sampling. Compared to state-of-the-art hybrid Monte Carlo in the charge basis, our approach accurately reproduces exact diagonalization results while reducing statistical uncertainties by an order of magnitude, opening a new path for simulations of doped correlated systems.
Paper Structure (1 section, 26 equations, 8 figures)

This paper contains 1 section, 26 equations, 8 figures.

Table of Contents

  1. End Matter

Figures (8)

  • Figure 1: Schematic illustration of the annealing procedure controlled by the parameter $\lambda$. At $\lambda=0$, the fermion determinant is absent and the target distribution is Gaussian. As $\lambda$ is increased, fermionic effects are gradually introduced, deforming the distribution until the full interacting Hubbard action with its multimodal structure is recovered at $\lambda=1$.
  • Figure 2: Average sign $\Sigma$ as a function of the chemical potential $\mu$ for an eight-site hexagonal lattice with $U = 2$, $\beta = 8$, and $N_t = 16$. Shown are results from the annealing-based NF approach in the spin basis (NF SP, yellow) and optimized HMC simulations in the charge basis Gantgen:2023byf (O+HMC CH, grey).
  • Figure 3: One-body correlation functions for an eight-site hexagonal lattice with $U=2$, $\beta=8$, $\mu=1.75$, and $N_t=40$. Shown are continous exact diagonalization results (ED, grey dashed), state-of-the-art optimized HMC in the charge basis (O+HMC CH, grey), and our annealing-based NF ansatz in the spin basis (NF SP, yellow). Both HMC and NF results are generated with 1M samples each.
  • Figure 4: One-body correlation functions for an 18-site hexagonal lattice with $U=2$, $\beta=8$, $\mu=2.5$, and $N_t=40$. Shown are state-of-the-art optimized HMC in the charge basis (O+HMC CH, grey) and our annealing-based NF ansatz in the spin basis (NF SP, yellow). Both HMC and NF results are generated with 1M samples each.
  • Figure 5: Distribution of the two-site Hubbard model in the spin basis ($U=3$, $\beta=5$, and $N_t$=20) for $\mu=0$ (left) and $\mu=2$ (right). Shown are the fields summed over the temporal direction, i.e., $\phi_x = \sum_{t=0}^{N_t-1} \phi_{xt}$.
  • ...and 3 more figures