Reducing the number of qubits in quantum simulations of one dimensional many-body Hamiltonians

TL;DR

This paper demonstrates that the Block Renormalization Group Method can significantly reduce the number of qubits needed to simulate one-dimensional many-body Hamiltonians like the Ising and Heisenberg models, while preserving key physical features.

Contribution

It introduces and validates the effectiveness of BRGM in accurately simulating large quantum systems with fewer qubits, especially for the Ising model, facilitating quantum simulations on NISQ devices.

Findings

BRGM reduces spins by 1/2 for Ising and 1/3 for Heisenberg models.

Exponential convergence observed between original and renormalized Ising results with increasing system size.

Exact correspondence of physical features for a 24-spin Ising chain between original and renormalized models.

Abstract

We investigate the Ising and Heisenberg models using the Block Renormalization Group Method (BRGM), focusing on its behavior across different system sizes. The BRGM reduces the number of spins by a factor of 1/2 (1/3) for the Ising (Heisenberg) model, effectively preserving essential physical features of the model while using only a fraction of the spins. Through a comparative analysis, we demonstrate that as the system size increases, there is an exponential convergence between results obtained from the original and renormalized Ising Hamiltonians, provided the coupling constants are redefined accordingly. Remarkably, for a spin chain with 24 spins, all physical features, including magnetization, correlation function, and entanglement entropy, exhibit an exact correspondence with the results from the original Hamiltonian. The study of the Heisenberg model also shows this tendency, although complete convergence may appear for a size much larger than 24 spins, and is therefore beyond our computational capabilities. The success of BRGM in accurately characterizing the Ising model, even with a relatively small number of spins, underscores its robustness and utility in studying complex physical systems, and facilitates its simulation on current NISQ computers, where the available number of qubits is largely constrained.