Robust stripes in the mixed-dimensional $t-J$ model

TL;DR

This paper investigates stripe order in a mixed-dimensional $t-J$ model, revealing stable stripe phases with high critical temperatures and hidden spin correlations, which could inform understanding of high-temperature superconductivity.

Contribution

It introduces a mixed-dimensional $t-J$ model exhibiting stable stripe phases with high critical temperatures, highlighting hidden spin correlations and potential for quantum simulation.

Findings

Stable vertical stripe phase without pairing

High critical temperatures around $J/2$

Enhanced antiferromagnetic correlations in the magnetic background

Abstract

Microscopically understanding competing orders in strongly correlated systems is a key challenge in modern quantum many-body physics. For example, the origin of stripe order and its relation to pairing in the Fermi-Hubbard model remains one of the central questions, and may help to understand the origin of high-temperature superconductivity in cuprates. Here, we analyze stripe formation in the doped mixed-dimensional (mixD) variant of the $t-J$ model, where charge carriers are restricted to move only in one direction, whereas magnetic SU(2) interactions are two-dimensional. Using the density matrix renormalization group at finite temperature, we find a stable vertical stripe phase in the absence of pairing, featuring incommensurate magnetic order and long-range charge density wave profiles over a wide range of dopings. We find high critical temperatures on the order of the magnetic coupling $\sim J/2$, hence being within reach of current quantum simulators. Snapshots of the many-body state, accessible to quantum simulators, reveal hidden spin correlations in the mixD setting, whereby antiferromagnetic correlations are enhanced when considering purely the magnetic background. The proposed model can be viewed as realizing a parent Hamiltonian of the stripe phase, whose hidden spin correlations lead to the predicted resilience against quantum and thermal fluctuations.