Radio-frequency driving of an attractive Fermi gas in a one-dimensional optical lattice

TL;DR

This paper explores how radio-frequency driving affects an attractive Fermi gas in a 1D optical lattice, revealing different dynamical regimes and providing insights into many-body excitations and non-equilibrium physics through experimental and simulation methods.

Contribution

It introduces a combined experimental and theoretical approach to study non-equilibrium dynamics of attractive Fermi gases under RF driving, linking transfer rates to spectral functions and pair correlations.

Findings

Identification of two dynamical regimes: Rabi-like oscillations and linear rise.

Connection of transfer rate to single-particle spectral function via linear response.

Observation of non-equilibrium pair correlation dynamics during RF drive.

Abstract

We investigate the response to radio-frequency driving of an ultracold gas of attractively interacting fermions in a one-dimensional optical lattice. We study the system dynamics by monitoring the driving-induced population transfer to a third state, and the evolution of the momentum density and pair distributions. Depending on the frequency of the radio-frequency field, two different dynamical regimes emerge when considering the evolution of the third level population. One regime exhibits (off)resonant many-body oscillations reminiscent of Rabi oscillations in a discrete two-level system, while the other displays a strong linear rise. Within this second regime, we connect, via linear response theory, the extracted transfer rate to the system single-particle spectral function, and infer the nature of the excitations from Bethe ansatz calculations. In addition, we show that this radio-frequency technique can be employed to gain insights into this many-body system coupling mechanism away from equilibrium. This is done by monitoring the momentum density redistributions and the evolution of the pair correlations during the drive. Capturing such non-equilibrium physics goes beyond a linear response treatment, and is achieved here by conducting time-dependent matrix product state simulations.