arXiv subjects

René Henke

Publications and source records attributed to René Henke.

3 recordsLinked to original sources

arXiv2025

Realization of repulsive polarons in the strongly correlated regime

Mobile impurities interacting with a quantum medium form quasiparticles known as polarons, a central concept in many-body physics. While the quantum impurity problem has been extensively studied with ultracold atomic gases, repulsive polarons in the strongly correlated regime have remained elusive. Typically, the impurity atoms bind into molecules or rapidly decay into deeper lying states before they can acquire an appreciable dressing cloud. Here, we report on the realization of polarons in a strongly repulsive quasi-two-dimensional quantum gas. Using a superfluid of $^6$Li dimers, we introduce impurities by promoting a small fraction of the dimers into higher levels of the transverse confining potential. These novel synthetic-spin polarons give access to the strongly repulsive regime where common decay channels are suppressed. We extract key polaron properties - the energy, quasiparticle residue, and effective mass - using trap modulation and Bragg spectroscopy. Our measurements are well captured by a microscopic T-matrix approach and quantum Monte Carlo simulations, revealing deviations from mean-field predictions. In particular, we measure a significant enhancement of the polaron mass, with values exceeding twice the free dimer mass. Our demonstration of a stable repulsive Bose polaron establishes a platform for studying impurity physics in low-dimensional and strongly correlated systems.

cond-mat.quant-gas↗

arXiv2025

Hybridization of the amplitude mode in a confined fermionic superfluid

In phase transitions, spontaneous symmetry breaking results in a non-zero order parameter and two collective excitations: the Goldstone and the amplitude mode. These modes, which define key properties of superconductors and fermionic superfluids, are well-understood in homogeneous systems. However, their behavior under strong confinement remains largely unexplored, particularly when their excitation energy becomes comparable to the imposed discrete level spacing. In this scenario, hybridization between different collective modes is expected to take place. Here, we show how the amplitude mode hybridizes with a spatial mode in a confined fermionic superfluid. Using lattice modulation spectroscopy, we observe the evolution of the mode throughout the entire crossover from the Bardeen-Cooper-Schrieffer (BCS) state to Bose-Einstein condensation (BEC) of molecules. In the BCS regime, the excitation energy is located at twice the pairing gap, then gradually becomes an in-gap excitation in the strongly correlated regime. Further to the BEC limit, the excitation energy approaches twice the level spacing. The spectral weight of this mode vanishes when approaching the superfluid critical temperature. Our experimental results are in excellent agreement with an effective field theory, providing strong evidence that amplitude oscillations hybridize with and eventually transform into breathing oscillations of the order parameter. The strong modification of the excitation spectrum reveals how confinement and finite-size effects impact fundamental modes of symmetry-broken states.

cond-mat.quant-gas↗

arXiv2021

Machine learner optimization of optical nanofiber-based dipole traps for cold $^{87}$Rb atoms

In two-color optical nanofiber-based dipole traps for cold alkali atoms, the trap efficiency depends on the wavelength and intensity of light in the evanescent field, and the initial laser-cooling process. Typically, no more than one atom can be trapped per trapping site. Improving the trapping efficiency can increase the number of filled trapping sites, thereby increasing the optical depth. Here, we report on the implementation of an in-loop stochastic artificial neural network machine learner to trap $^{87}$Rb atoms in an uncompensated two-color evanescent field dipole trap by optimizing the absorption of a near-resonant, nanofiber-guided, probe beam. By giving the neural network control of the laser cooling process, we observe an increase in the number of dipole-trapped atoms by $\sim$ 50%, a small decrease in their average temperature from 150 $μ$K to 140 $μ$K, and an increase in peak optical depth by 70%. The machine learner is able to quickly and effectively explore the large parameter space of the laser cooling control to find optimal parameters for loading the dipole traps. The increased number of atoms should facilitate studies of collective atom-light interactions mediated via the evanescent field.

physics.atom-ph↗