Preparation of one-dimensional chains and dense cold atomic clouds with a high numerical aperture four-lens system - Institut d'Optique Graduate School
Journal Articles Physical Review A Year : 2021

Preparation of one-dimensional chains and dense cold atomic clouds with a high numerical aperture four-lens system

Abstract

We report the efficient and fast ($\sim 2\mathrm{Hz}$) preparation of randomly loaded 1D chains of individual $^{87}$Rb atoms and of dense atomic clouds trapped in optical tweezers using a new experimental platform. This platform is designed for the study of both structured and disordered atomic systems in free space. It is composed of two high-resolution optical systems perpendicular to each other, enhancing observation and manipulation capabilities. The setup includes a dynamically controllable telescope, which we use to vary the tweezer beam waist. A D1 $\Lambda$-enhanced gray molasses enhances the loading of the traps from a magneto-optical trap. Using these tools, we prepare chains of up to $\sim 100$ atoms separated by $\sim 1 \mathrm{\mu m}$ by retro-reflecting the tweezer light, hence producing a 1D optical lattice with strong transverse confinement. Dense atomic clouds with peak densities up to $n_0 = 10^{15}\:\mathrm{at}/\mathrm{cm}^3$ are obtained by compression of an initial cloud. This high density results into interatomic distances smaller than $\lambda/(2\pi)$ for the D2 optical transitions, making it ideal to study light-induced interactions in dense samples.
Fichier principal
Vignette du fichier
2101.07544.pdf (533.54 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-03382766 , version 1 (18-10-2021)

Identifiers

Cite

Antoine Glicenstein, Giovanni Ferioli, Ludovic Brossard, Yvan R. P. Sortais, Daniel Barredo, et al.. Preparation of one-dimensional chains and dense cold atomic clouds with a high numerical aperture four-lens system. Physical Review A, 2021, 103 (4), pp.043301. ⟨10.1103/PhysRevA.103.043301⟩. ⟨hal-03382766⟩
124 View
152 Download

Altmetric

Share

More