Eleonora Lippi, Manuel Gerken, Stephan Häfner, Marc Repp, Rico Pires, Michael Rautenberg, Tobias Krom, Eva D. Kuhnle, Binh Tran, Juris Ulmanis, Bing Zhu, Lauriane Chomaz, Matthias Weidemüller
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引用次数: 0
Abstract
We present the experimental apparatus enabling the observation of the heteronuclear Efimov effect in an optically trapped ultracold mixture of \(^6\)Li-\(^{133}\)Cs with high-resolution control of the interactions. A compact double-species Zeeman slower consisting of four interleaving helical coils allows for a fast-switching between two optimized configurations for either Li or Cs and provides an efficient sequential loading into their respective MOTs. By means of a bichromatic optical trapping scheme based on species-selective trapping we prepare mixtures down to 100 nK of \({1\times 10^{4}}\) Cs atoms and \({7\times 10^{3}}\) Li atoms. Highly stable magnetic fields allow high-resolution atom-loss spectroscopy and enable to resolve splitting in the loss feature of a few tens of milligauss. These features allowed for a detailed study of the Efimov effect.
期刊介绍:
The journal Few-Body Systems presents original research work – experimental, theoretical and computational – investigating the behavior of any classical or quantum system consisting of a small number of well-defined constituent structures. The focus is on the research methods, properties, and results characteristic of few-body systems. Examples of few-body systems range from few-quark states, light nuclear and hadronic systems; few-electron atomic systems and small molecules; and specific systems in condensed matter and surface physics (such as quantum dots and highly correlated trapped systems), up to and including large-scale celestial structures.
Systems for which an equivalent one-body description is available or can be designed, and large systems for which specific many-body methods are needed are outside the scope of the journal.
The journal is devoted to the publication of all aspects of few-body systems research and applications. While concentrating on few-body systems well-suited to rigorous solutions, the journal also encourages interdisciplinary contributions that foster common approaches and insights, introduce and benchmark the use of novel tools (e.g. machine learning) and develop relevant applications (e.g. few-body aspects in quantum technologies).