Chin. Phys. Lett.  2020, Vol. 37 Issue (3): 036701    DOI: 10.1088/0256-307X/37/3/036701
Production of $^{87}$Rb Bose–Einstein Condensate with a Simple Evaporative Cooling Method
Rehman Fazal1, Jia-Zhen Li1, Zhi-Wen Chen1, Yuan Qin1, Ya-Yi Lin1, Zuan-Xian Zhang1, Shan-Chao Zhang1**, Wei Huang1**, Hui Yan1, Shi-Liang Zhu1,2
1Guangdong Provincial Key Laboratory of Quantum Engineering and Quantum Materials, GPETR Center for Quantum Precision Measurement and SPTE, South China Normal University, Guangzhou 510006
2National Laboratory of Solid State Microstructures, School of Physics, Nanjing University, Nanjing 210093
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Rehman Fazal, Jia-Zhen Li, Zhi-Wen Chen et al  2020 Chin. Phys. Lett. 37 036701
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Abstract A Bose–Einstein condensate with a large atom number is an important experimental platform for quantum simulation and quantum information research. An optical dipole trap is the a conventional way to hold the ultracold atoms, where an atomic cloud is evaporatively cooled down before reaching the Bose–Einstein condensate. A carefully designed trap depth controlling curve is typically required to realize the optimal evaporation cooling. We present and demonstrate a simple way to optimize the evaporation cooling in a crossed optical dipole trap. A polyline shape optical power control profile is easily obtained with our method, by which a pure Bose–Einstein condensate with atom number $1.73\times10^5 $ is produced. Theoretically, we numerically simulate the optimal evaporation cooling using the parameters of our apparatus based on a kinetic theory. Compared to the simulation results, our evaporation cooling shows a good performance. We believe that our simple method can be used to quickly realize evaporation cooling in optical dipole traps.
Received: 17 December 2019      Published: 22 February 2020
PACS:  67.85.Hj (Bose-Einstein condensates in optical potentials)  
  37.10.-x (Atom, molecule, and ion cooling methods) (Thermodynamics studies of evaporation and condensation)  
Fund: Supported by the National Key Research and Development Program of China (Grant Nos. 2016YFA0301803 and 2016YFA0302800), the Key-Area Research and Development Program of GuangDong Province (Grant No. 2019B030330001), the National Natural Science Foundation of China (Grant Nos. 61378012, 91636218, 11822403, 11804104, 11804105, 61875060 and U1801661), the Natural Science Foundation of Guangdong Province (Grant Nos. 2018A030313342 and 2018A0303130066), the Key Project of Science and Technology of Guangzhou (Grant No. 201804020055).
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Rehman Fazal
Jia-Zhen Li
Zhi-Wen Chen
Yuan Qin
Ya-Yi Lin
Zuan-Xian Zhang
Shan-Chao Zhang
Wei Huang
Hui Yan
Shi-Liang Zhu
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