Λ-Enhanced Gray Molasses Temperature Extraction

[Mattia Fiore]

Good morning,

I am currently working on optimizing Λ-enhanced grey molasses cooling for Rb-87 and extracting the associated temperatures as a function of the cooling parameters. Following the instructions in 04_Lambda_Enhanced_Cooling.ipynb, I have been modelling the three-level system and attempting to extract temperatures from the velocity distribution using v final, similar to the approach in 00_two_level_1D_molasses.ipynb.

My goal as a starting point is to reproduce the temperature trend shown in Fig. 2 of 'Λ -enhanced sub-Doppler cooling of lithium atoms in D1 gray molasses' Physical Review A 87, 063411 (2013) and then transition to Rb, but so far, my results have been imprecise. I have also attempted to implement a more complex Hamiltonian that accounts for the hyperfine structure, but this approach has proven to be computationally expensive.

Additionally, I came across the paper "Λ-Enhanced Gray Molasses in a Tetrahedral Laser Beam Geometry," which discusses pylcp temperature extraction in a similar setup. However, I could not find any publicly available code. Would you happen to know if there is any existing implementation that I could refer to, or could you provide any insights into how the temperature extraction was performed in that work?

Thank you in advance for your time and help.

Mattia

[Barker, Daniel S. (Fed)]

Hello Mattia,

 

I will dig up the code that I used for the tetrahedral gray molasses paper next week and share it with you. I can also say that getting unbiased temperatures from OBE lambda-enhanced cooling simulations was a bit tricky since lambda-enhanced cooling is sub-recoil limited.

 

The main tricks to getting reasonable temperatures were:

1. Using a binning method that did not assume a Gaussian distribution when creating the bins.
2. Fitting the histogram to both unimodal and bimodal Gaussians, and then using an information criterion to decide the best model.

 

I’d be happy to discuss further once I’ve looked at the code again to remember exactly how I approached the problem.

 

Daniel

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