2D MOT with a thermal source

[Vladimir Schkolnik]

Hi, I am planning to simulate a 2D MOT with atoms generated by a  source outside the MOT center. Has someone maybe successfully tried this and can share his code or give some tips?

Best

[Barker, Daniel S. (Fed)]

Hi Vladimir,

 

I apologize for taking so long to respond to this.

 

You’ve probably already figured out any problems that you had, but if not:

We’ve done a decent amount of capture/escape simulations of 3D MOTs, so the code certainly supports what you’re trying to do. I would suggest working from the F=0->F=1 MOT capture example: https://python-laser-cooling-physics.readthedocs.io/en/latest/examples/MOTs/01_F0_to_F1_1D_MOT_capture.html. You can then modify the lasers and level structure as needed to get to the target atom/geometry. This example should help with that: https://python-laser-cooling-physics.readthedocs.io/en/latest/examples/MOTs/06_real_atoms_3D_MOT.html.

 

If you need/want to estimate capture fraction from the thermal source then you can initialize the atoms in pylcp by sampling from a thermal distribution. I’ve had success with this using https://numpy.org/doc/stable/reference/random/generated/numpy.random.multivariate_normal.html.

 

Daniel

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[Manuel Morgado]

(I hope this could be a right place to write)

Hi Daniel,

I was looking the example of MOT capture, seems that k vector and Gamma decay are defined in a previous cell to this:

# Use the heuristic equation (or comment it out): 

eqn = pylcp.heuristiceq(laserBeams, magField, gamma=1, mass=mass)

pylcp.heuristiceq() takes gamma and k as arguments, both set to 1 by default, does not this require to have the values defined previously? I am confuse because the plots shown in the example seemed to be fine.

Thanks for you input!

Cheers,

manuel

[Eckel, Stephen P. (Fed)]

Hi Manuel,

 

Sorry for the confusing notation.  It’s unfortunate that we use the same variable names as we do keyword arguments.  The math in cell #2 of the example is just to determine the natural time and length scales of the problem: t0 and x0.  In cell #3, we define the laser beams and the governing equations, and we set gamma and k equal to one in these cases to solve the problem using the natural time and length scales of the problem.

 

In other words, it is most efficient to solve the problem in a set of units that makes gamma=1 and k=1 (the arguments we pass to the laser beams and heuristic equation in cell #3).  But in order to put the results back into useful units, we must know the timescale and distance that make gamma=1 and k=1.  These are evaluated in cell #2.  I’ll also point out there is a natural mass scale to, which is the mass variable in cell #2. 

 

More details about the natural units can be found in the pylcp paper.

 

Hope that helps!

 

-Steve

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