Physics – Condensed Matter – Quantum Gases
Scientific paper
2011-07-12
Physics
Condensed Matter
Quantum Gases
13 pages, 6 figures, version 3 published in PRA - Volume 84, Page 043648
Scientific paper
10.1103/PhysRevA.84.043648
We present a method for rapid prototyping of new Bragg ultra-cold atom interferometer (AI) designs useful for assessing the performance of such interferometers. The method simulates the overall effect on the condensate wave function in a given AI design using two separate elements. These are (1) modeling the effect of a Bragg pulse on the wave function and (2) approximating the evolution of the wave function during the intervals between the pulses. The actual sequence of these pulses and intervals is then followed to determine the approximate final wave function from which the interference pattern can be calculated. The exact evolution between pulses is assumed to be governed by the Gross-Pitaevskii (GP) equation whose solution is approximated using a Lagrangian Variational Method to facilitate rapid prototyping. The method presented here is an extension of an earlier one that was used to analyze the results of an experiment [J.E. Simsarian, et al., Phys. Rev. Lett. 83, 2040 (2000)], where the phase of a Bose-Einstein condensate was measured using a Mach- Zehnder-type Bragg AI. We have developed both 1D and 3D versions of this method and we have determined their validity by comparing their predicted interference patterns with those obtained by numerical integration of the 1D GP equation and with the results of the above experiment. We find excellent agreement between the 1D interference patterns predicted by this method and those found by the GP equation. We show that we can reproduce all of the results of that experiment without recourse to an ad hoc velocity-kick correction needed by the earlier method, including some experimental results that the earlier model did not predict. We also found that this method provides estimates of 1D interference patterns at least four orders-of-magnitude faster than direct numerical solution of the 1D GP equation.
Benton Brandon
Clark Charles W.
Edwards Mark
Heward Jeffrey
Krygier Michael
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