Gradient-Based Inverse Optimization of Atom-Chip Wire Currents for BEC Transport

Abstract

Modulating wire currents to shift a magnetic trap along an atom chip enables smooth contact-free delivery of Bose-Einstein condensates but can deform the confinement profile causing parametric heating and atom loss. We introduce a fast simulation framework based on inverse optimization that, given an initial trap and a predefined trajectory over time, computes a wire current schedule that transports the atoms and restores the trap geometry upon arrival. We assess trap's minimum energy, lateral displacement, confinement profile and an adiabaticity parameter over a 2.4 mm trajectory for various transport durations between 2s and 5s, demonstrating the trade-off between speed and adiabaticity.