Preparing defect-free atom arrays from stochastically loaded optical tweezers requires efficient rearrangement algorithms, yet practical guides covering the complete pipeline from hardware alignment to executable waveforms remain scarce. To the best of our knowledge, only one open-source framework currently exists that enables the reproduction and benchmarking of existing algorithms while also serving as a development tool 1. This work addresses this practical gap by presenting a guide for rearranging atoms in optical tweezers and extending the existing open-source framework. (1) We present an alignment guide for an acousto-optic deflector (AOD)-based optical setup. (2) We benchmark an image extraction pipeline that identifies the imaging stage as the dominant time constraint, supporting both position-agnostic blob detection and faster threshold detection at calibrated positions. (3) We evaluate thirteen rearrangement algorithms (eleven single-species and two dual-species) under a physically motivated Rydberg-platform noise model, finding in simulation that single-shot rearrangement is unreliable under this noise model for all algorithms and that a closed-loop correction protocol with three to five reimaging rounds restores nearperfect array success for up to 169 target atoms at modest time cost. (4) We develop an analytical error model that decomposes the per-round fill rate into algorithmic efficiency, move-error probability, and vacuum loss, yielding a closed-form expression for the multi-round success probability. (5) We provide an radio frequency (RF) signal generation framework that translates algorithmic move sequences into executable AWG frequency ramps, including four interchangeable DDS execution strategies. All algorithmic and benchmarking results are based on simulation. Experimental validation is the immediate next step.
Kaiser et al. (Thu,) studied this question.