We present efficient implementations of atom reconfiguration algorithms for both CPUs and GPUs, along with a batching routine to merge displacement operations for parallel execution. Leveraging graph-theoretic methods, our approach derives improved algorithms that achieve reduced time complexity and faster operational running times. First, we introduce an enhanced version of the redistribution-reconfiguration (red-rec) algorithm, which offers superior operational and runtime performance. We detail its efficient implementation on a GPU using a parallel approach. Next, we present an optimized version of the assignment-reconfiguration-ordering (aro) algorithm, specifically tailored for unweighted grid graphs. Finally, we introduce the bird algorithm to solve reconfiguration problems on grids, achieving performance gains over both red-rec and aro. These algorithms can be used to prepare defect-free configurations of neutral atoms in arrays of optical traps, serve as subroutines in more complex algorithms, or cross-benchmark the operational and runtime performance of new algorithms. They are suitable for realizing quantum circuits incorporating displacement operations and are optimized for real-time operation on increasingly large system sizes.
@article{arxiv.2504.06182,
title = {Efficient algorithms to solve atom reconfiguration problems. III. The bird and batching algorithms and other parallel implementations on GPUs},
author = {Fouad Afiouni and Remy El Sabeh and Naomi Nishimura and Izzat El Hajj and Amer E. Mouawad and Alexandre Cooper},
journal= {arXiv preprint arXiv:2504.06182},
year = {2025}
}