Dual-step optimization for binary sequences with high merit factorsPšeničnik, Blaž (Avtor) Mlinarič, Rene (Avtor) Brest, Janez (Avtor) Bošković, Borko (Avtor) binary sequencesGolay's merit factorautocorrelationalgorithmsThe problem of finding aperiodic low auto-correlation binary sequences (LABS) presents a significant computational challenge, particularly as the sequence length increases. Such sequences have important applications in communication engineering, physics, chemistry, and cryptography. This paper introduces a dual-step algorithm for long binary sequences with high merit factors. The first step employs a parallel algorithm utilizing skew-symmetry and restriction classes to generate sequence candidates with merit factors above a predefined threshold. The second step uses a priority queue algorithm to refine these candidates further, searching the entire search space unrestrictedly. By combining GPU-based parallel computing and dual-step optimization, our approach has successfully identified best-known binary sequences for all lengths ranging from 450 to 527, with the exception of length 518, where the previous best-known merit factor value was matched with a different sequence. This hybrid method significantly outperforms traditional exhaustive and stochastic search methods, offering an efficient solution for finding long sequences with good merit factors.Elsevier Inc.20252025-05-30 11:16:02Članek v reviji93000sl© 2025 The Author(s)