mlsanityData to 7 Oct 2026

Low Autocorrelation Binary Sequences

arXiv 1512.02475 ↗First posted 8 Dec 2015cond-mat.stat-mech math.CO math.OCcited by 10

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Abstract (arXiv)

Binary sequences with minimal autocorrelations have applications in communication engineering, mathematics and computer science. In statistical physics they appear as groundstates of the Bernasconi model. Finding these sequences is a notoriously hard problem, that so far can be solved only by exhaustive search. We review recent algorithms and present a new algorithm that finds optimal sequences of length N in time Theta(N,1.73N). We computed all optimal sequences for N≤ 66 and all optimal skewsymmetric sequences for N≤ 119.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Dec 2015.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 2; 2024: 0; 2025: 5; 2026: 2.

10 papers.

  1. 2023Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spacescited by 27
  2. 2023Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddingscited by 24
  3. 2025SWIFT-FMQA: Enhancing Factorization Machine with Quadratic-Optimization Annealing via Sliding Windowcited by 4
  4. 2025Exact Spin Elimination for Quadratic and k-Local Ising Optimizationcited by 1
  5. 2025Omnipresent Yet Overlooked: Heat Kernels in Combinatorial Bayesian Optimizationcited by 1
  6. 2022Quality-diversity in dissimilarity spacescited by 0
  7. 2025Reconstructing Rational Functions on Finite Abelian Groups with Higher Autocorrelationscited by 0
  8. 2025MOCA-HESP: Meta High-dimensional Bayesian Optimization for Combinatorial and Mixed Spaces via Hyper-ellipsoid Partitioningcited by 0
  9. 2026Prioritizing Search Space Regions in the Low Autocorrelation Binary Sequences Problemcited by 0
  10. 2026ILP-BO: Integer Linear Programming-Based Black-Box Optimizationcited by 0