NegaBent, No Regrets: Evolving Spectrally Flat Boolean Functions

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Authors: Claude Carlet, Marko Ðurasević, Ermes Franch, Domagoj Jakobović, Luca Mariot, Stjepan Picek
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Abstract

Negabent Boolean functions are defined by having a flat magnitude spectrum under the nega-Hadamard transform. They exist in both even and odd dimensions, and the subclass of functions that are simultaneously bent and negabent (bent-negabent) has attracted interest due to the combined optimal periodic and negaperiodic spectral properties. In this work, we investigate how evolutionary algorithms can be used to evolve (bent-)negabent Boolean functions. Our experimental results indicate that evolutionary algorithms, especially genetic programming, are a suitable approach for evolving negabent Boolean functions, and we successfully evolve such functions in all dimensions we consider.

Fields of Study & Subjects

Evolutionary Algorithms and Applications Coding theory and cryptography Metaheuristic Optimization Algorithms Research

Publication details

Journal / source
Genetic and Evolutionary Computation Conference Companion (GECCO Companion)
Pages
589–592
Publication date
13 July 2026
Language
EN