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September 28, 20250 citationsOpen Access

On the Fitness Landscape in the NK Model

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WCW. L. ChenSTSi Tang

Key Points

  • The nk model exhibits a multiple-peak structure in the fitness landscape, suggesting many near-fittest genomes.
  • Exact limits for free energy and maximum fitness are identified using spin glass methodologies at any temperature.
  • The model shows that near-fittest evolutionary paths become impossible as fitness levels approach the global maximum.
  • Choosing a sufficiently small alpha allows the construction of evolutionary paths maintained at a given fitness level.

Abstract

The NK model, introduced by Kauffman, Levin, and Weinberger, is a random field used to describe the fitness landscape of certain species with N genetic loci, each interacting with K others. The model has wide applications in understanding evolutionary and natural selection as it captures ruggedness feature of the fitness landscape. Earlier literature has been focused on the case K being a fixed positive integer and used tools from Ergodic and Markov theory. In this paper, by viewing it as a statistical physics object, we investigate the NK model in the regime K/Nα (0, 1] via the spin glass methodologies. Our main result identifies the exact limits for the free energy at any temperature and the maximum fitness. Moreover, we show that the NK model exhibits a multiple-peak structure, namely, the number of near-fittest genomes that are asymptotically orthogonal to each other is exponentially large. Based on establishing the overlap gap properties, we obtain quantitative descriptions for the geometry of the fitness landscape and deduce that, in particular, near-fittest evolutionary paths become impossible as the fitness levels of the genomes approach the global maximum for any α (0, 1]. Nevertheless, we also show that by choosing α sufficiently small, an evolutionary path maintained at a given fitness level can be constructed with high probability.

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Cite This Study

Chen et al. (2025) studied this question.

synapsesocial.com/papers/68d913a34ddcf71ba560b7f7https://doi.org/10.48550/arxiv.2508.12464
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