Beauty and structural complexity

Samy Lakhal (1) , Alexandre Darmon , Jean-Philippe Bouchaud (2) , Michael Benzaquen (1, 2)

1 LadHyX - Laboratoire d'hydrodynamique
2 CFM - Capital Fund Management

We revisit the long-standing question of the relation between image appreciation and its statistical properties. We generate two different sets of random images well distributed along three measures of entropic complexity. We run a large-scale survey in which people are asked to sort the images by preference, which reveals maximum appreciation at intermediate entropic complexity. We show that the algorithmic complexity of the coarse-grained images, expected to capture structural complexity while abstracting from high frequency noise, is a good predictor of preferences. Our analysis suggests that there might exist some universal quantitative criteria for aesthetic judgement.

Domaines: Physique [physics]; Mécanique statistique [cond-mat.stat-mech]

Samy Lakhal, Alexandre Darmon, Jean-Philippe Bouchaud, Michael Benzaquen. Beauty and structural complexity. Physical Review Research, 2020. ⟨hal-02323024⟩