Selective Imperfection as a Generative Framework for Analysis, Creativity and Discovery
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Abstract (arXiv)
We introduce materiomusic as a generative framework linking the hierarchical structures of matter with the compositional logic of music. Across proteins, spider webs and flame dynamics, vibrational and architectural principles recur as tonal hierarchies, harmonic progressions, and long-range musical form. Using reversible mappings, from molecular spectra to musical tones and from three-dimensional networks to playable instruments, we show how sound functions as a scientific probe, an epistemic inversion where listening becomes a mode of seeing and musical composition becomes a blueprint for matter. These mappings excavate deep time: patterns originating in femtosecond molecular vibrations or billion-year evolutionary histories become audible. We posit that novelty in science and art emerges when constraints cannot be satisfied within existing degrees of freedom, forcing expansion of the space of viable configurations. Selective imperfection provides the mechanism restoring balance between coherence and adaptability. Quantitative support comes from exhaustive enumeration of all 2^12 musical scales, revealing that culturally significant systems cluster in a mid-entropy, mid-defect corridor, directly paralleling the Hall-Petch optimum where intermediate defect densities maximize material strength. Iterating these mappings creates productive collisions between human creativity and physics, generating new information as musical structures encounter evolutionary constraints. We show how swarm-based AI models compose music exhibiting human-like structural signatures such as small-world connectivity, modular integration, long-range coherence, suggesting a route beyond interpolation toward invention. We show that science and art are generative acts of world-building under constraint, with vibration as a shared grammar organizing structure across scales.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 6 of its 56 references that are in the map. First posted on arXiv 30 Dec 2025.
Builds on
6 of 56 references.
References · 6
- 2024Accelerating Scientific Discovery with Generative Knowledge Extraction, Graph-Based Representation, and Multimodal Intelligent Graph Reasoningcited by 27
- 2025Agentic Deep Graph Reasoning Yields Self-Organizing Knowledge Networkscited by 12
- 2025Swarms of Large Language Model Agents for Protein Sequence Design with Experimental Validationcited by 5
- 2020Liquified protein vibrations, classification and cross-paradigm de novo image generation using deep neural networkscited by 2
- 2023Modeling and design of heterogeneous hierarchical bioinspired spider web structures using generative deep learning and additive manufacturingcited by 2
- 2025MusicSwarm: Biologically Inspired Intelligence for Music Compositioncited by 1
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Citing papers per year: 2026: 2.
2 papers.