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arXiv · 2402.08681

Chain Reaction of Ideas: Can Radioactive Decay Predict Technological Innovation?

Guilherme S. Y. Giardini·Carlo R. da Cunha
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Abstract

This work demonstrates the application of a birth-death Markov process, inspired by radioactive decay, to capture the dynamics of innovation processes. Leveraging the Bass diffusion model, we derive a Gompertz-like function explaining the long-term innovation trends. The validity of our model is confirmed using citation data, Google trends, and a recurrent neural network, which also reveals short-term fluctuations. Further analysis through an automaton model suggests these fluctuations can arise from the inherent stochastic nature of the underlying physics.

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Guilherme S. Y. Giardini, Carlo R. da Cunha. 2024-02-13. Chain Reaction of Ideas: Can Radioactive Decay Predict Technological Innovation?. https://arxiv.org/abs/2402.08681

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