Computational and Biological Analogies for Understanding Fine-Tuned Parameters in Physics
Clement Vidal

TL;DR
This philosophical paper investigates how computational and biological analogies can shed light on the fine-tuning problem in cosmology, emphasizing their usefulness and limitations in understanding physical constants and initial conditions.
Contribution
It introduces a nuanced analysis of computational and biological analogies for the fine-tuning problem, including preliminary studies and discussions on their interpretative potential and risks.
Findings
Analogies are valuable cognitive tools but can be misused.
The universe may be modeled as a computational entity.
Extensions of biological analogy, like intelligent life, are discussed for their legitimacy.
Abstract
In this philosophical paper, we explore computational and biological analogies to address the fine-tuning problem in cosmology. We first clarify what it means for physical constants or initial conditions to be fine-tuned. We review important distinctions such as the dimensionless and dimensional physical constants, and the classification of constants proposed by Levy-Leblond. Then we explore how two great analogies, computational and biological, can give new insights into our problem. This paper includes a preliminary study to examine the two analogies. Importantly, analogies are both useful and fundamental cognitive tools, but can also be misused or misinterpreted. The idea that our universe might be modelled as a computational entity is analysed, and we discuss the distinction between physical laws and initial conditions using algorithmic information theory. Smolin introduced the…
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