Optimization and variability can coexist

Marianne Bauer; William Bialek; Chase Goddard; Caroline M. Holmes; Kamesh Krishnamurthy; Stephanie E. Palmer; Rich Pang; David J. Schwab; Lee Susman

arXiv · 2505.23398

Optimization and variability can coexist

Marianne Bauer·William Bialek·Chase Goddard·Caroline M. Holmes·Kamesh Krishnamurthy·Stephanie E. Palmer·Rich Pang·David J. Schwab·Lee Susman

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Abstract

Many biological systems perform close to their physical limits, but promoting this optimality to a general principle seems to require implausibly fine tuning of parameters. Using examples from a wide range of systems, we show that this intuition is wrong. Near an optimum, functional performance depends on parameters in a "sloppy'' way, with some combinations of parameters being only weakly constrained. Absent any other constraints, this predicts that we should observe widely varying parameters, and we make this precise: the entropy in parameter space can be extensive even if performance on average is very close to optimal. This removes a major objection to optimization as a general principle, and rationalizes the observed variability.

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Marianne Bauer, William Bialek, Chase Goddard, Caroline M. Holmes, Kamesh Krishnamurthy, Stephanie E. Palmer, Rich Pang, David J. Schwab, Lee Susman. 2025-05-29. Optimization and variability can coexist. https://arxiv.org/abs/2505.23398

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