Thermodynamic Depth of Causal States: When Paddling around in Occam's Pool Shallowness Is a Virtue
Open Access Publications from the University of California

## Thermodynamic Depth of Causal States: When Paddling around in Occam's Pool Shallowness Is a Virtue

• Author(s): Crutchfield, James P
• Shalizi, Cosma Rohilla
• et al.
Abstract

Thermodynamic depth is an appealing but flawed structural complexity measure. It depends on a set of macroscopic states for a system, but neither its original introduction by Lloyd and Pagels nor any follow-up work has considered how to select these states. Depth, therefore, is at root arbitrary. Computational mechanics, an alternative approach to structural complexity, provides a definition for a system's minimal, necessary causal states and a procedure for finding them. We show that the rate of increase in thermodynamic depth, or {\it dive}, is the system's reverse-time Shannon entropy rate, and so depth only measures degrees of macroscopic randomness, not structure. To fix this we redefine the depth in terms of the causal state representation---$\epsilon$-machines---and show that this representation gives the minimum dive consistent with accurate prediction. Thus, $\epsilon$-machines are optimally shallow.

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