Part I: Foundations

The Free Energy Landscape

Introduction
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The Free Energy Landscape

For systems amenable to such analysis, one can define an effective free energy functional:

F[x]=U[x]TS[x]+(non-equilibrium corrections)\mathcal{F}[\mathbf{x}] = U[\mathbf{x}] - T \cdot S[\mathbf{x}] + \text{(non-equilibrium corrections)}

where UU captures internal energy, SS entropy, and TT an effective temperature. The dynamics can often be written as:

dxdt=ΓxF[x]+η(t)\frac{d\mathbf{x}}{dt} = -\Gamma \cdot \nabla_\mathbf{x} \mathcal{F}[\mathbf{x}] + \bm{\eta}(t)

for some positive-definite mobility tensor Γ\Gamma. In this representation:

  • Local minima of F\mathcal{F} correspond to metastable attractors
  • Saddle points determine transition rates between attractors
  • The depth of minima relative to barriers determines persistence times

One structure within this landscape will recur throughout the book. For a self-maintaining system, the viability manifold VRn\viable \subset \R^n is the region of state space within which the system can persist indefinitely (or for times long relative to observation scales):

V={xRn:E[τexit(x)]>Tthreshold}\viable = \left\{ \mathbf{x} \in \R^n : \E\left[\tau_{\text{exit}}(\mathbf{x})\right] > T_{\text{threshold}} \right\}

where τexit(x)\tau_{\text{exit}}(\mathbf{x}) is the first passage time to a dissolution state starting from x\mathbf{x}.

x1x2V∂Vviabledissolution

The viability manifold will play a central role in understanding normativity: trajectories that remain within V\viable are, in a precise sense, “good” for the system, while trajectories that approach the boundary V\partial\viable are “bad.”

Viability Theory

The viability manifold concept connects to Aubin’s viability theory (1991), which provides mathematical tools for analyzing systems that must satisfy state constraints over time. Key results:

  • A state is viable iff there exists at least one trajectory remaining in V\viable forever
  • The viability kernel is the largest subset from which viable trajectories exist
  • For controlled systems, viability requires the control to “point inward” at boundaries

I’ll add stochasticity and connect viability to phenomenology: the felt sense of threat corresponds to proximity to V\partial\viable.