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ICML 2026 · Interactive

🧭 The Deterministic Horizon — Explorer

Drag the decoherence parameters and watch neural chain-of-thought accuracy decay with reasoning depth. The Deterministic Horizon d* — where accuracy crosses your threshold — is solved in closed form, live. Past it, tool delegation wins.

Decoherence parameters

paper MLE 0.020 · 95% CI [0.017, 0.023]
shared across models · paper 0.15
O(10²) steps — not the raw context window O(10⁵)
depth where P(correct)=α defines d*
empirical C3 mean ≈ 0.92

Accuracy vs. reasoning depth

Deterministic Horizon
P(correct) at d*
Tool advantage past d*
Neural CoT P(d)=exp(−dε₀−γd(d+1)/2L_eff) Tool-integrated (C3) Horizon d*

Delegation decision

If my next subproblem is state-tracking steps deep →