Reasoning Phases Are Continuous, Not Discrete: Evidence from Switching Linear Dynamical Systems Applied to Chain-of-Thought Residual Streams

A widespread assumption in mechanistic interpretability holds that chain-of-thought (CoT) reasoning unfolds through discrete, recoverable cognitive phases-a prediction that would enable phase-specific circuit analysis and steering interventions. We test this using Switching Linear Dynamical Systems (SLDS) applied to residual-stream activations of DeepSeek-R1-Distill-Llama-8B across 997 MATH-benchmark traces at layer~16, complemented by a boundary diagnostic and a variance-discrimination analysis. Phase boundaries produce statistically significant but metrically weak distributional shifts (PC2: Cohen's $d = -0.293$, $p = 8.5\times10^{-6}$), and PCA directions are statistically independent of phase-discriminative directions (Spearman $\rho = -0.025$, $p = 0.78$), explaining why standard dimensionality reduction systematically discards the phase signal. Across all three experimental conditions and hyperparameter regimes, SLDS fails categorically to recover phase sequences (NMI $\leq 0.005$); inferred states instead capture positional structure ($\chi^2 = 2343$, $p \approx 0$) and syntactic token-type patterns ($\chi^2 = 293$, $p < 10^{-44}$). We conclude that CoT reasoning is a \emph{continuous dynamical process}: discrete-phase interpretability frameworks will systematically underfit residual-stream dynamics, and continuous-trajectory approaches are necessary.