For a wide class of models, dynamical partition function provides lower bound for the stochastically averaged number of fixed points of the SDE-defined diffeomorphisms, Z t t ′ | t − − t ′ → → ∞ ∞ = ∑ ∑ p e − − ( t − − t ′ ) E p ≤ ≤ ⟨ ⟨ # # { fixed points of M t ′ t } ⟩ ⟩ noise ∝ ∝ e ( t − − t ′ ) S . Here, index p runs over "physical states", i.e., the eigenstates that grow fastest with the rate of the exponential growth given as, Γ Γ g = − − min α α Re ⁡ ⁡ E α α ≥ ≥ 0 , and parameter S can be viewed as stochastic version of dynamical entropy such as topological entropy. Positive entropy is one of the key signatures of deterministic chaos. Therefore, the situation with positive Γ Γ g must be identified as chaotic in the generalized, stochastic sense as it implies positive entropy: 0 < Γ Γ g ≤ ≤ S . At the same time, positive Γ Γ g implies that TS is broken spontaneously, that is, the ground state in not supersymmetric because its eigenvalue is not zero. In other words, positive dynamical entropy is a reason to identify spontaneous TS breaking as the stochastic generalization of the concept of dynamical chaos. Noteworthy, Langevin SDEs are never chaotic because the spectrum of their SEO is real non-negative.