One might also be interested in the temporal evolution of microscopic variables. In other words, how the value of a microscopic variable at a given position and time, R and t , influences the value of the same microscopic variable at a later time, t + τ τ (and usually at the same position). Such temporal correlations are quantified via equal-position correlation functions, C ( 0 , τ τ ) . They are defined analogously to above equal-time correlation functions, but we now neglect spatial dependencies by setting r = 0 , yielding: C ( 0 , τ τ ) = ⟨ ⟨ s 1 ( R , t ) ⋅ ⋅ s 2 ( R , t + τ τ ) ⟩ ⟩ − − ⟨ ⟨ s 1 ( R , t ) ⟩ ⟩ ⟨ ⟨ s 2 ( R , t + τ τ ) ⟩ ⟩ .