Large deviations and conditioning for chaotic non-invertible deterministic maps: analysis via the forward deterministic dynamics and the backward stochastic dynamics

Abstract

The large deviation properties of trajectory observables for chaotic non-invertible deterministic maps as studied recently by Smith (2022 Phys. Rev. E 106 L042202) and by Gutierrez et al (2023 arXiv:2304.13754) are revisited in order to analyze in detail the similarities and the differences with the case of stochastic Markov chains. More concretely, we focus on the simplest example displaying the two essential properties of local stretching and global folding, namely the doubling map xt+1=2xt[mod1] on the real-space interval x∈[0,1[ that can also be analyzed via the decomposition x=∑l=1+∞σl2l into binary coefficients σl=0,1 . The large deviation properties of trajectory observables can be studied either via deformations of the forward deterministic dynamics or via deformations of the backward stochastic dynamics. Our main conclusions concerning the construction of the corresponding Doob canonical conditioned processes are: (i) non-trivial conditioned dynamics can be constructed only in the backward stochastic perspective where the reweighting of existing transitions is possible, and not in the forward deterministic perspective; (ii) the corresponding conditioned steady state is not smooth on the real-space interval x∈[0,1[ and can be better characterized in the binary space σl=1,2,..,+∞ . As a consequence, the backward stochastic dynamics in the binary space are also the most appropriate framework to analyze higher levels of large deviations, and we obtain the explicit large deviations at level 2 for the probability of the empirical density of long backward trajectories.