Generalizing the multidimensional thermodynamic uncertainty relation to combinations of arbitrary counting variables

Abstract

Uncertainty relations provide lower bounds for otherwise hidden quantities of a partially accessible Markov network like the mean entropy production rate and the total dynamical activity. The thermodynamic uncertainty relation (TUR) is arguably the most prominent one and involves the precision of a fluctuating net current. One of its major generalizations is the multidimensional TUR (MTUR), which yields a tighter bound by using covariances of a set of observed net currents. We generalize this latter bound to time-dependently driven processes with arbitrary initial state and arbitrary measurement duration. Furthermore, this bound can be used with a set of fluctuating counting observables each of which can be time-antisymmetric, time-symmetric or time-asymmetric, i.e., a net current, a traffic or a flow. We can even allow for coarse-grained observations in which each counting observable could consist of multiple indiscernable observed transitions of the underlying system. Thus, we generalize the MTUR, extensions of the TUR for time-dependent processes based on one current, and an estimator based on one flux or on one traffic in a unifying way. We illustrate this general uncertainty relation with simple examples.