(382l) Inferring Broken Detailed Balance in the Absence of Observable Currents

Time irreversibility is the hallmark of nonequilibrium dissipative processes. Detecting dissipation is essential for our basic understanding of the underlying physical mechanism, however, it remains a challenge in the absence of observable directed motion, flows, or fluxes. Additional difficulty arises in complex systems where determining the entropy production requires detailed information about the system's dynamic evolution and internal degrees of freedom, which poses a major challenge in realistic scenarios. In living systems, for example, the dissipation is directly related to the hydrolysis of fuel molecules such as adenosine triphosphate (ATP), whose consumption rate is difficult to directly measure in many experimental setups. Here we introduce a novel approach to detect time irreversibility and estimate the entropy production from time-series measurements, even in the absence of observable currents. We apply our technique to two different physical systems, namely, a partially hidden network and a molecular motor. Our method is completely generic and does not require complete information about the system dynamics. Hence, it can be implemented in scenarios where only partial information is available and thus provides a new tool for studying nonequilibrium phenomena.