Cycle Flux Ranking of Network Analysis in Quantum Thermal Devices

Manipulating quantum thermal transport relies on uncovering the principle working cycles of quantum devices. Here we introduce the cycle flux ranking of network analysis to nonequilibrium thermal devices characterized as a quantum-transition network. To excavate the principal mechanism out of complex transport behaviors, we decompose the network into cycle trajectories, collect the cycle fluxes by algebraic graph theory, and select top-ranked cycle fluxes, i.e., the cycle trajectories with highest probabilities. We exemplify the cycle flux ranking in typical quantum device models, e.g., a thermal-drag spin-Seebeck pump and a quantum thermal transistor. Top-ranked cycle trajectories indeed elucidate the principal working mechanisms. Therefore, cycle flux ranking provides an alternative perspective that naturally describes the working cycle corresponding to the main functionality of quantum thermal devices, which would further guide the device optimization with desired performance.