Akademik Veri Yönetim Sistemi
International Journal of Advanced Natural Sciences and Engineering Researches, cilt.10, sa.3, ss.107-111, 2026 (Hakemli Dergi)
In this work, we're looking at a simplified Hamiltonian model for information erasure in Quantum Internet of Things (QIoT) systems - basically just two qubits that interact with each other. We've set up a toy model where we continuously measure one qubit and use that info to control the other one. This basically lets us engineer the reservoir entropy before the environment starts messing things up. The feedback we engineer through the reservoir connects directly to how much energy it costs to erase information, and this lets us control how much mutual information the qubits share. We discuss both so-called ‘conditional’ (i.e., stochastic) and ‘unconditional’ (ensemble-averaged) master equations to describe the dynamics of the system under measurement-and-feedback protocol. This mutual information is quantified and embedded into a correlation-corrected Landauer bound, showing that quantum correlations can help us erase information using less work than the usual Landauer limit. A simple stability analysis shows the existence of an optimal feedback gain that maximizes the entropy transfer while maintaining system stability. So, our simple model here connects the quantum-level processes with the bigger thermodynamic picture - things like heat flow, entropy, and free energy when the system's out of equilibrium. We link explicitly feedback strength, dissipation rates, and correlation dynamics to provides a toy but physically intuitive model for the control in QIoT. Our model is based on the recent advances in quantum thermodynamics, reservoir engineering, and feedback-controlled quantum systems. This gives us a new way to think about building energy-efficient QIoT systems and opens some interesting possibilities for scaling more nodes, dealing with memory effects in the environment, and optimizing control across entire networks.