LAUSR

Digital twins are replicas of real-world objects that connect physical and digital spaces in real-time. In this letter, we derive bounds on the probability of error for the virtual twin being a true representative under a generic computational and communication model. We show that the representative performance of a digital twin depends on the quality of the model employed by the digital twin and the amount of directed information flowing between the virtual and physical entities. We illustrate the bounds developed and the interdependence of parameters with a numerical example.