Dynamical uncertainty propagation with noisy quantum parameters

Many quantum technologies rely on high-precision dynamics, which

raises the question of how these are influenced by the experimental

uncertainties that are always present in real-life settings. A standard

approach in the literature to assess this is Monte Carlo sampling, which

suffers from two major drawbacks. First, it is computationally expensive.

Second, it does not reveal the effect that each individual uncertainty

parameter has on the state of the system. In this work [Dalgaard et al., Phys. Rev. Lett. 128, 150503 (2022)], we

evade both these drawbacks by incorporating propagation of uncertainty

directly into simulations of quantum dynamics, thereby obtaining

a method that is orders of magnitude faster than Monte Carlo

simulations and directly provides information on how each uncertainty

parameter influences the system dynamics. Additionally, we compare

our method to experimental results obtained using the IBM quantum

computers.