junctions operating in the tunneling regime, where even minor variations in device geometry can lead to substantial performance fluctuations. In this work, we develop a quantitative model for the variability of the Josephson energy EJ induced by interface roughness at the Al/AlOx interfaces. The roughness is modeled as a Gaussian random field characterized by two parameters: the root-mean-square roughness amplitude σ and the transverse correlation length ξ. These parameters are extracted from the literature and molecular dynamics simulations. Quantum transport is treated using the Ambegaokar–Baratoff relation combined with a local thickness approximation. Numerical simulations over 5,000 Josephson junctions show that EJ follows a log-normal distribution. The mean value of EJ increases with σ and decreases slightly with ξ, while the variance of EJ increases with both σ and ξ. These results paint a quantitative and intuitive picture of Josephson energy variability induced by surface roughness, with direct relevance for junction design.
Device variability of Josephson junctions induced by interface roughness
As quantum processors scale to large qubit numbers, device-to-device variability emerges as a critical challenge. Superconducting qubits are commonly realized using Al/AlOx/Al Josephson