Leveraging Machine Learning Force Fields (MLFFs) to Simulate Large Atomistic Systems for Fidelity Improvement of Superconducting Qubits and Sensors

Søren Smidstrup, Shela Aboud, Ricardo Borges +4

Materials engineering using atomistic modeling is an essential tool for the development of qubits and quantum sensors. Traditional density-functional theory (DFT) does however not…