Differentiable master equation solver for quantum device characterisation

Understand

Differentiable models of physical systems provide a powerful platform for gradient-based algorithms, with particular impact on parameter estimation and optimal control.

• Quantum systems present a particular challenge for such characterisation and control, owing to their inherently stochastic nature and sensitivity to environmental parameters.
• To address this challenge, we present a versatile differentiable quantum master equation solver, and incorporate this solver into a framework for device characterisation.
• Our approach utilises gradient-based optimisation and Bayesian inference to provide estimates and uncertainties in quantum device parameters.