Speaker
Description
Faithful simulations of quantum processors are essential for computer-aided quantum computer design. In this talk, we will demonstrate that the simulation of superconducting qubits can be made differentiable with respect to both the design and control parameters. In addition, we can evaluate the gradient of typical design objectives in a single reverse computation. This leads to a speedup proportional to the number of parameters in the objective function against the finite difference method. We can thus utilize the gradients to optimize design and control parameters jointly and efficiently, extending the scope of quantum optimal control. For example, we can use this approach to design chips for more robust gate schemes or specific purposes like a near-term quantum application or a quantum error correction scheme.
