Aditya Jain | Applied Math, University of Waterloo
Optimal control and compiling of quantum circuits
Controlling quantum computers is a notoriously difficult task. Quantum gates are performed via unitary operations, which are in turn implemented by the evolution of Hamiltonians. These Hamiltonians are controlled by external devices. In this talk, I will discuss gradient-based optimization method to arrive at optimal control parameters for these devices. I will discuss how good physical fidelity of gates does not necessarily lead to good logical fidelity, and propose potential solutions.
In the present era of cloud based quantum computation, small scale quantum computers are available which can be used to run circuits consisting of anywhere between 2 and 20 qubits. The qubits are noisy : error rates vary and are high. As a result, execution of the same quantum gate gives different accuracies, depending on which qubit and/or qubit pairs the gate is applied on. Error diagnostics can be used to allocate qubits and schedule gates on the hardware in a clever way, which maximizes the success rate of quantum algorithms. I will discuss how to frame this as an optimization problem and discuss approaches to solve the task.