Robust control objectives with respect to static noise operators can be added as an alternative cost function, similar to solving min time problems. For example, dephasing robustness can be accomplished for single qubit gates if the control is robust with respect to Pauli-Z.
Describe the solution you'd like
A new objective for robust control, as well as a new problem template for robust control with fidelity constraints, modelled after min time.
Additional information
Suppose the ideal dynamics are generated by the control $H_C(t)$. In the presence of noise $H_C(t) + H_N$, take the decomposition $U(t) = U_C(t) \left(U^\dag_C(t) U(t)\right) =: U_C(t)\widetilde{U}_N(t)$. We can expand the noise operator $\widetilde{U}_N(t)$ using the Magnus expansion, and look for controls that make this identity to first order in $H_N$.
Robust control objectives with respect to static noise operators can be added as an alternative cost function, similar to solving min time problems. For example, dephasing robustness can be accomplished for single qubit gates if the control is robust with respect to Pauli-Z.
Describe the solution you'd like A new objective for robust control, as well as a new problem template for robust control with fidelity constraints, modelled after min time.
Additional information Suppose the ideal dynamics are generated by the control $H_C(t)$. In the presence of noise $H_C(t) + H_N$, take the decomposition $U(t) = U_C(t) \left(U^\dag_C(t) U(t)\right) =: U_C(t)\widetilde{U}_N(t)$. We can expand the noise operator $\widetilde{U}_N(t)$ using the Magnus expansion, and look for controls that make this identity to first order in $H_N$.