I am interested in various aspects of quantum computing and information. My Ph.D. is broadly focused on quantum tomography and state estimation. I like to learn new math and apply it to quantum information theory.
Quantum mean states are nicer than you think: Fast algorithms to find states maximizing average fidelity - Afham, Richard Kueng, and Chris Ferrie **(arXiv).
Summary. We solve the problem of finding states that maximize average fidelity over a finite distribution of quantum states. This optimal state (or fidelity barycenter) can be thought of as a single summarizing state of the distribution, akin to Euclidean mean. We find various related results including upper- and lower-bounds for optimal average fidelity and demonstrate applications in Bayesian quantum tomography.
Riemannian-geometric generalizations of quantum fidelities and Bures-Wasserstein distance - Afham ****and Chris Ferrie **(Journal of Mathematical Physics) (arXiv).
Summary. We introduce and study Generalized fidelity, which is a generalization of quantum fidelities based on the Riemannian geometry of the Bures-Wasserstein manifold. Generalized fidelity can recover various known fidelities like Uhlmann-, Holevo- and Matsumoto-fidelity. We study various geometric properties of generalized fidelity and associated quantities.
24th Australian Institute of Physics Congress (Dec 2022)
Work on average fidelity maximization was presented as a talk.
QMATH 15 at UC Davis (Sep 2022).
Gave a contributed talk in the quantum information track. Talk based on recent paper on average fidelity maximization.
QMATH Masterclass in Entropic Inequalities at Copenhagen University (Aug 2022).
Attended a week-long lecture series on quantum entropies. Presented poster on recent paper on average fidelity maximization.