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Abstract

Quantum fidelities are cornerstone metrics in quantum sciences, widely used to quantify the similarity of quantum states. Despite its prominence and age, several of its properties remain unexplored. This thesis advances our understanding of fidelities and its generalizations by addressing open problems and introducing novel frameworks rooted in quantum information theory and Riemannian geometry.

This thesis focuses mainly on three of problems. In the first part, we resolve the problem of maximizing average fidelity over finite ensembles of quantum states. By constructing a semidefinite program to compute the maximum average fidelity and deriving scalable fixed-point algorithms, we demonstrate significant improvements in computational runtime. We also derive novel bounds and expressions for near-optimal states, which are exact in special cases, such as when the ensemble consists of commuting states. These results provide new tools for applications, including Bayesian quantum tomography, where they address outstanding challenges. 

In the second part, we extend the concept of fidelity by introducing a family of generalized fidelities based on the Riemannian geometry of the Bures–Wasserstein manifold. This framework unifies and generalizes several existing quantum fidelities, including Uhlmann-, Holevo-, and Matsumoto-fidelity, and preserves their celebrated properties. Through a rigorous mathematical treatment, we establish invariance and covariance properties, derive an Uhlmann-like theorem, and discuss some possible generalizations of quantum divergences.

In the third part, we study the problem of projecting positive matrices to certain convex and compact sets with respect to Bures distance (or equivalently Uhlmann fidelity). These convex and compact sets are defined by quantum channels, and for certain channels, most importantly partial trace, we derive a closed-form for the projection.

Using the closed form for partial-trace projection we demonstrate various applications for our results including quantum process tomography and random state generation. Moreover, these results also endow the pretty good measurement and Petz recovery map with novel geometric and operational interpretations.

The existence of closed-form for specific channels is related to the saturation of the data processing inequality (DPI) for fidelity. Thus our results also provide explicit examples for the saturation of DPI for fidelity.

Together, these contributions provide a comprehensive study of quantum fidelities bridging foundational theory and practical applications.

Details

1010268
Title
Optimizing and Generalizing Quantum Fidelities
Author
Number of pages
208
Publication year
2025
Degree date
2025
School code
1295
Source
DAI-B 87/5(E), Dissertation Abstracts International
ISBN
9798263317874
University/institution
University of Technology Sydney (Australia)
University location
Australia
Degree
Ph.D.
Source type
Dissertation or Thesis
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
32408770
ProQuest document ID
3273138794
Document URL
https://www.proquest.com/dissertations-theses/optimizing-generalizing-quantum-fidelities/docview/3273138794/se-2?accountid=208611
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Database
ProQuest One Academic