**Abstract**: Network Utility Maximization (NUM) is a powerful mathematical framework that can be used to design and analyse classical communication protocols. NUM has enabled the development of distributed algorithms for solving the resource allocation problem, while at the same time providing certain guarantees, e.g., that of fair treatment, to the users of a network. In this talk, I will discuss our work on extending the notion of NUM to quantum networks, and introduce three quantum utility functions – each incorporating a different entanglement measure. The aim of the study is both to gain an understanding of some of the ways in which quantum users may perceive utility, as well as to explore structured and theoretically-motivated methods of simultaneously servicing multiple users in distributed quantum systems. Using our quantum NUM constructions, we develop an optimization framework for networks that use the single-photon scheme for entanglement generation, which enables us to solve the resource allocation problem while exploring rate-fidelity tradeoffs within the network topologies that we consider. We find that our utility functions result in contrasting behaviors which provide some ideas regarding the suitability of quantum network utility definitions to different quantum applications.

**Bio**: Gayane Vardoyan is an Assistant Professor at the College of Information and Computer Sciences, University of Massachusetts, Amherst. Previously, she was an Assistant Professor at QuTech’s Quantum Internet Division, and EEMCS, TU Delft. Prior to this, she was a postdoc researcher at TU Delft, where she worked with Prof. Stephanie Wehner. Vardoyan received her PhD from the University of Massachusetts, Amherst, where she worked in systems and networking. Her PhD advisor was Prof. Don Towsley. Vardoyan’s research interests currently focus on the modeling and performance analysis of distributed quantum systems. She received her Master of Science in 2017 from UMass Amherst and her Bachelor of Science in Electrical Engineering and Computer Sciences from the University of California at Berkeley. Previously, she worked at the Argonne National Lab and the Computation Institute at the University of Chicago.