Upcoming Talks

Photons offer a versatile platform for information processing, from long-distance quantum communication to scalable computing and machine learning. However, realizing distributed photonic information processing requires advances not only in individual optical devices, but also in network protocols, computing architectures, and system-level co-design. In this talk, I will present our research toward scalable and distributed photonic information processing. I will first discuss the physical infrastructure and protocols for large-scale quantum networks, including vacuum beam guides and efficient peer-to-peer entanglement distribution. I will then introduce our work on resource-efficient photonic quantum computing architectures. Finally, I will discuss our recent efforts in privacy-preserving optical inference and distributed machine learning, exploring how shared photonic computing resources can support secure and personalized computation with minimal client-side requirements. Together, these efforts illustrate a full-stack approach to building scalable, efficient, and secure photonic information processing systems. References [1] Huang, Y. et al. Vacuum Beam Guide for Large Scale Quantum Networks. Phys. Rev. Lett. 133, 020801 (2024). [2] Huang, Y. et al. A Comprehensive Characterization of the Vacuum Beam Guide and Its Applications. arXiv:2511.20031 (2025). [3] Huang, Y. et al. Peer-to-Peer Distribution of Graph States Across Spacetime Quantum Networks of Arbitrary Topology. Proc. ACM Meas. Anal. Comput. Syst. 9(2), Article 31 (2025). [4] Ren, X., Huang, Y., Liang, Z. & Barbalace, A. A Scalable and Robust Compilation Framework for Emitter-Photonic Graph State. ACM/IEEE DAC (2025). [5] Ren, X. et al. Photonic Quantum Computing on Spin Memory Architecture with Tree-Encoded Fusion. IEEE/ACM ISCA (2026).

Yuexun Huang is a Ph.D. candidate in Quantum Engineering at the University of Chicago, advised by Prof. Liang Jiang. His research focuses on photonic information processing, spanning quantum optics, distributed quantum networks, photonic computing architectures, and privacy-preserving machine learning. His work has appeared in Physical Review Letters and ACM SIGMETRICS, with additional research contributions accepted at ISCA and MICRO. He received his B.S. in Physics from the University of Science and Technology of China.

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This talk examines two complementary approaches to controlling photonic states for quantum technologies: precision-engineered resonator lattices and integrated electro-optic manipulation of multiple photonic degrees of freedom. First, it introduces the Surface Nanoscale Axial Photonics (SNAP) platform, in which nanoscale effective-radius variations along an optical fiber create ultra-low-loss, high-Q microresonator networks with sub-angstrom fabrication control. The discussion highlights the recent demonstration of multiband topological heterojunctions using coupled SNAP resonators configured as Su–Schrieffer–Heeger lattices. By exploiting multiple axial mode orders and nonvolatile resonance matching across more than 20 non-uniformly coupled sites, this work establishes SNAP as a promising platform for one-dimensional analogue Hamiltonian simulation and the experimental study of topological boundary and interface modes. The second topic considers electro-optic light control in thin-film lithium niobate (TFLN) with a focus on polarization-diverse phase modulation towards polarization–frequency hyperentanglement. TFLN’s strong Pockels nonlinearity offers a route to high-bandwidth, reconfigurable frequency-domain control, while polarization-diverse device architectures seek to extend that control to both polarization eigenmodes. The talk will examine how simultaneous manipulation of polarization and frequency can support higher-dimensional photonic-state engineering, including hyperentangled states and more resource-efficient interfaces for quantum communication and photonic information processing. Together, these platforms illustrate how advances in fabrication precision, topological design, and integrated electro-optics can expand the controllability and scalability of quantum light.

Dashiell L. P. Vitullo is a Research Physicist in the Quantum Networks team at DEVCOM Army Research Laboratory (ARL) and a Visiting Scientist with MIT’s Quantum Photonics and AI group.