Upcoming Talks

Analog physical neural networks offer promising advancements in energy efficiency and computational speed over their digital counterparts but are typically operated in rather high-power regimes to maintain a sufficient signal-to-noise ratio (SNR). What happens if an analog system is instead operated in an ultra-low-power regime, in which the behavior of the system becomes highly stochastic and the noise is no longer a small perturbation on the signal? We immerse ourselves in the intricate dance of optical neural networks at quantum limits, where neuron activations hinge on the solitary act of a photon’s arrival, orchestrated by quantum uncertainty. Despite the overwhelming noise levels (SNR ≈ 1), our research successfully demonstrates that stochastic neural networks can be precisely trained to perform deterministic tasks with high accuracy. The methodology developed for training incorporates the stochastic nature of photon detection as a fundamental aspect. We experimentally demonstrated show a 98% accuracy for MNIST classification using an optical neural network with a hidden layer functioning at the single-photon level, utilizing only 0.008 photons per multiply-accumulate (MAC) operation, or 0.003 attojoules per MAC. Our experiment showed a greater than 40-fold reduction in photon use per inference compared to previous efforts without compromising accuracy. These findings underscore the viability of harnessing highly stochastic analog systems, even those dominated by inevitable quantum noise, for reliable neural network operations when trained appropriately.

Shi-Yuan Ma is a senior PhD candidate at Cornell University, working with Prof. Peter McMahon from 2019. His doctoral research is centered on optical computing and quantum optics, and he is eager to extend his exploration to diverse computational platforms. Shi-Yuan’s research interests focus on harnessing the potential computational power of physical systems, particularly through the use of machine learning techniques to train and analyze complex (stochastic) data and mechanisms. Prior to Cornell University, Shi-Yuan received his B.S. degree in Physics from University of Science and Technology of China, with a minor in Computer Science.

Global efforts are currently in progress to develop prototypes for quantum networks, with the goal of realizing the quantum Internet. In this presentation, I will explore the fundamental design considerations for the quantum Internet. To address this question, I will delve into two distinct visions: 1- A unified classical-quantum Internet enabled through packet-switching. 2- Building an optical grid for entanglement distribution, effectively transforming the classical Internet into the quantum Internet. I will conclude by examining the economic aspects of building quantum networks using satellites versus optical fibers.

Alireza Shabani is a scientist and entrepreneur who recently established a quantum lab for Cisco Systems. Prior to that, he founded Qulab, a pharmaceutical startup leveraging AI to automate drug design. He was also a senior scientist at Google Quantum AI Lab. His research has been at the intersection of quantum physics, engineering, and biology. He holds a Ph.D. in electrical engineering from the University of Southern California and was a postdoctoral scholar at Princeton University and UC-Berkeley.

Solid-state quantum emitters have attracted much attention as an integrated source of photonic and spin qubits, which are basic elements for a range of quantum applications. Recent advances in the generation, manipulation, and integration of these emitters have demonstrated a variety of quantum resources: bright quantum light sources, quantum memories, and spin-photon interfaces. In particular, controllable quantum emitters in photonic cavities or waveguides enable scalable quantum interactions between multiple photons and emitters. Given their high performance and scalability, quantum emitters are taking the next stages towards scalable, integrated quantum systems on photonic integrated circuits or fiber optics. Therefore, all quantum operations are efficiently possible in compact optics systems. In this talk, I introduce important challenges and recent races in scalable, integrated quantum photonics systems and new approaches to interfacing quantum emitters to commercial fiber platforms efficiently

Je-Hyung Kim received his Ph.D. in Physics at the Korea Advanced Institute of Science and Technology (KAIST), South Korea, in 2014. He was a postdoc researcher at the University of Maryland from 2014 to 2017. Since 2017, he has joined the Department of Physics at the Ulsan National Institute of Science and Technology (UNIST), South Korea, and is now an associate professor at UNIST. Major research topics of his group are fundamental studies of quantum light-matter interactions based on solid-state quantum emitters and their applications to quantum information technologies.