Quantum Computing

Name: Jason Pelc, HP: Classical computing with quantum objects
Start: 2014-03-28T01:30:00Z
Location: Classroom at Hacker Dojo

Jason Pelc, HP: Classical computing with quantum objects

Mar 27, 2014 · 6:30 PM
Classroom at Hacker Dojo

Meet Jason Pelc, an HP Labs scientist and Stanford Ph.D who will introduce us to photonics computing.

Title: Classical computing with quantum objects: a photonics perspective

Abstract: The days of exponential performance improvements in computers from miniaturization of semiconductor circuits are over. So what’s next? While the prospects for quantum computation are tantalizing, a nearer term objective should be an improved understanding of how underutilized quantum resources, like coherence, can be put to use in classical computation without relying on large-scale entanglement. At HP Labs we have started a research program, supported by DARPA, aimed at demonstrating logic devices operating at ultra-low energies using photonic devices exploiting quantum coherence.

In this talk, I will introduce this project and its objectives. I will introduce the concept of computing using optical nonlinearities. While optical nonlinearities are famously weak, the confinement of light to sub-cubic-wavelength volumes using high-quality-factor photonic nanocavities makes extremely low power nonlinear optical processes possible. I will discuss quantum optical simulations of large-scale sequential logic circuits made of these photonic components, which indicate that reliable performance is possible with a few tens of photons (a small handful of attojoules) per device. I will discuss technology platforms for ultralow-power integrated nonlinear optics using both III-V and group IV semiconductors, and will give some recent experimental results and prospects for scaling.

Bio: Jason Pelc is a research scientist in the Large-Scale Integrated Photonics group at HP Labs in Palo Alto, CA, where he performs research on nonlinear and quantum nanophotonic devices, silicon photonics for datacenter communications, holographic displays, and multi-view imaging systems. He received a Ph.D. in Applied Physics from Stanford in 2012, and a S.B. in Physics with Electrical Engineering from MIT in 2006.

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