Symposium S.EL06-Photonic Materials for Information Processing and Computing

With the end of Moore’s law and Dennard scaling, the field of computing and information processing has opened up to non-van Neumann architectures embracing a variety of concepts such as analog quantum or neuromorphic systems. Within this golden age for hardware development, the role of the underlying functional materials needs a fresh look with emerging technologies and applications in-mind. The bosonic character of photons bears unique advantages in terms of bandwidth, delay, signal integrity and potentially low power, enabling applications ranging from cryptography, LiDAR, data-comm, to machine learning and quantum computing. However, photonics has also pain points such as large footprint, cumbersome E-O conversion, no easy memory solution, and challenging packaging. Realistic opportunities for compute engines using photonics and optoelectronics (or electro-optic hybrids) exist, however, they require a careful consideration from both device structure and system architecture perspectives. It is the aim of this symposium to discuss the current status and the role of materials for this plethora of emerging computing systems and identify how photonic technologies might find unique value propositions in both niche and mainstream applications.

Photons are ideal for communication applications and hence distributed and analog computing systems such as neuromorphic computing. This includes interesting options for photonics such as optical reservoir computing, photonic perceptrons, Fourier-optics processors, random laser networks, and spiking and deep neural networks, etc. Photonics is also crucial for quantum computing and communication. Quantum gates are relatively straightforward realizable, and photonic qubits are being developed with improved dephasing times. Quantum communication and cryptography have been tested in deployed optical links. Photons are used in various hybrid quantum systems. Recent progress in topological photonics and optomechanics are highly relevant for quantum computers with either photonic or electronic qubits. In addition, much interest has also been focused on next generation ultralow energy/bit, high-speed, reconfigurable interconnect for densely interconnected systems for on-chip communication. In this symposium we discuss the research and innovations on these photonic materials for devices and circuits while keeping the functional system algorithm in mind.

Topics will include:

Photonic materials for deep-neural and spiking-neural networks
Photonic Perceptrons; Random Laser Networks; Reservoir Computer Approaches
Photonics for buffering or memory
Photonic materials for quantum computing, and transducers for quantum computing
Quantum communication and cryptography
Photonic quantum sensing
Single photon source and detectors
Monolithically integrated light sources and detector on silicon; Nanoscale light sources and photodetectors
Plasmonic and hybrid cavity devices and materials; Squeezed light
Topological material for photonics
Nanostructured materials for computing: quantum wells, nanowires
Simulation of novel photonic devices and materials

Invited Speakers:

Evelyn Hu (Harvard University, USA)
Eli Yablonovitch (University of California, Berkeley, USA)
David Awschalom (The University of Chicago, USA)
Vinod Menon (City College of New York, USA)
Jelena Vuckovic (Stanford University, USA)
Stefan Abel (IBM-Zurich, Switzerland)
Ritesh Agarwal (University of Pennsylvania, USA)
Yasuhiko Arakawa (The University of Tokyo, Japan)
Ray Chen (The University of Texas at Austin, USA)
Marcelo Davanco (National Institute of Standards and Technology, USA)
Anna Fontcuberta i Morral (École Polytechnique Fédérale de Lausanne, Switzerland)
Bahram Jalali (University of California, Los Angeles, USA)
Mercedeh Khajavikhan (University of Central Florida, USA)
Sae Woo Nam (National Institute of Standards and Technology, USA)
Cunzheng Ning (Arizona State University, USA)
Justin Norman (University of California, Santa Barbara, USA)
Jason Orcutt (IBM T.J. Watson Research Center, USA)
Riccardo Sapienza (Imperial College London, United Kingdom)
Bhavin Shastri (Queen's University, Canada)
Hiroki Takesue (Nippon Telegraph and Telephone Corporation, Japan)
Hong Tang (Yale University, USA)
Noelia Vico Trivino (IBM Research-Zurich, Switzerland)
Yoshihisa Yamamoto (Stanford University, USA)