Stanford OTL's quantum and photonic computing portfolio addresses critical bottlenecks in AI computation, data center infrastructure, and secure communications through optical and quantum technologies that dramatically reduce energy consumption while increasing processing speed.
The portfolio includes:
• AI/ML Photonic Accelerators & Data Center Optics – Technologies for training neural networks on optical devices, high-bandwidth interconnects, and cost-reducing polarization-insensitive fiber systems.
• Quantum Computing Hardware & Architecture – Cryogenic materials with enhanced performance, scalable quantum processors, and fault-tolerant architectures.
• Chip-Scale Lasers & Integrated Photonic Systems – Compact, manufacturable components including on-chip titanium-sapphire lasers and self-configuring optical filters.
• Quantum Networking & Secure Communications – Quantum-enhanced modulators, baseband quantum networks, and photonic blockchain systems.
• Advanced Sensing, Imaging & Metrology – Quantum performance advantages in single-molecule spectroscopy and on-chip information processing.
• Thermal Management – Solutions for both ultra-cold quantum system requirements and data center cooling needs.
Supporting technologies include foundry-compatible manufacturing platforms and automated design tools for scalable production of quantum photonic devices.
This research is led by Stanford faculty including:
- Jelena Vuckovic - quantum photonics and nanophotonics
- Shanhui Fan - photonic systems and neural networks
- Amir Safavi-Naeini - quantum optomechanics
- David Miller - photonic computing
- Jon Simon - condensed matter physics and quantum optics
- David Schuster - superconducting quantum circuits and hybrid quantum systems
Please direct your interest in this portfolio or any of its technologies to otl-connect@stanford.edu.