Summary
Scaling solid-state quantum processors to a useful threshold while maintaining the requisite precision in quantum control remains a challenge. We propose a quantum metal-oxide-semiconductor (QMOS) architecture operating at cryogenic temperatures that is based on a network/node approach as a means to scalability. By working with QMOS, we benefit from the deep investments and advances that have been made in conventional CMOS device processing, and natural compatibility with CMOS integration. The architecture uses one of the most promising error correction schemes: topological stabilizer codes acting on a two-dimensional qubit arrays, also known as surface codes. The network/node approach is advantageous because it separates the surface code operation into two fundamental parts: local node operations involving a handful of qubits, which should be feasible to demonstrate in the near-term, and medium range entanglement distribution based on electron shuttling, which is challenging but can be developed in parallel. A major focus of this project is to simplify QMOS devices – reducing the number of gate electrodes per device, even down to a single electrode. The team led by Dr. Baugh with collaborators Dr. Lan Wei and Dr. Michel Pioro-Ladrière combines expertise in electrical engineering and CMOS integrated design, QMOS fabrication and physics. By testing the viability of a network/node approach, this project charts a path toward a large-scale quantum information processor in silicon.
Related Content
Towards large area, resonant quantum tunneling diodes by continuous Langmuir transfer of exfoliated 2D materials
Summary Atomically thin 2D materials constitute promising building blocks for quantum devices due to their exotic, layer-dependent electronic properties. The ability to stack these materials in alternating layers enables heterostructures to be built in almost limitless combinations and over small enough length scales to observe quantum phenomena. So far though, practical implementation of devices based […]
April 1, 2020
Engineering and Characterizing Programmable Interaction Graphs in a Trapped Ion Quantum Simulator
Summary Quantum simulators have the potential to bring unprecedented capabilities in areas such as the discovery of new materials and drugs. Engineering precise and programmable interaction graphs between qubits or spins forms the backbone of simulator applications. The trapped ion system is unique in that the interaction graph between qubits can be programmed, in […]
July 24, 2018
Harnessing the Promise of Quantum Materials for Future Electronic Devices
Summary Two-dimensional (2D) quantum materials, such as graphene and molybdenum disulfide, have great potential for use in future flexible and wearable electronics applications. With traditional silicon-based electronics nearing their theoretical performance limits, nano-electronics made from 2D quantum materials offer breakthrough opportunities for energy-efficient, wearable ubiquitous computation. In this project, we will study integration of […]
June 14, 2018
Spin-transfer Torque Magnetic Random Access Memory for On-chip Spin Information Storage
Summary Leakage power in semiconductor memories, such as Dynamic Random Access Memory (DRAM) and Static Random Access Memory (SRAM), can be substantial and is one of the limits for scalability of classical electronics. This is attributed to the fact that the information stored is volatile, requiring constant refreshing, as well as reprogramming upon powering […]
August 6, 2018