Summary
Trapped ions are one of the most advanced technologies for quantum computing, offering multi-qubit control in a universal quantum computing architecture and the ability to perform calculations with unprecedented precision. In this project we construct a shared trapped-ion quantum computing platform, QuantumIon, that will enable a broader and interdisciplinary scientific community to access an advanced quantum computing platform, thereby accelerating the discovery of new methods and applications of quantum computing.To this end, we build appropriate control electronics, test the suitability of our chosen barium isotope for multi-qubit operations, and construct a 10-qubit processor and benchmark its performance in collaboration with Joseph Emerson. We then demonstrate quantum algorithms from a variety of applications areas: quantum simulation by Rajibul Islam in collaboration with Christine Muschik, quantum error correction in collaboration with Raymond Laflamme, and characterization of multi-level qudits by Crystal Senko in collaboration with Joseph Emerson and Joel Wallman. The QuantumIon will make trapped ion hardware more automated and accessible to users, opening up a range of new experiments from quantum optics to multi-level qudit manipulation to quantum error correction.
Related Content
Implementing High-fidelity Quantum Gates in Multi-level Trapped Ions
Summary The scalability of quantum processors is limited by current error rates for single-qubit gates. By encoding more than a single bit of information within a single ion, multi-level “qudits” offer a promising method of increasing the information density within a quantum processor, and therefore minimizing the number of gates and associated error rates. […]
July 30, 2018
Hybrid Quantum Repeater based on Atomic Quantum Memories and Telecom Wavelength Entangled Photon-Pairs Generated from Semiconductor Nanowires
Summary Losses in physical channels, such as optical fibres, limit existing quantum communication systems to modest distance ranges. Since amplification of quantum signals is fundamentally not possible, we look to extend the range and functionality of these quantum channels by adding quantum memory nodes that can daisy-chain multiple lengths of quantum channels through entanglement […]
October 29, 2018
Building Blocks for Quantum Neuromorphic Computing: Superconducting Quantum Memcapacitors
Quantum neuromorphic computing (QNC) is a novel method that combines quantum computing with brain-inspired neuromorphic computing. Neuromorphic computing performs computations using a complex ensemble of artificial neurons and synapses (i.e., electrical circuits) to emulate the human brain. QNC may lead to a quantum advantage by realizing these components with quantum memory elements, or memelements, which […]
June 12, 2023
Extensible Technology for a Medium-Scale Superconducting Quantum Processor
Summary Superconducting quantum bits, or qubits, use circuits made from superconducting materials to harness quantum mechanical states. These devices contain many atoms, but can behave as simple, controllable qubits. We are building technologies for the control and measurement of superconducting qubits to enable the first demonstration of an extensible, medium-scale quantum processor. Our approach […]
November 28, 2016