This project will build superconducting quantum neural networks as dedicated quantum machine learning hardware, which can outperform classical von Neumann architectures in its further development. This will combine the latest innovations, machine learning and quantum computing, into a radically new technology. The project starts in 2019.
OpenSuperQ aims at developing a full-stack quantum computing system of up to 100 qubits and to sustainably make it available at a central site for external users. This system will be applied to tasks of quantum simulation in quantum chemistry which serve as a high-level benchmark, and to problems related to optimization and machine learning.
The quest for building quantum information processors is currently pursued along two largely orthogonal paths, one based on optical frequency excitations in atoms or ions in vacuum or embedded in a solid and the other based on microwave frequency excitations in superconducting or semiconducting micro- and nano-structures. While optical approaches drastically differ in their implementation from microwave implementations, solid state approaches based on superconducting electronic circuits and semiconductor quantum dots have very similar requirements for their successful implementation.
Large-scale quantum computation hinges on the ability to preserve and process quantum information with higher fidelity by increasing redundancy in a quantum error correction (QEC) code. Achieving such quantum fault tolerance in an extensible architecture remains an outstanding challenge for all experimental quantum computing platforms.
EU, Horizon 2020 Quantum Simulators provide new levels of understanding of equilibrium and out-of-equilibrium properties of many-body quantum systems, one of the most challenging problems in physics. The main objective of the RYSQ proposal is to use Rydberg atoms for quantum simulations, because their outstanding versatility will allow us to perform a great variety of useful quantum simulations, by exploiting different aspects of the same experimental and theoretical tools.
NCCR QSIT, Subproject Hybrid quantum systems using microwave frequency on-chip resonators as a coupling bus
Swiss National Science Foundation (SNSF), NCCR We combine the expertise of different research groups to explore novel hybrid quantum systems in joint interdisciplinary projects. One major goal is to combine the long coherence times available in microscopic quantum systems with the strong interactions and high level of integration available in solid-state systems to explore new approaches to quantum information processing.
Exploring Geometric Effects and Geometric Gates with Superconducting Circuits
Swiss National Science Foundation (SNSF) The intimate relation between geometry and quantum mechanics is exemplified best by the concept of the geometric phase, a quantity acquired during the evolution of a system which is purely defined by the path of the system state in Hilbert space.
ERC Advanced Grant Today superconducting electronic circuits are one of the prime physical systems to explore both foundations and technological applications of quantum mechanics. The concept of processing information more efficiently using quantum mechanics has stimulated enormous progress in control and measurement of quantum electronic circuits
Scalable Superconducting Processors for Entangled Quantum Information Technology (ScaleQIT)
EU, 7th Framework Programme FP7 The ScaleQIT vision is to “develop a conceptual platform for potentially disruptive technologies, advance their scope and breadth and speed up the process of bringing them from the lab to the real world.” ScaleQIT will address the engineering side of quantum information processing (QIP), analyzing and implementing realistic scenarios for scaling-up superconducting hybrid systems for quantum computing and quantum simulation.
