Postdoc opening: candidate will be performing calculations using both quantum simulators and existing quantum hardware Read More

Co-Design

The QSC integrates research across its three thrusts to establish co-design approaches for scalable and coherent quantum information systems. This integration drives interactions between the specific aims of each thrust and establishes a co-design feedback loop. The industrial “pull” for new technologies in quantum simulation and quantum sensing in turn drives this co-design process and provides a direct path to connect these technologies to the marketplace.

The QSC integrates 4 levels of the S&T innovation chain to transition discoveries to computing and sensing systems.

Fundamental science

Basic research underpins discoveries and innovation to deliver long-term impacts

Devices

Applied science builds new paradigms and devices for next-gen quantum technologies

Prototypes

First uses drive development and feedback for improved solutions

Applications

Real-world solutions accelerate the impact of quantum tech

Systems

Technology transfer
Integration of solutions into commercial systems to bolster US economic competitiveness

Topologically protected quantum information co-design

Led by LANL’s Filip Ronning

Fundamental science

fundamental science
Co-design materials for anyon physics using feedback from materials and algorithms thrusts

Devices

Develop devices to probe anyons physics using feedback from materials and devices thrusts

Prototypes

TISC scructure
Test anyon fusion and braiding using feedback between materials and algorithms thrusts

Applications

Validate non-Abelian statistics using feedback between materials and algorithms thrusts

Technology transfer

Error-resistant quantum devices
Transition discoveries in quantum materials to new qubits

Quantum simulations of scientific applications co-design

Led by UCSB’s David Weld

Fundamental science

Co-design simulation methods using feedback between materials, algorithms, and devices

Devices

Develop analog simulations using feedback between algorithms and devices

Prototypes

Test analog quantum simulation using feedback from materials, algorithms, and devices

Applications

Validate quantum simulations using feedback between materials and algorithms

Technology transfer

Quantum simulation platforms
Transition discoveries in quantum devices to new quantum computing applications

Quantum sensing for real-world applications co-design

Led by Fermilab’s Daniel Bowring

Fundamental science

Co-design sensors using feedback between materials, algorithms, and devices

Devices

Develop new qubits using feedback from materials and simulations thrusts

Prototypes

Test detection of waves of dark matter between algorithms and devices

Applications

Validate surface state measurements using feedback between materials and devices

Technology transfer

Quantum sensing capabilities
Transition discoveries in sensor design to new applications in materials characterization and dark matter searches

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