Riverlane-Led Consortium Receives £6.8 Million ($9M USD) For Attacking Error Correction Via Auto-...

By Carolyn Mathas

A UK consortium led by Riverlane, is building an auto-calibrated quantum system to meet the challenges of controlling hundreds of qubits simultaneously across a variety of quantum hardware. In current noisy intermediate-scale quantum (NISQ) devices, controllable hardware qubits cannot exist with error-free precision. Calibration is inefficient, costly and time consuming, representing a major bottleneck. Without auto-calibration, error correction cannot be scaled.

Consortium members are joining to build ‘Deltaflow Control’. Funded by Innovate UK, the £6.8M project (approximately $9M USD), will apply machine learning to identify fast, automated, and scalable ways to implement calibration, maximize hardware performance and accelerate the UK quantum industry.

The consortium includes quantum hardware suppliers Oxford Ionics and SEEQC representing trapped ion and superconducting qubits respectively. The University of Oxford provides access to semiconductor qubit circuits, and expertise in tuning semiconductor quantum devices through ML techniques. Mind Foundry will use ML techniques to calibrate qubits for faster, more predictable measurements. QT Hub will assist in bridging the gap between today’s available NISQ devices and emerging fault tolerant computers, and The National Physical Laboratory (NPL) and the University of Edinburgh will set measurement standards that ensure validity and precision.

Over the next three years, the consortium intends to break through calibration challenges, removing it as a barrier. The project will ultimately pave the way for cutting edge quantum hardware, transforming such industries as materials development, drug discovery, and finance. Visit the press release on the Riverlane website here.

March 27, 2022