Quantum computing pioneer Alice & Bob has announced a collaboration with NVIDIA to integrate the chipmaker’s NVQLink architecture into its fault-tolerant quantum computing systems.
The partnership centres around NVQLink, NVIDIA’s open-source platform launched at GTC Washington this week that integrates GPUs into real-time quantum feedback loops, addressing a critical challenge in fault-tolerant quantum computing (FTQC).
NVQLink accelerates the development of logical qubits by enabling GPU computation alongside qubit decoding and calibration.
“In the near future, every NVIDIA GPU scientific supercomputer will be hybrid, tightly coupled with quantum processors to expand what is possible with computing,” said Jensen Huang, founder and CEO of NVIDIA.
“NVQLink is the Rosetta Stone connecting quantum and classical supercomputers — uniting them into a single, coherent system that marks the onset of the quantum-GPU computing era.”
The collaboration between Alice & Bob and NVIDIA builds on existing ties between the companies’ quantum software teams.
Products, including Alice & Bob’s high-performance GPU simulation tool Dynamiqs, were developed using the NVIDIA CUDA-Q platform.
Alice & Bob believe NVQLink will enable better FTQC solutions, bringing forward timelines for practical quantum computing applications.
“We are thrilled to see NVIDIA’s NVQLink addressing the layers of the FTQC stack we’ve long considered critical: logical orchestration, decoding, and live calibration,” said Jérémie Guillaud, VP of Firmware at Alice & Bob.
“This launch is a clear signal that fault-tolerant quantum computers, such as Alice & Bob’s QPUs, are about to reach industrial maturity.”
Based in Paris and Boston, Alice & Bob aims to create the first fault-tolerant quantum computer. Founded in 2020, the company has raised €130 million, employs over 150 staff, and has produced experimental results that surpass those of major technology firms.
Advised by Nobel Prize-winning researchers, Alice & Bob specialises in cat qubits, a technology it claims can reduce hardware requirements for large-scale quantum computers by up to 200 times compared with competing approaches.