Quantum Machines and Nvidia use machine learning to get closer to an error-corrected quantum computer

Nov 3, 2024

Quantum Machines and Nvidia progress toward error-corrected quantum computing using machine learning.

Quantum Machines and Nvidia use machine learning to get closer to an error-corrected quantum computer

: Quantum Machines and Nvidia have collaborated to enhance quantum computing through better qubit control on Nvidia’s DGX platform using reinforcement learning. This collaboration focuses on calibrating qubits by frequently recalibrating π pulses, which can improve fidelity and enable quantum error correction. The process uses off-the-shelf algorithms and is expected to expand into deep circuits in the future.

Quantum Machines and Nvidia have joined forces to push towards error-corrected quantum computing, leveraging machine learning techniques to better control qubits. The partnership, which incorporates Nvidia’s powerful DGX platform, has successfully utilized an off-the-shelf reinforcement learning model to enhance calibration of the qubits in a Rigetti quantum chip.

This collaboration places emphasis on recalibrating π pulses, key to managing qubit rotations within a quantum processor. By applying reinforcement learning, the partners aim to maintain high fidelity in quantum computers, a crucial requirement in the journey toward successful quantum error correction.

The project illustrates the significant impact of even small improvements in calibration on error correction outcomes. As this journey continues, the team expects to extend these advancements to more complex circuits, utilizing Nvidia’s upcoming Blackwell chips for even greater computing power.