RIKEN Brings AI to Quantum Error Correction

New research could make quantum computers more efficient

A team of researchers at the RIKEN Center for Supercompuging in Japan have developed a method for using machine learning to improve error correction for quantum computers. According to the press release at the RIKEN website: “...the researchers leveraged machine learning in a search for error correction schemes that minimize the device overhead while maintaining good error correcting performance. To this end, they focused on an autonomous approach to quantum error correction, where a cleverly designed, artificial environment replaces the necessity to perform frequent error-detecting measurements. They also looked at bosonic qubit encodings, which are available and utilized in some of the currently most promising and widespread quantum computing machines based on superconducting circuits.”

Part of the team’s focus was on finding the right bosonic qubit encodings. They found that a surprisingly simple encoding “could not only greatly reduce the device complexity compared to other proposed encodings, but also outperformed its competitors in terms of its capability to correct errors.”

Lead author Yexiong Zeng adds, “Our work not only demonstrates the potential for deploying machine learning towards quantum error correction, but it may also bring us a step closer to the successful implementation of quantum error correction in experiments.”