888-384-7144 info@insidequantumtechnology.com

Google’s AI Researchers Build Machine Learning Algorithm to Model Unwanted Noise in Quantum Computers

By IQT News posted 09 Oct 2019

(TheRegister.uk) AI researchers at Google have built a machine learning algorithm to model unwanted noise that can disrupt qubits in quantum computers.
Qubits have to be carefully controlled to get them to interact with one another in a quantum system. So Google engineers developed a reinforcement learning algorithm for something they call “quantum control optimization”.
“Our framework provides a reduction in the average quantum logic gate error of up to two orders-of-magnitude over standard stochastic gradient descent solutions and a significant decrease in gate time from optimal gate synthesis counterparts,” it said this week.
The algorithm’s goal is to predict the amount of error introduced in a quantum system based on the state its in and model how that error can be reduced in simulations. “Our results open a venue for wider applications in quantum simulation, quantum chemistry and quantum supremacy tests using near-term quantum devices,” Google concluded.

Subscribe to Our Email Newsletter

Stay up-to-date on all the latest news from the Quantum Technology industry and receive information and offers from third party vendors.

IQT Partner Program

Quantum Xchange
Quintessence Labs
Post Quantum
Montana Instruments
Quantum Dice

Become an IQT partner