Google AI Quantum

Building quantum processors and algorithms to dramatically accelerate computational tasks for machine intelligence

Google AI Quantum
Recent Insight
  • Quantum Outlook 2021
    2021 will be the first test for hardware players’ newly minted roadmaps. Expectations on when new algorithms and software will be able to exploit these devices to offer genuine quantum advantage differ widely. The long term importance of the Quantum Internet as the end-destination for the sector will continue to... Read more
  • Quantum Internet Outlook 2021
    Business must act now to secure itself against the security threat posed by future quantum computers. Fortunately new quantum-resistant maths-based crypto is on track to protect businesses that act promptly. To understand the growing momentum behind additional physics-based quantum security, it’s necessary to appreciate its unique enduring security promise and... Read more
  • Quantum Software Outlook 2021
    IBM continues to dominate the quantum cloud. However access to new more powerful processors will increase competition in the early adopter market. Ideas for user-engagement and education continue to explode with innovation. In the long term, supporting developers is a challenge the conventional software industry understands, but don’t forget that... Read more
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Project Description

The goal of the Quantum AI team at Google is to build a universal quantum computer. We are developing quantum algorithms in particular with a focus on those which can already run on today’s pre-error corrected quantum processors. Quantum algorithms for optimization, sampling, and quantum simulation hold the promise of dramatic speedups over the fastest classical computers.
The focus of our hardware team is to improve the quality and quantity of the quantum bits (qubits) in our quantum processors. Performing calculations faster than conventional supercomputers requires high fidelity in qubit initialization, operation, and measurement with sufficiently high degree of control and connectivity. We achieve this by researching novel chip architectures and materials.
Our theory group is developing practical algorithms for pre and post-error corrected quantum processors. Examples are quantum chemistry simulations, quantum-assisted optimization, and quantum neural networks. Our cloud team is working to provide access to quantum processors via the Google Cloud Platform. The Quantum AI lab collaborates with universities, national labs, and companies around the world.

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