Google AI Quantum

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

Google AI Quantum
Recent Insight
  • Quantum safe cryptography – the big picture
    Recently updated advice on quantum security technologies from the UK NCSC is bluntly sceptical about the promised benefits of quantum key distribution. This seems at odds with the scramble of governments around the world to promote the development of quantum networking technologies. Who is right? Future large scale quantum computers... Read more
  • Quantum software – beneath the quantum hype
    Commercial activity around quantum computing has risen to fever pitch over the last year. Many point to the traditional cycle of hype and consolidation in tech markets. Some have become quick to call ‘bullshit’ much of the activity at the current commercial frontier. Others predict a coming quantum winter. How... Read more
  • Quantum Outlook 2020
    2020 will be a watershed year for the Quantum Revolution. There will be surprising early applications, though previously over-hyped timelines may leave some disappointed. Geopolitical considerations will be hard to ignore as major national programmes set out their stalls. The chill winds of a quantum winter may threaten some, but... 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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