Google AI Quantum

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

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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
Latest News
  • Achieving Precision in Quantum Material Simulations
    Posted by Charles Neill and Zhang Jiang, Senior Research Scientists, Google Quantum AI In fall of 2019, we demonstrated that the Sycamore quantum processor could outperform the most powerful classical computers when applied to a tailor-made problem. The next challenge... Read more
    Source: Google AI Blog Published on: Jun 25, 2021
  • Quantum Machine Learning and the Power of Data
    Posted by Jarrod McClean, Staff Research Scientist and Hsin-Yuan (Robert) Huang1, Intern, Google Quantum AI Quantum computing has rapidly advanced in both theory and practice in recent years, and with it the hope for the potential impact in real applications.... Read more
    Source: Google AI Blog Published on: Jun 22, 2021
  • Announcing the 2021 Research Scholar Program Recipients
    Posted by Negar Saei, Program Manager, University Relations In March 2020 we introduced the Research Scholar Program, an effort focused on developing collaborations with new professors and encouraging the formation of long-term relationships with the academic community. In November we... Read more
    Source: Google AI Blog Published on: Apr 07, 2021
  • Announcing the 2020 Google PhD Fellows
    Posted by Susie Kim, Program Manager, University RelationsGoogle created the PhD Fellowship Program in 2009 to recognize and support outstanding graduate students who seek to influence the future of technology by pursuing exceptional research in computer science and related fields.... Read more
    Source: Google AI Blog Published on: Oct 08, 2020
  • Scaling Up Fundamental Quantum Chemistry Simulations on Quantum Hardware
    Posted by Nicholas Rubin and Charles Neill, Research Scientists, Google AI Quantum Accurate computational prediction of chemical processes from the quantum mechanical laws that govern them is a tool that can unlock new frontiers in chemistry, improving a wide variety... Read more
    Source: Google AI Blog Published on: Aug 27, 2020
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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