Building quantum processors and algorithms to dramatically accelerate computational tasks for machine intelligence
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Recent Insight
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Navigating the quantum storm
The quantum sector faces a perfect storm of depressed tech markets, lengthening timelines to revenue and unwinding hype. The sector’s long-term potential remains unbound, but startups, investors and governments face a period of challenge. With challenge comes opportunity. The post Navigating the quantum storm appeared first on Fact Based Insight.... Read more
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Quantum Software Outlook 2022
IBM continues to lead the quantum cloud, but faces real competition to service early quantum applications. Building the future of this market still looks like a long game. It may be more important to pick a partner with the right strategy than just to compare today’s product features. The post... Read more
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Quantum Algorithms Outlook 2022
In contrast to the hype, the early applications of quantum computers look modest. But they do exist. The talented teams developing quantum algorithms still have a fight on their hands to bring forward the date of true broad quantum advantage. What might be achieved and when? The post Quantum Algorithms... Read more
Latest News
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Overcoming leakage on error-corrected quantum processors
Posted by Kevin Miao and Matt McEwen, Research Scientists, Quantum AI Team The qubits that make up Google quantum devices are delicate and noisy, so it’s necessary to incorporate error correction procedures that identify and account for qubit errors on... Read more
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Measurement-induced entanglement phase transitions in a quantum circuit
Posted by Jesse Hoke, Student Researcher, and Pedram Roushan, Senior Research Scientist, Quantum AI Team Quantum mechanics allows many phenomena that are classically impossible: a quantum particle can exist in a superposition of two states simultaneously or be entangled with... Read more
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Developing industrial use cases for physical simulation on future error-corrected quantum computers
Posted by Nicholas Rubin, Senior Research Scientist, and Ryan Babbush, Head of Quantum Algorithms, Quantum AI Team If you’ve paid attention to the quantum computing space, you’ve heard the claim that in the future, quantum computers will solve certain problems... Read more
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Scalable spherical CNNs for scientific applications
Posted by Carlos Esteves and Ameesh Makadia, Research Scientists, Google Research, Athena Team Typical deep learning models for computer vision, like convolutional neural networks (CNNs) and vision transformers (ViT), process signals assuming planar (flat) spaces. For example, digital images are... Read more
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How to compare a noisy quantum processor to a classical computer
Posted by Sergio Boixo and Vadim Smelyanskiy, Principal Scientists, Google Quantum AI Team A full-scale error-corrected quantum computer will be able to solve some problems that are impossible for classical computers, but building such a device is a huge endeavor.... Read more