Ankaa-3 features a broad hardware redesign enabling superior performance. Enhancements across the technology stack include a new cryogenic hardware design, an overhaul of the qubit circuit layout, precise qubit frequency targeting with Alternating-Bias Assisted Annealing, and flexible gate architecture with precise controls. Ankaa-3 has achieved a 99.5% median two-qubit gate fidelity.
Forest users have run more than 65 million experiments on our platform to date. Here’s a snapshot of the latest papers and projects resulting from those experiments, spanning quantum chemistry, machine learning, and quantum information.
Quantum Kitchen Sinks: An algorithm for machine learning on near-term quantum computers
Introducing a new approach to hybrid algorithms for NISQ devices, and one that is applicable to a rather broad class of machine learning problems known as supervised machine learning.
We’re happy to announce the release of pyQuil 1.9. This release is the latest in our series of regular releases, and it’s filled with convenience features, enhancements, bug fixes, and documentation improvements.
Rigetti software engineer Steven Heidel explains in simple terms all the new and innovative software engineering involved in making quantum computers work.
This past weekend we hosted our first-ever quantum computing hackathon, drawing attendees from right here in Berkeley and as far away as Osaka, Tokyo, Basel, Toronto, Melbourne, London, and more.
This blog will focus on topics that are relevant to quantum developers. We’ll share updates from our own quantum engineering lab here, research papers from the community, and notable advances and demonstrations of quantum algorithms.