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.
Rigetti Computing reports second quarter 2023 results
Rigetti Computing, Inc. (Nasdaq: RGTI) (“Rigetti” or the “Company”), a pioneer in full-stack quantum-classical computing, today announced its financial results for the second quarter ended June 30, 2023.
Rigetti Computing to report second quarter 2023 financial results and host conference call on August 10, 2023
Rigetti Computing, Inc. ("Rigetti" or the "Company") (Nasdaq: RGTI), a pioneer in hybrid quantum-classical computing, announced today that it will release second quarter 2023 results on Thursday, August 10, 2023, after market close.
Rigetti and ADIA Lab sign collaboration agreement to develop quantum machine learning solution for probability distribution classification
Together, Rigetti and ADIA Lab plan to design, build, execute, and optimize a quantum computing solution intended to address the probability distribution classification problem, one of the greatest challenges of quantitative finance.
Celebrating a decade of Rigetti: An evolution of technology and a quantum ecosystem
Today, we celebrate a decade of the passion, talent, and ingenuity that the Rigetti team and its partners have brought to not only our technology, but to the flourishing ecosystem of students, researchers, and industry professionals leveraging quantum computing.
Rigetti Computing reports first quarter 2023 results
Rigetti Computing, Inc. (Nasdaq: RGTI) (“Rigetti” or the “Company”), a pioneer in full-stack quantum-classical computing, today announced its financial results for the first quarter ended March 31, 2023.
Rigetti Computing to report first quarter 2023 financial results and host conference call on May 11, 2023
Rigetti Computing, Inc. ("Rigetti" or the "Company") (Nasdaq: RGTI), a pioneer in hybrid quantum-classical computing, announced today that it will release first quarter 2023 results on Thursday, May 11, 2023, after market close.
Recession prediction via signature kernels enhanced with quantum features
In this blog post, we illustrate a novel approach for addressing the problem of forecasting economic recession periods using cutting-edge quantum machine learning techniques, combining classical signature methods with a quantum data transformation.
Rigetti Computing reports fourth-quarter and full-year 2022 results
Rigetti Computing, Inc. (Nasdaq: RGTI) (“Rigetti” or the “Company”), a pioneer in full-stack quantum-classical computing, today announced its financial results for the fourth quarter and year ended December 31, 2022.
Rigetti Computing to report fourth quarter and full year 2022 financial results and host conference call on March 27, 2023
Rigetti Computing, Inc. ("Rigetti" or the "Company") (Nasdaq: RGTI), a pioneer in hybrid quantum-classical computing, announced today that it will release fourth quarter and full year 2022 results on Monday, March 27, 2023, after market close.
Rigetti Computing announces updated strategic plan to prioritize achieving higher performance system and potential path to narrow quantum advantage
Rigetti Computing, Inc. (“Rigetti” or “the Company”) (NASDAQ: RGTI), a pioneer in hybrid quantum-classical computing systems, today announced that its Board has approved an updated business strategy, including revisions to its technology roadmap.
Rigetti Computing appoints Dr. Subodh Kulkarni as President and Chief Executive Officer
Seasoned public company executive with background in the semiconductor industry brings track-record of success in scaling and commercializing cutting-edge technologies
Rigetti’s “quanvolutional” neural network demonstrates potential promise in medical imaging
Rigetti’s quanvolutional neural network method enhanced the performance of a typical machine learning model for identifying breast cancer and pneumonia in Rigetti experimentation.