NVIDIA Ising Delivers Breakthrough Performance in Quantum Calibration and Error Correction, Empowering Researchers and Enterprises to Build Scalable, High-Performance Quantum Systems<\/p>\n
News Summary:<\/p>\n
\n\tThe NVIDIA Ising open model family delivers the world\u2019s best AI-based quantum processor calibration capabilities, as well as quantum error-correction decoding that is up to 2.5x faster and 3x more accurate than traditional approaches.
\n\tLeading quantum enterprises, academic institutions and research labs adopting Ising include Academia Sinica, Fermi National Accelerator Laboratory, Harvard John A. Paulson School of Engineering and Applied Sciences, Infleqtion, IQM Quantum Computers, Lawrence Berkeley National Laboratory\u2019s Advanced Quantum Testbed and the U.K. National Physical Laboratory (NPL).
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NVIDIA today announced the world\u2019s first family of open source quantum AI models,\u00a0NVIDIA Ising<\/a>, designed to help researchers and enterprises build quantum processors capable of running useful applications.<\/p>\n To achieve useful quantum applications at scale, significant breakthroughs are needed in quantum processor calibration and quantum error correction. AI is key for turning today\u2019s quantum processors into large-scale, reliable computers. Open models empower developers to build high-performance AI while maintaining total control over their data and infrastructure.<\/p>\n Named after a landmark mathematical model that dramatically simplified the understanding of complex physical systems, the NVIDIA Ising family provides high-performance, scalable AI tools for quantum error correction and calibration \u2014 two of the most critical challenges in building hybrid-quantum classical systems.<\/p>\n Ising models run the world\u2019s best quantum processor calibration and enable researchers to tackle much larger, more complex problems with quantum computers by delivering up to 2.5x faster performance and 3x higher accuracy for the decoding process needed for quantum error correction.<\/p>\n \u201cAI is essential to making quantum computing practical,\u201d said Jensen Huang, founder and CEO of NVIDIA. \u201cWith Ising, AI becomes the control plane \u2014 the operating system of quantum machines \u2014 transforming fragile qubits to scalable and reliable quantum-GPU systems.\u201d<\/p>\n The quantum computing market is expected to surpass $11 billion in 2030, according to analyst firm Resonance. This growth trajectory is highly dependent on continued progress in addressing critical engineering challenges, such as quantum error correction and scalability.<\/p>\n NVIDIA Ising includes state-of-the-art customizable models, tools and data that accelerate quantum processors:<\/p>\n
Ecosystem Adoption Ising Calibration is already in use by Atom Computing, Academia Sinica, EeroQ<\/a>, Conductor Quantum, Fermi National Accelerator Laboratory<\/a>, Harvard John A. Paulson School of Engineering and Applied Sciences,\u00a0Infleqtion<\/a>, IonQ, IQM Quantum Computers<\/a>, Lawrence Berkeley National Laboratory\u2019s Advanced Quantum Testbed<\/a>, Q-CTRL<\/a> and the U.K. National Physical Laboratory (NPL).<\/p>\n Ising Decoding is being deployed by Cornell University, EdenCode<\/a>, Infleqtion, IQM Quantum Computers, Quantum Elements, Sandia National Laboratories, SEEQC, University of California San Diego<\/a>, UC Santa Barbara, University of Chicago, University of Southern California and Yonsei University.<\/p>\n In addition, NVIDIA is providing a cookbook of quantum computing workflows and training data along with NVIDIA NIM<\/a>\u2122 microservices, equipping developers to fine-tune models for specific hardware architectures and use cases with minimal setup. The models can also run locally on researchers\u2019 systems, protecting proprietary data.<\/p>\n NVIDIA Ising complements the NVIDIA CUDA-Q<\/a>\u2122 software platform for hybrid quantum-classical computing and integrates with the NVIDIA NVQLink<\/a>\u2122 QPU-GPU hardware interconnect for real-time control and quantum error correction, providing researchers and developers with a full suite of tools needed to turn today\u2019s qubits into tomorrow\u2019s accelerated quantum supercomputers.<\/p>\n Get Started With NVIDIA Open Models These open models, data and frameworks are available on GitHub, Hugging Face and build.nvidia.com<\/a>.<\/p>\n Learn more by watching the special address from NVIDIA Quantum Day<\/a> and tuning in to this NVIDIA AI Podcast episode<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"NVIDIA Ising Delivers Breakthrough Performance in Quantum Calibration and Error Correction, Empowering Researchers and Enterprises to Build Scalable,…\n","protected":false},"author":2,"featured_media":606614,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[256,254,255,64,63,105],"class_list":{"0":"post-606613","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-artificial-intelligence","8":"tag-ai","9":"tag-artificial-intelligence","10":"tag-artificialintelligence","11":"tag-au","12":"tag-australia","13":"tag-technology"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts\/606613","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/comments?post=606613"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts\/606613\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/media\/606614"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/media?parent=606613"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/categories?post=606613"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/tags?post=606613"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\n\tIsing Calibration: A vision language model that can rapidly interpret and react to measurements from quantum processors. This enables AI agents to automate continuous calibration, reducing the time needed from days to hours.
\n\tIsing Decoding: Two variants of a 3D convolutional neural network model \u2014 optimized for either speed or accuracy \u2014 to perform real-time decoding for quantum error correction. Ising Decoding models are up to 2.5x faster and 3x more accurate than pyMatching, the current open source industry standard.
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\nLeading enterprises, academic institutions and research labs are adopting Ising for quantum computing development.<\/p>\n
\nNVIDIA Ising joins NVIDIA\u2019s open model portfolio, which includes NVIDIA Nemotron\u2122 for agentic systems, NVIDIA Cosmos\u2122 for physical AI, NVIDIA Alpamayo for autonomous vehicles, NVIDIA Isaac\u2122 GR00T for robotics and NVIDIA BioNeMo\u2122 for biomedical research.<\/p>\n