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ORCA Computing Advances Photonic Quantum Simulation with NVIDIA cuTensorNet - The Quantum Insider

Google News – Quantum Computing
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ORCA Computing announced a breakthrough in photonic quantum simulation using NVIDIA’s accelerated computing and cuTensorNet library, enabling scalable hybrid quantum-classical workflows for photonic systems. The collaboration addresses a critical gap in quantum simulation infrastructure, as most existing tools focus on qubit-based models, leaving photonic systems underserved. ORCA’s GPU-accelerated simulator leverages NVIDIA’s cuQuantum to model larger photonic circuits efficiently. The new simulator aligns with ORCA’s PT-2 processor, allowing faster, large-scale simulations for algorithm prototyping, architecture validation, and performance benchmarking in hybrid environments. ORCA will open-source the photonic simulator alongside NVIDIA’s upcoming CUDA-Q release, expanding community access and enabling reproducible benchmarking across photonic workflows. NVIDIA’s Sam Stanwyck highlighted the partnership’s role in advancing quantum supercomputing, emphasizing cuQuantum’s ability to scale simulations for future hybrid quantum-classical systems.
ORCA Computing Advances Photonic Quantum Simulation with NVIDIA cuTensorNet - The Quantum Insider

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PRESS RELEASE — ORCA Computing, a leading quantum computing company, today announced a major step forward in accelerating photonic quantum simulation through the use of NVIDIA accelerated computing and the cuTensorNet library, expanding support for scalable hybrid quantum-classical workflows. High-performance simulation plays a critical role in the development and validation of quantum computing systems. Many existing simulation tools were designed around qubit-based models, creating a gap in infrastructure for photonic quantum systems. ORCA has addressed this gap by developing a GPU-accelerated photonic simulator built on NVIDIA’s cuQuantum library, enabling significantly improved scalability for modeling larger photonic circuits. By leveraging NVIDIA accelerated computing, ORCA’s approach enables faster simulations of photonic systems at larger scales aligned with ORCA’s PT-2 processor. This capability provides researchers and developers with practical tools to prototype algorithms, validate architectures and benchmark performance in a hybrid quantum-classical environment. “Our collaboration with NVIDIA strengthens the foundation for scalable photonic quantum computing,” saidWilliam Clements, Head of Applications and Software at ORCA Computing. “GPU-accelerated simulation is an essential component of hybrid quantum-classical integration and expands the tools available to developers working within the CUDA ecosystem.” ORCA plans to open-source the photonic simulator in alignment with an upcoming NVIDIA CUDA-Q release, enabling broader community access and reproducible benchmarking across photonic workflows. “GPU-accelerated simulations are driving breakthroughs in quantum computing, and cuQuantum enables the largest simulations achievable,” said Sam Stanwyck, Director of Quantum Product at NVIDIA. “Through our collaboration with ORCA, researchers in photonic quantum computing can now scale their simulations of photonic systems and develop the hybrid algorithms for future quantum supercomputing systems.” Keep track of everything going on in the Quantum Technology Market. hbspt.forms.create({ portalId: "7697776", formId: "bb678241-852f-447e-b9b3-fdc974f72f81", region: "na1", onFormReady: function($form) { const conversionPageField = $form.find('input[name="conversion_page"]'); if (conversionPageField.length) { conversionPageField.val(window.location.href); } const verticalField = $form.find('input[name="vertical"]'); if (verticalField.length) { verticalField[0].value = 'Quantum'; } } }); [ivory-search id=”2367594″ title=”Custom Search Form”] One of our team will be in touch to learn more about your requirements, and provide pricing and access options. Necessary cookies are always on to ensure the website works. Optional cookies help us understand how the site is used.

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Source: Google News – Quantum Computing