ORCA Computing Advances Photonic Quantum Simulation with NVIDIA cuTensorNet

MAR 16 2026ORCA announces 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,” said William 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.”This latest announcement builds on ORCA Computing’s Advancement of Hybrid Quantum–Classical Integration with NVIDIA NVQLink, ORCA’s Collaboration with PCSS to Deliver Data Centers Blueprint for Quantum AI Integration Built on NVIDIA and ORCA’s pioneering launch of a hybrid quantum-classical platform for AI at PSNC with NVIDIA CUDA-Q.Collectively, these initiatives underscore the strategic collaboration at the intersection of photonic quantum systems and GPU accelerated AI, reinforcing ORCA’s overall hybrid quantum-classical strategy.For additional technical details, see our blog post: Accelerating photonic quantum simulations with GPUs.David Hall DPhilHead of DeliveryProf. Ian Walmsley is Chairman of the ORCA Computing Board and a leading figure in quantum optics, quantum memories and waveguide circuits. He is Provost of Imperial College, London, an Honorary Fellow at St Hugh's College, Oxford and a Fellow of the Royal Society, The Optical Society, the Institute of Physics and the American Physical Society. Previously, he was President of the Optical Society of America, Pro-Vice-Chancellor for Research and Innovation, Hooke Professor of Experimental Physics at the University of Oxford and Director of the NQIT (Networked Quantum Information Technologies) hub. Prof. Walmsley is recognised for developing the SPIDER technique for characterising ultra-fast laser pulses.Enhance renewable energy optimisation and accelerate the development of biofuels. Investigating molecular structures is an important pursuit in computational chemistry, especially in fields likes biofuel formulation, material innovation, and pharmaceutical development where research acceleration is critical. The specific problem considered here is significant across the energy industry, as molecule’s possible structures directly determine many of its physical and chemical traits. However, the vast array of possible configurations and high computational requirements make it difficult for traditional methods to find low-energy conformations for certain molecules. ORCA partnered has with bp to explore a hybrid quantum-classical approach using generative adversarial network (GAN) algorithms. This approach aims to generate low-energy conformations of small and medium size hydrocarbon molecules, offering a potential solution to the computational hurdles faced in molecular exploration.