Quantum Motion and NVIDIA have found a way to simplify a key stage of quantum simulation of molecules
British company Quantum Motion, in collaboration with NVIDIA, has introduced an innovative solution to one of the most challenging problems in quantum computing—preparing quantum states for molecular simulation. This stage, as is well known, often requires significantly more computational resources than the subsequent calculation itself, and has long remained a major barrier to the practical application of quantum computers in chemistry and materials science.
The researchers proposed using artificial intelligence for data preprocessing. Instead of burdening the quantum processor with the complex task of finding the desired molecular state, part of the work is offloaded to classical AI. This approach reduces the number of required quantum operations and lowers the demands on the hardware itself.
Open Source and the CUDA-Q Platform
The development team has published the source code of the GPU-accelerated package created for quantum chemistry tasks. Along with it, detailed guides on using the solution on NVIDIA's CUDA-Q platform have been released. This makes the technology accessible to a wide range of researchers and engineers.
Why Is This a Breakthrough?
One of the main promises of quantum computers is the ability to simulate molecular behavior with precision unattainable by traditional supercomputers. Such calculations are critical for developing new drugs, batteries, fertilizers, and industrial materials. However, in practice, quantum systems face fundamental limitations. The key one is the need to translate the problem into a special quantum state corresponding to the structure of the molecule under study. For complex compounds, this process becomes extremely costly and resource-intensive.
Hybrid Computing—A New Trend
The work by Quantum Motion and NVIDIA reflects a growing industry trend: instead of waiting for the perfect universal quantum computer to emerge, companies are learning to combine the capabilities of AI, classical computing, and quantum processors. This hybrid approach allows quantum technologies to be brought closer to real-world scientific and industrial problems more quickly. While this is not yet a commercial breakthrough, the development removes one of the bottlenecks that has long hindered the application of quantum computers in chemical calculations.
Expert opinion: This is an important step, demonstrating that practical quantum chemistry is becoming a reality faster than many expected. Optimizing the state preparation stage with AI is not just a technical improvement but a paradigm shift that could dramatically accelerate the adoption of quantum computing in pharmaceuticals and materials science.