This article discusses how quantum-centric supercomputing, which combines quantum and classical computing, could significantly advance materials science. By addressing the memory limitations that hamper classical computing, this approach promises more accurate atomic simulations, particularly useful for energy storage, aerospace, and sustainable materials development. Specialized quantum algorithms, such as the variational quantum eigensolver and quantum phase estimation, are being optimized for this field. However, challenges remain, including error management and integration with existing systems. Overall, quantum computing could reshape innovation across various industries.
For more details, please continue reading the full article under the following link:
Please consult also the Quantum Server Marketplace platform for the outsourcing of computational science R&D projects to external expert consultants through remote collaborations:
#materials #materialsscience #materialsengineering #computationalchemistry #modelling #chemistry #researchanddevelopment #research #MaterialsSquare #ComputationalChemistry #Tutorial #DFT #simulationsoftware #simulation