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Researchers have developed a hybrid DFT-Quantum Embedding framework that strategically partitions molecular simulations, using quantum solvers for chemically active regions while relying on classical HPC for the rest. This approach directly addresses longstanding accuracy limitations in Density Functional Theory by leveraging variational quantum algorithms to model strong electron correlations without sacrificing scalability. The method represents a significant step forward in computational chemistry, offering improved precision for complex materials and drug discovery applications.

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Researchers Simulate Molecules with Hybrid Hpc-Quantum Embedding

Quantum Zeitgeist28 august 20266 min de cititArticolul și perspectiva sunt în engleză.

By partitioning complex molecular systems, a new hybrid approach combines the strengths of classical and quantum computation to overcome longstanding limitations in predicting electronic behaviour. This DFT-Quantum Embedding (QDFT) framework treats chemically relevant portions with a quantum solver, while classical HPC handles the remainder, offering a pathway beyond the approximations inherent in standard Density Functional Theory. The resulting simulations demonstrate improved accuracy alongside the scalability needed for complex materials and drug discovery.

A hybrid Density Functional Theory–Quantum Embedding (QDFT) framework integrates DFT with a quantum electronic-structure solver, enabling treatment of chemically relevant parts of a system using the Variational Quantum Eigensolver (VQE) while the rest is handled by DFT, improving accuracy and retaining the scalability of High-Performance Computing (HPC). Namrata Manglani at C-DAC, Pune, and colleagues have created a new computational method that merges conventional supercomputing with the potential of quantum computers. This hybrid approach, termed DFT-Quantum Embedding, tackles limitations in current molecular simulations, particularly when dealing with complex electron interactions. By dividing calculations strategically, the team improved the accuracy of modelling electronic structures while maintaining the processing…

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