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A new Rust-based DFT code achieves sub-meV accuracy against Quantum ESPRESSO via a novel, fixture-driven validation system.
Hybrid functional DFT calculations can now be accurately learned by neural networks using compact AO Hamiltonians derived from PW data, bypassing the need for explicit nonlocal operator reconstruction.
LevelSyn achieves a remarkable 6.89% power reduction and 27.48% timing improvement by integrating physical awareness into logic synthesis, revolutionizing design closure efficiency.