Prediction of new Ti-N phases using machine learned interatomic potential

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The algorithm maintains a running "best distance" that starts at infinity. As it walks the tree, it checks each visited point and updates the best distance if it finds something closer. Before recursing into a child node, it checks whether the closest possible point in that child's bounding box is farther than the current best. If so, the entire subtree gets pruned.

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This Tweet is currently unavailable. It might be loading or has been removed.,这一点在搜狗输入法2026中也有详细论述

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