
vectors that map to their scalar multiples, and the associated scalars
Eigenvectors are special directions in a mathematical space that don't change direction when a transformation is applied to them—they only get stretched or shrunk by a fixed amount called an eigenvalue. These concepts matter because they help us understand how transformations work, and they appear throughout science and engineering in applications like analyzing vibrations, compressing images, and predicting long-term behavior of systems.
AI-generated from the Wikipedia summary — may contain errors.
In linear algebra, an eigenvector (/ˈaɪɡən-/ EYE-gən-) or characteristic vector is a (nonzero) vector that has its direction unchanged (or reversed) by a given linear transformation. More precisely, an eigenvector
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Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).