Two vectors are orthogonal when their inner product is zero.
For real Euclidean vectors, the inner product is the dot product, so and are orthogonal: . For nonzero Euclidean vectors, this means their angle is . The zero vector is orthogonal to every vector, although it has no direction or defined angle.[ref]
https://ocw.mit.edu/courses/18-06-linear-algebra-spring-2010/resources/lecture-14-orthogonal-vectors-and-subspaces/. Strang, MIT 18.06, Lecture 14: orthogonal vectors and subspaces
In an abstract inner product space, orthogonality always refers to its chosen inner product. For example, the weighted inner product makes and orthogonal, since . Their ordinary dot product is , so their arrows are not perpendicular in the usual Cartesian coordinate system. The algebraic definition also applies to functions, where arrows need not be available.
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