MHB The Orthogonality of Vectors and Matrices

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Three vectors being orthogonal implies that they are perpendicular to each other, but this does not automatically mean the corresponding matrix is orthogonal. For a matrix to be orthogonal, its columns must be orthonormal, meaning they not only need to be orthogonal but also have a unit length. To verify if the columns are orthonormal, one should check that the dot product of different vectors equals zero and the dot product of each vector with itself equals one. The Kronecker delta is used to express these conditions succinctly. Understanding these concepts is crucial for working with orthogonal matrices in linear algebra.
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Hello MHB,
I wounder if I did understand correct, If we got 3 vector and they all are orthogonala, $$v_1=(x_1,y_1,z_1)$$,$$v_2=(x_2,y_2,z_2)$$,$$v_3=(x_3,y_3,z_3)$$ does that also mean that the matrix orthogonal so the invrese for the matrix is transport?

Regards,
$$|\pi\rangle$$
 
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Close, but not quite. A matrix being orthogonal means that its columns are orthonormal.
 
Ackbach said:
Close, but not quite. A matrix being orthogonal means that its columns are orthonormal.
How can I check if a columns are orthonormal? If I got it correct if $$v_1,v_2,v_3$$ shall be orthonormal that means that $$v_1*v_2*v_3=0$$

Regards,
$$|\pi\rangle$$
 
Check that $v_{i} \cdot v_{j}=\delta_{ij}$. Here
$$\delta_{ij}=\begin{cases}0,\quad &i \not=j \\ 1,\quad &i=j \end{cases}$$
is the Kronecker delta.
 
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