Ideal representation for vectors/covectors

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The ideal representation for vectors and covectors is established as using column matrices for vectors and row matrices for covectors. Vectors are expressed in the form ##v^1 \mathbf{e}_1 + v^2 \mathbf{e}_2##, while covectors utilize the notation ##v_1 \mathbf{e}^1 + v_2 \mathbf{e}^2##. This distinction aligns with the conventions in differential geometry, where tangent vectors are represented as ##\frac{\partial}{\partial x^i}## and covectors as ##dx^i##. The matrix representation further supports this, with vectors as single-column matrices and covectors as single-row matrices.

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Jhenrique
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A vector can be expressed by a column matrix or by a row matrix, however is preferably use the column matrix for represent vectors and row matrix for covectors.

So, analogously, we can express a vector v as v1 e1 + v2 e2 or as v1 e1 + v2 e2. But I think that a vector is represented more correctly with one of those two possibilities, whereas that a covector is better represented with the other. The question is, which representation is the ideal representation for a vector and for a covector?
 
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Jhenrique said:
A vector can be expressed by a column matrix or by a row matrix, however is preferably use the column matrix for represent vectors and row matrix for covectors.

So, analogously, we can express a vector v as v1 e1 + v2 e2 or as v1 e1 + v2 e2. But I think that a vector is represented more correctly with one of those two possibilities, whereas that a covector is better represented with the other. The question is, which representation is the ideal representation for a vector and for a covector?

The notation ##v_1 \mathbf{e}^1 + v_2 \mathbf{e}^2## is used for covectors. For example, in differential geometry, you have the covectors ##dx^i##.

The notation ##v^1 \mathbf{e}_1 + v^2 \mathbf{e}_2## is used for vectors. For example, tangent vectors to a manifold are given by ##\frac{\partial}{\partial x^i}## (which is seen as a lower index).

This is consistent with matrices. A matrix is written as ##(\alpha^i_j)_{i,j}##, where ##i## denotes the rows and ##j## the columns. So we have, for example

\left(\begin{array}{cc} \alpha_1^1 & \alpha^1_2\\ \alpha^2_1 & \alpha_2^2 \end{array}\right)

In particular, in the case of one column, we get a vector:

\left(\begin{array}{c} v^1 \\ v^2\end{array}\right)

And in the case of one row, we get a covector:

\left(\begin{array}{cc} v_1 & v_2\end{array}\right)

Also see: http://en.wikipedia.org/wiki/Einstein_notation
 
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Thanks you!

To use the indices mixed is a thing that irritate me a lot, the indices for scalar components is the contrary of the indices of the unit vectors. I don't understand the why this...
 

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