Understanding Reciprocal Lattice Vectors and Orthogonality in Primitive Lattices

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The discussion focuses on the relationship between direct and reciprocal lattice vectors, emphasizing their orthogonality conditions. It establishes that the orthogonality is defined by the equation a_i · g_j = 2πδ_{i,j}, where a_i are direct lattice vectors and g_j are reciprocal lattice vectors. The participants explore methods for calculating reciprocal vectors, including using matrix representations and direct formulas involving cross products of lattice vectors. There is some confusion regarding the dimensions of matrices involved, clarifying that both A and G are 3x3 matrices. The conversation concludes with a request for clarification on the components of these vectors.
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f(\vec{r}) = f(\vec{r}+\vec{T})

\vec{T}= u_{1} \vec{a_{1}} + u_{2} \vec{a_{2}}+u_{3} \vec{a_{3}}

u_{1},u_{2},u_{3} are integers.

f(\vec{r}+\vec{T})= \sum n_{g} e^{(i\vec{G}.(\vec{r}+\vec{R}) )}= f(\vec{r})

e^{i\vec{G}.\vec{R} }= 1
\vec{G}.\vec{R} = 2\pi m

we call \vec{G}=h\vec{g_{1}} + k \vec{g_{2}}+l \vec{g_{3}} reciprocal lattice vector.

but what about the primitive lattice vectors \vec{g_{1}} , \vec{g_{2}} , \vec{g_{3}} ?

To simplify the discussion consider \vec{T_{1}} in 1D;

\vec{T_{1}} = u_{1} \vec{a_{1}}

\vec{G}.\vec{T} =(h\vec{g_{1}} + k \vec{g_{2}}+l \vec{g_{3}}) . ( u_{1} \vec{a_{1}}) = 2 \pi m

Is there any definiton that indicates direct primitive lattice vectors and reciprocal primitive lattice vectors orthogonalities?
i.e

\vec{g_{1}} . \vec{a_{1}} = 2 \pi

\vec{g_{2}} . \vec{a_{1}} = \vec{g_{3}} . \vec{a_{1}} = 0
 
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g1,g2,g3 are the primitive vectors for the reciprocal lattice.
And the orthogonality condition is \vec{a}_i \cdot \vec{g}_j = 2\pi \delta_{i,j}

A trick for calculating the reciprocal vectors is to form the matrix A where the columns are the direct lattice vectors, and the matrix G where the columns are the reciprocal lattice vectors. Then you have
G^T \cdot A = 2\pi I
so
G = 2\pi (A^{-1})^T
 
I is 3x3 identity martix isn't it?
 
yes it is
 
It's still confusing for me..
so how can I invers a (1x3) matrix?
 
You can get the vectors \vec{g_1}, \vec{g_2}, \vec{g_3} without using any matrices. To do this use the following formulas:
\vec{g_1}=2\pi\frac{[\vec{a_2},\vec{a_3}]}{\vec{a_1}[\vec{a_2},\vec{a_3}]}, \vec{g_2}=2\pi\frac{[\vec{a_3},\vec{a_1}]}{\vec{a_1}[\vec{a_2},\vec{a_3}]}, \vec{g_3}=2\pi\frac{[\vec{a_1},\vec{a_2}]}{\vec{a_1}[\vec{a_2},\vec{a_3}]}.
 
A and G are 3x3 matrices, not 1x3 matrices. The columns of A are the vectors of your lattice:
A = \left( <br /> \left( \! \! \begin{array}{c}\\ \vec{a}_1 \\ \, \end{array} \!\! \right)<br /> \left( \! \! \begin{array}{c}\\ \vec{a}_2 \\ \, \end{array} \!\! \right)<br /> \left( \! \! \begin{array}{c}\\ \vec{a}_3 \\ \, \end{array} \!\! \right) \right)

Personally, I think this is easier than manually evaluating three separate cross products. But either way works.
 
corydalus said:
You can get the vectors \vec{g_1}, \vec{g_2}, \vec{g_3} without using any matrices. To do this use the following formulas:
\vec{g_1}=2\pi\frac{[\vec{a_2},\vec{a_3}]}{\vec{a_1}[\vec{a_2},\vec{a_3}]}, \vec{g_2}=2\pi\frac{[\vec{a_3},\vec{a_1}]}{\vec{a_1}[\vec{a_2},\vec{a_3}]}, \vec{g_3}=2\pi\frac{[\vec{a_1},\vec{a_2}]}{\vec{a_1}[\vec{a_2},\vec{a_3}]}.

Thanks but the discussion is how we get these formulas.

kanato said:
A and G are 3x3 matrices, not 1x3 matrices. The columns of A are the vectors of your lattice:
A = \left( <br /> \left( \! \! \begin{array}{c}\\ \vec{a}_1 \\ \, \end{array} \!\! \right)<br /> \left( \! \! \begin{array}{c}\\ \vec{a}_2 \\ \, \end{array} \!\! \right)<br /> \left( \! \! \begin{array}{c}\\ \vec{a}_3 \\ \, \end{array} \!\! \right) \right)

Personally, I think this is easier than manually evaluating three separate cross products. But either way works.


O.K , as you said ai and gi must be vectors which has three components. The question is what are these components?
 
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