Index Notation, multiplying scalar, vector and tensor.

In summary: The formula you are referring to is the Einstein summation convention. It states that repeated indices should be summed over when multiplying a scalar, vector, and tensor. This is an easy way to check calculations. If you have an equation you need the free indices on both sides to be the same, then you are using the summation convention correctly.
  • #1
hellomrrobot
10
0
I am confused at why ##V_{i,j}V_{j,k}A_{km,i}## the result will end up being a vector (V is a vector and A is a tensor)

What are some general rules when you are multiplying a scalar, vector and tensor?
 
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  • #2
Do you know of the Einstein summation convention?

Lets expand the product (which really is a contraction) you have given.

##V_{i,j}V_{j,k}A_{km,i} = (\partial_jV_i)\cdot (\partial_k V_j) \cdot (\partial_i A_{km})##

The summation convention I mentioned before states that repeated indices should be summed over.
For example ##V_i V_i = \sum_j V_jV_j## for a vector.(This is an alternative notation for the norm squared)

How to know what the resultant object is?
Well you find out what the free indices are. A free index is an index that isn't repeated.
A scalar has no free indices, a vector has one and a tensor 2 or more.
The power of the summation convention is that you can easily check calculations.
if you have an equation you need the free indices on both sides to be the same.

Another big advantage is the use of symmetry.
If you have 2 tensors ##A_{ij}\text{ and } S_{ij}## where A is antisymmetric in its indices and S symmetric you can show that ##A_{ij}S_{ij} = 0##.
 
  • #3
Such an expression would usually be written as something like ## V_{,j}^{i}V_{,k}^{j}A_{km,i} ##. The summation convention then says to sum over all indices that appear exactly once raised and exactly once lowered. But if the metric tensor is the flat space, Euclidean one, then, e.g. ## V_i = V^i ## and we can use a "generalized summation convention", where indices that are repeated are summed over, regardless of whether they are raised or lowered. Notice then that all the indices in your expression are summed over except for ## m ##. The result is a quantity with one index, in this case a vector. If there were no "free" indices left, then you would have had a scalar. If there were two free indices left, you would have had a second rank tensor.
 
  • #4
Geofleur said:
But if the metric tensor is the flat space, Euclidean one...
Not only do you need a flat space, you also have to be using Cartesian coordinates to be able to safely ignore the distinction between raised and lowered indices, right?
 
  • #5
That's right!
 
  • #6
Your objections are correct, it sometimes happens that people get lazy.
I've seen texts before where they use this sloppy version of the convention. (An example I encountere is the book Lie Algebras in particle physics by Howard Georgi)

Can you give some more context for that formula? Maybe we can shed a light on this. (and how you can check this whenever you encounter such a problem)
 

1. What is Index Notation?

Index Notation is a mathematical notation used to express higher-dimensional quantities, such as vectors and tensors, in a compact and consistent way. It involves using indices to represent the different components of a quantity, instead of explicitly writing them out.

2. How do you multiply a scalar and a vector using Index Notation?

To multiply a scalar and a vector using Index Notation, you simply multiply the scalar by each component of the vector. For example, if we have a scalar a and a vector v with components vi, the product would be expressed as avi.

3. What is the difference between multiplying two vectors and multiplying a vector and a tensor using Index Notation?

Multiplying two vectors using Index Notation is the same as the dot product, where the result is a scalar. However, multiplying a vector and a tensor results in a new tensor with higher rank and components that are the product of the vector and each component of the tensor.

4. Can you use Index Notation to express the cross product?

No, Index Notation cannot be used to express the cross product. The cross product is a vector operation that involves taking the determinant of a matrix, which cannot be represented using indices.

5. How is the Einstein Summation Convention used in Index Notation?

The Einstein Summation Convention is a shorthand notation used in Index Notation to simplify expressions involving repeated indices. It states that when an index appears twice in a term, once as a subscript and once as a superscript, it implies summation over all possible values of that index.

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