How many independent components does a tensor have?

In summary, the number of independent components of a tensor depends on its rank and the dimensions of the space it occupies. For a tensor of rank \( r \) in \( n \)-dimensional space, the total number of components is \( n^r \), but due to symmetries and constraints, the number of independent components is generally less than this total. Specific formulas exist for different tensor types, such as symmetric or antisymmetric tensors, which further refine the count of independent components.
  • #1
MatinSAR
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Homework Statement
How many independent component does a tensor have?
Relevant Equations
Tensor analysis.
1705790546832.png

It's a 4th-dimensional 4th-rank tensor so at first we have ##4^4=256## components.
According to the book, Given that ##R_{iklm}=-R_{ikml}## 256 components reduces to 96. But I cannot see how.
For one pair of i,k 16 components are dependent. We have 12 pairs of i,k(for ##i≠k## becsuse for i=k tensor's components should be 0) so 256 should reduces to ##256-12*16=4*16=64##.Thanks for your help ...
 
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  • #2
We have 16 independent combinations of ##i,k##. For each such combination, we have an antisymmetric tensor ##R_{..lm}=-R_{..ml}##. ... That gives us ##96## components.
 
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  • #3
MatinSAR said:
We have 12 pairs of i,k
only six pairs: 01 02 03 12 13 23

##\ ##
 
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  • #4
MatinSAR said:
According to the book, Given that ##R_{iklm}=-R_{ikml}## 256 components reduces to 96. But I cannot see how.
For one pair of i,k 16 components are dependent. We have 12 pairs of i,k(for ##i≠k## becsuse for i=k tensor's components should be 0) so 256 should reduces to ##256-12*16=4*16=64##.

A better idea just came in to my mind:
For ##m=l## we have ##R_{ikmm}=0## so ##4^3=64## compenents should be zero. Therefor we have 192 independent components. If I divide this 192 by 2 I'll get the right answer.
For ##m≠l## we have ##R_{iklm}=-R_{ikml}## but how it imply that 192 should be divivded by 2?
 
  • #5
Hill said:
We have 16 independent combinations of ##i,k##. For each such combination, we have an antisymmetric tensor ##R_{..lm}=-R_{..ml}##. ... That gives us ##96## components.
The problem is that I cannot see why.
BvU said:
only six pairs: 01 02 03 12 13 23

##\ ##
Did you remove duplicate combinations? (like 3 2)
 
  • #6
MatinSAR said:
The problem is that I cannot see why.
The antisymmetric tensor has 6 independent components. That is, 6 for each one of 16 combinations of ##i,k##. Total: ##16 \times 6=96##.
 
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  • #7
MatinSAR said:
The problem is that I cannot see why.

Did you remove duplicate combinations? (like 3 2)
That's what independent means: if 32 = -23 there is only one independent component, not two. So only 01, 02, 03, 12, 13 & 23 are independent (and 00, 11, 22, 33 all vanish), so 6 independent components total.
 
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  • #8
Hill said:
The antisymmetric tensor has 6 independent components.
renormalize said:
That's what independent means: if 32 = -23 there is only one independent component, not two. So only 01, 02, 03, 12, 13 & 23 are independent (and 00, 11, 22, 33 all vanish), so 6 independent components total.

This is true only for 4th-dimensional 4th-rank tensor? Or every tensor?
What a bout symmetric tensor? Does it have 6 independent components?
 
  • #9
MatinSAR said:
This is true only for 4th-dimensional 4th-rank tensor?
4-dimensional, rank 2.
MatinSAR said:
What a bout symmetric tensor? Does it have 6 independent components?
No. You can make a list or draw a matrix, and count.
 
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  • #10
MatinSAR said:
This is true only for 4th-dimensional 4th-rank tensor? Or every tensor?
What a bout symmetric tensor? Does it have 6 independent components?
My count was for an antisymmetric rank-2 tensor in 4 dimensions (for your example, the symmetries of the rank-4 Riemann tensor behave like the product of two independent antisymmetric rank-2 tensors, hence 6 x 6 = 36 independent components total). A symmetric rank-2 tensor in 4-dimensions has 10 components: 00, 01, 02, 03, 11, 12, 13, 22, 23, 33. In other dimensions the counts are different.
 
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  • #11
So I should think more about it. Thank you to everyone.
 
  • #12
For an NxN matrix, the number of independent elements is
general: ##N^2##
symmetric: ##\frac 12N(N+1)##
antisymmetric: ##\frac 12N(N-1)##
 
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  • #13
Thank you to everyone ... I've understand the first step.
We have 256 components. For ##R_{iklm}## we know there are 16 combinations of i and k and there are 16 combinations of m and l.
Using equation ##R_{iklm}=-R_{ikml}## we know there are 10 dependent components. So we have ##256 - 16(10) = 96## independent components.

Now using next equation ##R_{iklm}=-R_{kilm}## again there are 96 independent components. But how can I find out How many of these 96 independent components also apply to the previous condition and are now repeated?
 
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  • #14
One more question, Should I use all three equations?
1705818424831.png
 
  • #15
MatinSAR said:
One more question, Should I use all three equations?
View attachment 338924
That's only two equations. Any two imply the third.
 
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  • #16
At first we have 256 independent components, using ##R_{iklm}=-R_{ikml}## 256 reduces to 96.
Then using ##R_{iklm}=-R_{kilm} ## 96 reduces to 36. Am I right?
 
  • #17
MatinSAR said:
We have 256 components. For ##R_{iklm}## we know there are 16 combinations of i and k and there are 16 combinations of m and l and.
Using equation ##R_{iklm}=-R_{ikml}## we know there are 10 dependent components. So we have ##256 - 16(10) = 96## independent components.

Now using next equation ##R_{iklm}=-R_{kilm}## again there are 96 independent components. But how can I find out How many of these 96 independent components also apply to the previous condition and are now repeated?
Consider the rank-4 product ##P_{iklm}=A_{ik}B_{lm}## of two arbitrary rank-2 tensors ##A_{ik}## and ##B_{lm}##. Each tensor ##A## and ##B## has in general ##16## components, so the product ##P## starts with ##16\times 16=256## distinct components. Now impose the two independent antisymmetries:$$P_{iklm}=-P_{kilm}\Rightarrow A_{ik}B_{lm}=-A_{ki}B_{lm}\Rightarrow A\text{ has 6 components}$$$$P_{iklm}=-P_{ikml}\Rightarrow A_{ik}B_{lm}=-A_{ik}B_{ml}\Rightarrow B\text{ has 6 components}$$So the two antisymmetries together give ##P=A\times B## a total of ##6\times 6=36## independent components. The same argument applies to ##R_{iklm}##.
 
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  • #18
renormalize said:
Consider the rank-4 product ##P_{iklm}=A_{ik}B_{lm}## of two arbitrary rank-2 tensors ##A_{ik}## and ##B_{lm}##. Each tensor ##A## and ##B## has in general ##16## components, so the product ##P## starts with ##16\times 16=256## distinct components. Now impose the two independent antisymmetries:$$P_{iklm}=-P_{kilm}\Rightarrow A_{ik}B_{lm}=-A_{ki}B_{lm}\Rightarrow A\text{ has 6 components}$$$$P_{iklm}=-P_{ikml}\Rightarrow A_{ik}B_{lm}=-A_{ik}B_{ml}\Rightarrow B\text{ has 6 components}$$So the two antisymmetries together give ##P=A\times B## a total of ##6\times 6=36## independent components. The same argument applies to ##R_{iklm}##.
This method is different from what my proffessor told us ...
And it is easier. Thank you.

Problem is solved. Thank You, Everyone!
 
  • #19
renormalize said:
Consider the rank-4 product ##P_{iklm}=A_{ik}B_{lm}## of two arbitrary rank-2 tensors ##A_{ik}## and ##B_{lm}##. Each tensor ##A## and ##B## has in general ##16## components, so the product ##P## starts with ##16\times 16=256## distinct components. Now impose the two independent antisymmetries:$$P_{iklm}=-P_{kilm}\Rightarrow A_{ik}B_{lm}=-A_{ki}B_{lm}\Rightarrow A\text{ has 6 components}$$$$P_{iklm}=-P_{ikml}\Rightarrow A_{ik}B_{lm}=-A_{ik}B_{ml}\Rightarrow B\text{ has 6 components}$$So the two antisymmetries together give ##P=A\times B## a total of ##6\times 6=36## independent components. The same argument applies to ##R_{iklm}##.
Hello. I've thought about your suggested method. What I've understand is that because of ##P_{iklm}=-P_{kilm}\Rightarrow A_{ik}B_{lm}=-A_{ki}B_{lm}## A can only have 6 independent components but components of B are unaffected. So till now we have 16*6=96 independent components.
After applying ##P_{iklm}=-P_{ikml}\Rightarrow A_{ik}B_{lm}=-A_{ik}B_{ml}## Which does not affect A But affects B, B can have only 6 independent components. Applying both gives us a 6*6 matrix with 36 independet components. Am I right?!
 

FAQ: How many independent components does a tensor have?

What factors determine the number of independent components of a tensor?

The number of independent components of a tensor depends on the tensor's rank (or order) and the dimensionality of the space in which it resides. For example, in an n-dimensional space, a rank-2 tensor would have n^2 components, but the actual number of independent components can be reduced by symmetries or antisymmetries.

How many independent components does a rank-2 tensor have in 3-dimensional space?

A general rank-2 tensor in 3-dimensional space has 3^2 = 9 components. However, if the tensor has certain symmetries (such as being symmetric or antisymmetric), the number of independent components can be reduced. For instance, a symmetric rank-2 tensor has 6 independent components, while an antisymmetric rank-2 tensor has 3 independent components.

What is the difference between a symmetric and an antisymmetric tensor in terms of independent components?

A symmetric tensor has components that are invariant under the exchange of indices, which reduces the number of independent components. For example, a symmetric rank-2 tensor in n-dimensional space has n(n+1)/2 independent components. An antisymmetric tensor, on the other hand, changes sign under the exchange of indices and has n(n-1)/2 independent components.

How do you calculate the number of independent components of a rank-3 tensor in 4-dimensional space?

A general rank-3 tensor in 4-dimensional space has 4^3 = 64 components. If there are no symmetries, all 64 components are independent. If the tensor has symmetries, such as being totally symmetric or totally antisymmetric, the number of independent components would be reduced accordingly.

Can the number of independent components of a tensor be affected by the metric of the space?

Yes, the metric of the space can affect the number of independent components of a tensor. For example, in a space with a specific metric, certain components of the tensor might be related to each other, effectively reducing the number of independent components. This is particularly relevant in the context of general relativity, where the metric tensor itself has symmetries that reduce its independent components.

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