Do Vectors Remain Invariant and What Defines Tensor Rank?

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Discussion Overview

The discussion revolves around the invariance of vectors under coordinate transformations and the definition of tensor rank. Participants explore the implications of these concepts in the context of vector and tensor mathematics, focusing on the terminology and definitions related to tensor rank.

Discussion Character

  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant asserts that while the components of a vector change under a coordinate transformation, the vector itself remains invariant.
  • Another participant proposes that a tensor of rank 1 can be expressed as the product of contravariant and covariant components, questioning whether this means both T^a and R_a are tensors of rank one or if V = (T^a)(R_a) is the tensor of rank one.
  • A different participant agrees that the components of a vector change with the basis, but the vector itself does not depend on coordinates, supporting the first participant's assertion.
  • One participant clarifies that when counting tensor rank, only the indices on the components should be considered, not the basis, suggesting a specific approach to defining rank.

Areas of Agreement / Disagreement

Participants generally agree on the invariance of vectors under coordinate transformations, but there is some contention regarding the definition of tensor rank and how it should be counted.

Contextual Notes

There are unresolved aspects regarding the terminology of 'rank' and how it applies to tensors, particularly in distinguishing between contravariant and covariant components.

TupoyVolk
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"The components of a vector change under a coordinate transformation, but the vector itself does not."
ie:
V = a*x + b*y = c*x' + d*y'
Though the components (and the basis) have changed, V is still = V.
Question 1:
Is that right? (I'm assuming so, the main Q is below)

Tensor rank (according to wolfram)
"The total number of contravariant and covariant indices of a tensor."
It is commonly said
"A vector is a tensor of rank 1"

Does this mean (A):
T^a, and R_a
are tensors of rank one

or does it mean (B):
V = (T^a)(R_a) is a tensor of rank one?

If it is (A), then how can a vector be regarded as a tensor of rank 1, when it is
(contravariant components)*(covariant basis)

I'm able to do the maths, but the terminology of 'rank' has been bugging me! :blushing:
 
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Gah, I'm pretty sure from clicking the linked definition of tensor on here, I got the answer :P

Tensor of rank 1 = V^a*e_a

Components of a tensor of rank 1 = V^a.

Oui?
 
The components of a vector change when the basis is changed, but the vector does not, since a vector is something that exists without coordinates.

So your question 1 is right.

As for your other question, you don't count the basis when counting rank, just the indices on the component. If there are no indices on the components, then count the indices of the basis. But don't count both.
 
Cheers! Much appreciated.
 

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