Covariant equation intuition confusing me

In summary, the components of a vector in two dimensions are defined in relation to a change of coordinates from (x,y) to (x',y'), with the contravariant components transforming using the inverse matrix and the covariant components using the same matrix. This approach is considered obsolete and the modern approach defines a vector space V and its dual space V*, with components transforming contravariantly and covariantly respectively. All tensors are reference frame independent, but their components with respect to an ordered basis are not. One form refers to the old term for a co-variant vector in this approach.
  • #1
NotASmurf
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Hey all, I've just started tensor analysis but do not understand why in contravarient uses 1 and covarient uses 2, could someone please explain these? Perhaps my understanding of the definitions is causing me to misunderstand why its written like this. Any help appreciated.
co.png
 
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  • #2
Can you explain your notation? What are "x',y',x,y" supposed to be in this picture?
 
  • #3
"The components of a vector in two dimensions are defined in the literature in relation to a change of coordinates from (x,y) to (x',y'), say. The contravariant components are those which transform as follows e.g. for the new coordinate x' in terms of the old (x,y):"
 
  • #4
NotASmurf said:
"The components of a vector in two dimensions are defined in the literature in relation to a change of coordinates from (x,y) to (x',y'), say. The contravariant components are those which transform as follows e.g. for the new coordinate x' in terms of the old (x,y):"

That is some seriously confusing notation. What book is this?

A change of coordinates from (x,y) to (x',y') looks simply like ##x'=x'(x,y),~y'=y'(x,y)## so these are simply functions of the old coordinates. Vector and one form components transform similarly to the picture you uploaded, but I've never seen that kind of notation. Usually the notation is such that for a vector: $$V^{\alpha'} = \sum_\beta \frac{\partial x^{\alpha'}}{\partial x^\beta} V^\beta$$ And for a one form: $$\omega_{\alpha'}=\sum_\beta \frac{\partial x^\beta}{\partial x^{\alpha'}}\omega_\beta$$
 
  • #5
Those equations and the corresponding ones for y' define covariant and contravariant in this (obsolete and horrible) approach to tensors, so it's a bit odd to ask why the equations look the way they do. It does however make sense to ask why those terms are used. The idea is that in the covariant case, the matrix that transforms ##\begin{pmatrix}x\\ y\end{pmatrix}## to ##\begin{pmatrix}x'\\ y'\end{pmatrix}## is the same matrix that transforms the basis vectors (hence the term covariant), and in the contravariant case, the matrix that does the transformation is the inverse of the matrix that transforms the basis vectors (hence the term contravariant).

The modern approach starts with a vector space V. Its dual space V* is defined as the vector space of linear maps from V into ℝ. Now suppose that ##(e_1,\dots,e_n)## and ##(e_1',\dots,e_n')## are ordered bases for V. There must exist numbers ##M^j_i## such that ##e_i'=M^j_i e_j## (each of the primed basis vectors can be expressed as a linear combination of the unprimed basis vectors). Now we can examine the relationship between the components of an arbitrary ##v\in V## with respect to these two ordered bases. It turns out that it's given by ##v^i{}'=(M^{-1})^i_j v^j##. Because of this, the n-tuple of components is said to "transform contravariantly".

Edit: I fixed a typo in the paragraph above after it was pointed out by Matterwave below.

There's a simple way to use an ordered basis for V to define an ordered basis for V*. Because of this, it makes sense to ask for the relationship between the components of an arbitrary ##f\in V^*## with respect to the two ordered basis for ##V^*## that are defined from the two ordered bases for ##V## mentioned above. It turns out that the relationship is given by ##f_i'=M_i^j f_j##. Because of this, the n-tuple of components is said to "transform covariantly".

You can find many of the details of this approach in this post. I also recommend chapter 3 in "A first course in general relativity" by Schutz. It's a nice introduction to this stuff.
 
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  • #6
Thank you so much.
 
  • #7
Fredrik said:
There must exist numbers ##M^j_i## such that ##e_i'=M^j_i e_i##

I believe you mean ##e_i'=M^j_i e_j## :)
 
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  • #8
Fredrik said:
in the contra-variant case, the matrix that does the transformation is the inverse of the matrix that transforms the basis vectors
Confusion, in the video teaching me this they say that
equation 4 is the contravarient one and that equation 5 (the inverse) is the covariant one, your intuition made sense but this confused me now, his notation isn't helping.
cov.png


Also covarient is the one that is reference frame independent right? Apologies for newbie-ness.
 
  • #9
See post #4, "contra variant vector" is the old term for "vector" and "co variant vector" is the old term for "one form". Contra variant tensors have indices up and co variant tensors have indices down.

All tensors are "reference frame independent", in the appropriate sense.
 
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  • #10
NotASmurf said:
Confusion, in the video teaching me this they say that
equation 4 is the contravarient one and that equation 5 (the inverse) is the covariant one, your intuition made sense but this confused me now, his notation isn't helping.
In my notation, the first one is ##T_y^{mn}=(M^{-1})^m{}_r(M^{-1})^n{}_s T_x^{rs}## and the second one is ##T_{mn}(y)=M^r{}_m M^s{}_n T_{rs}(x)##.

NotASmurf said:
Also covarient is the one that is reference frame independent right?
Elements of ##V## and elements of ##V^*## are all independent of the frame (=the ordered basis). But their components with respect to an ordered basis are not.
 
  • #11
Matterwave said:
I believe you mean ##e_i'=M^j_i e_j## :)
Yes, thanks. I wrote that post very quickly. I have edited that typo now. Also, it would have been even better to write ##e_i'=M^j{}_i e_j##, because when we start using the metric to raise and lower indices, we're going to have to keep track of the horizontal positions of the indices.
 
  • #12
Matterwave said:
See post #4, "contra variant vector" is the old term for "vector" and "co variant vector" is the old term for "one form". Contra variant tensors have indices up and co variant tensors have indices down.

All tensors are "reference frame independent", in the appropriate sense.
one form? what does that mean?
Thanks for help so far, I liked your definition of contravarient.
 
  • #13
NotASmurf said:
one form? what does that mean?
Thanks for help so far, I liked your definition of contravarient.
There's a vector space ##T_pM## associated with each point ##p## in a smooth manifold ##M##. An element of ##T_pM## is called a tangent vector at ##p##. An element of ##T_pM^*## is called a cotangent vector at ##p##. A vector field on ##M## is a function that associates a tangent vector at ##p## with each ##p\in M##. A cotangent vector field on ##M## is a function that associates a cotangent vector at ##p## with each ##p\in M##. A cotangent vector field is also called a 1-form (for reasons that I will not go into here).
 
  • #14
NotASmurf said:
one form? what does that mean?
Thanks for help so far, I liked your definition of contravarient.

For now, you can just think of it as simply another way to say "co variant vector". The language of forms (there are 0-forms, 1-forms, 2-forms, etc.), mostly worked through by Elie Cartan, is a very powerful one in differential geometry. It gives a rigorous definition of integration on manifolds, a connection and congruence independent definition of a derivative (called an exterior derivative), as well as a generalization of the fundamental theorem of calculus (called Stoke's theorem) on manifolds. But until you get to that, "one form" will just be another word for "co variant vector".
 

1. What is a covariant equation?

A covariant equation is a mathematical expression that describes the relationship between two or more variables in a way that is consistent with the principles of covariance. This means that the equation remains the same even when the variables are transformed or changed, as long as the underlying relationship between the variables remains the same.

2. Why is the concept of covariance confusing?

The concept of covariance can be confusing because it is a fundamental concept in mathematics that can be applied to a variety of fields, such as physics and statistics. It requires a solid understanding of mathematical concepts, such as linear algebra and tensor calculus, which can be difficult to grasp. Additionally, the notation used for covariance can vary depending on the field, adding to the confusion.

3. How does covariance relate to the concept of symmetry?

Covariance and symmetry are closely related concepts. Covariance describes how an equation or relationship between variables remains the same even when the variables are transformed. This is similar to the concept of symmetry, which describes how an object or system remains the same under certain transformations. In fact, covariance is a mathematical representation of symmetry.

4. Can you provide an example of a covariant equation?

One example of a covariant equation is the equation for the conservation of energy in physics, which states that the total energy in a closed system remains constant over time. This equation remains the same even when the variables, such as the types of energy present or the location of the system, are changed.

5. Why is understanding covariant equations important?

Covariant equations are important because they allow us to describe and understand complex relationships between variables in a way that is consistent and invariant under transformations. This is crucial in many fields, such as physics and engineering, where understanding the underlying principles and laws is essential for making accurate predictions and solving problems.

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