How Does Covector Existence Relate to Tensor Dimensions in Winitzki's Lemma 3?

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In summary, Peter is reading Sergei Winitzki's book on Linear Algebra via Exterior Products and is currently focused on Section 1.7.3. He needs help understanding an aspect of the proof of Lemma 3 in this section. Winitzki's text mentions the existence of a covector f^* in V^* that satisfies certain conditions. Peter is struggling to show this from first principles and is unsure of the relevance of Exercise 1 in Section 6.3. However, after receiving clarification on the author's use of notation, Peter now has a better understanding of the proof and is grateful for the help provided by Samy and Andrew.
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I am reading Segei Winitzki's book: Linear Algebra via Exterior Products ...

I am currently focused on Section 1.7.3 Dimension of a Tensor Product is the Product of the Dimensions ... ...

I need help in order to get a clear understanding of an aspect of the proof of Lemma 3 in Section 1.7.3 ...

The relevant part of Winitzki's text reads as follows:
?temp_hash=9370430caeb830ed3fa7ba46922fa5c7.png

?temp_hash=9370430caeb830ed3fa7ba46922fa5c7.png


In the above quotation from Winitzki we read the following:

" ... ... By the result of Exercise 1 in Sec. 6.3 there exists a covector [itex]f^* \in V^*[/itex] such that

[itex]f^* ( v_j ) = \delta_{ j_1 j }[/itex] for [itex]j = 1, \ ... \ ... \ , \ n[/itex] ... ... "I cannot see how to show that there exists a covector [itex]f^* \in V^*[/itex] such that

[itex]f^* ( v_j ) = \delta_{ j_1 j }[/itex] for [itex]j = 1, \ ... \ ... \ , \ n[/itex] ... ...Can someone help me to show this from first principles ... ?It may be irrelevant to my problem ... but I cannot see the relevance of Exercise 1 in Section 6 which reads as follows:
?temp_hash=9370430caeb830ed3fa7ba46922fa5c7.png
Exercise 1 refers to Example 2 which reads as follows:
?temp_hash=9370430caeb830ed3fa7ba46922fa5c7.png

?temp_hash=9370430caeb830ed3fa7ba46922fa5c7.png


BUT ... since I wish to show the result:

... ... ... "there exists a covector [itex]f^* \in V^*[/itex] such that

[itex]f^* ( v_j ) = \delta_{ j_1 j }[/itex] for [itex]j = 1, \ ... \ ... \ , \ n[/itex] ... ..."... from first principles the above example is irrelevant ... BUT then ... I cannot see its relevance anyway!Hope someone can help ... ...

Peter

===========================================================

*** NOTE ***

To help readers understand Winitzki's approach and notation for tensors I am providing Winitzki's introduction to Section 1.7 ... ... as follows ... ... :
?temp_hash=e67c8c3ac372f69967191c4fbbbc85c6.png

?temp_hash=e67c8c3ac372f69967191c4fbbbc85c6.png

?temp_hash=e67c8c3ac372f69967191c4fbbbc85c6.png
 

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  • Winitzki - 1 - Lemma 3 - Section 1.7.3 - PART 1      ....png
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  • Winitzki - Exercise 1 - Section 1.6            ....png
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  • Winitzki - 1 - Example 2 - Section 1.6 - PART 1      ....png
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  • Winitzki - 1 - Section 1.7 - PART 1     ....png
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  • #2
Math Amateur said:
In the above quotation from Winitzki we read the following:

" ... ... By the result of Exercise 1 in Sec. 6.3 there exists a covector [itex]f^* \in V^*[/itex] such that

[itex]f^* ( v_j ) = \delta_{ j_1 j }[/itex] for [itex]j = 1, \ ... \ ... \ , \ n[/itex] ... ... "I cannot see how to show that there exists a covector [itex]f^* \in V^*[/itex] such that

[itex]f^* ( v_j ) = \delta_{ j_1 j }[/itex] for [itex]j = 1, \ ... \ ... \ , \ n[/itex] ... ...Can someone help me to show this from first principles ... ?
Read what lavinia explained here:
lavinia said:
If one has a basis ##e_{i}## for the vectors space, then a basis for the vector space of covectors - called the dual basis are the linear maps ##π_{i}## defined by ##π_{i}(e_{j}) = δ_{ij}## This is the covector that assigns 1 to the i'th basis vector and zero to all of the others - as mentioned already above. For each choice of basis ##e_{i}## one has a corresponding choice of basis ##π_{i}## for the vector space of covectors.

The covectors ##v_{i}## mentioned above are the same as the covectors ##π_{i}##. So the function that picks out the i'th coordinate of a vector with respect to a basis is a covector.
 
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  • #3
Math Amateur said:
In the above quotation from Winitzki we read the following:

" ... ... By the result of Exercise 1 in Sec. 6.3 there exists a covector [itex]f^* \in V^*[/itex] such that

[itex]f^* ( v_j ) = \delta_{ j_1 j }[/itex] for [itex]j = 1, \ ... \ ... \ , \ n[/itex] ... ... "I cannot see how to show that there exists a covector [itex]f^* \in V^*[/itex] such that

[itex]f^* ( v_j ) = \delta_{ j_1 j }[/itex] for [itex]j = 1, \ ... \ ... \ , \ n[/itex] ... ...Can someone help me to show this from first principles ... ?
Firstly, the author's use of notation is unhelpful, because they are using ##f^*## for two very different maps, one from ##V## to ##\mathbb{R}## and one from ##V\otimes W## to ##\mathbb{R}##. They should use different symbols for the two different maps.

Let's assume ##f^*## refers only to the first map. We show there exists such a map (which is a covector) simply by defining its operation on a set of basis vectors, and then extending it to cover the whole of the domain ##V## using the linearity rules. To be very clear, let's use a different symbol. Given a basis ##B\equiv \{v_1,...,v_n\}## for ##V##, we first define a function ##g^{j_1}:B\to\mathbb{R}## by

$$g^{j_1}(v_k)=\delta_k^{j_1}$$

for ##k\in\{1,...,n\}##.

Then we define ##f^*## to be the linear function from ##V## to ##\mathbb{R}## that agrees with ##g^{j_1}## on ##B##. It is a basic result of linear algebra (no tensors required) that such a function exists and is unique. If you are not comfortable just accepting that fact, a proof should be easy to find in any decent linear algebra text, or it's easy to prove from scratch. The existence follows from the fact that ##\{v_1,...,v_n\}## spans ##V##. To prove uniqueness, assume there are two such extension functions. Then their difference is also a linear function from ##V## to ##\mathbb{R}## and, by looking at its operation on the basis vectors, it's easily seen to be identically zero.
 
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  • #4
Thanks Samy and Andrew ... appreciate the help ...

Still working through the Lemma ... but I must say Andrew, your point on the notation really changed things for me ... I now have a pretty good understanding regarding what is going on in the proof of Lemma 3 ...

Thanks again,

Peter
 

Related to How Does Covector Existence Relate to Tensor Dimensions in Winitzki's Lemma 3?

1. What is the definition of a tensor?

A tensor is a mathematical object that represents a relationship between sets of vectors and covectors. It is a generalization of scalars, vectors, and matrices, and can have any number of indices.

2. What is the significance of Winitzki's Lemma 3 in tensor analysis?

Winitzki's Lemma 3 is an important result in tensor analysis that provides a way to simplify the calculation of derivatives of tensor fields. It states that the derivative of a tensor field can be expressed in terms of the partial derivatives of its components, making it easier to work with in practical applications.

3. Can you explain the notation used in Winitzki's Lemma 3?

The notation used in Winitzki's Lemma 3 involves the use of Einstein summation convention, where repeated indices are implicitly summed over. It also uses the notation of partial derivatives, denoted by a comma followed by the corresponding index.

4. What are the assumptions made in Winitzki's Lemma 3?

Winitzki's Lemma 3 assumes that the tensor field is smooth and that the coordinate system used is also smooth. It also assumes that the tensor field is defined on a manifold with a well-defined metric.

5. How is Winitzki's Lemma 3 used in practical applications?

Winitzki's Lemma 3 is used in various fields such as physics, engineering, and computer science, where tensor analysis is commonly used. It allows for the efficient calculation of derivatives of tensor fields, making it a valuable tool in a range of applications, including mechanics, electromagnetism, and general relativity.

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