Isomorphic Finite Dimensional Vector Spaces

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Discussion Overview

The discussion centers on the concept of isomorphic finite dimensional vector spaces, particularly the conditions under which two vector spaces can be considered isomorphic. Participants explore the implications of dimensionality and the requirements for vector spaces to be over the same field, referencing the text "Linear Algebra Done Right" by Axler.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant expresses confusion about the assertion that two vector spaces are isomorphic if and only if they have the same dimension, suggesting that there may be cases where spaces with the same dimension are not isomorphic, particularly when considering different operations or fields.
  • Another participant provides a definition of isomorphism through a linear transformation between two n-dimensional vector spaces over the same base field, implying that such a transformation guarantees isomorphism.
  • A participant reiterates the importance of the field over which the vector spaces are defined, arguing that the counterexample presented does not constitute a valid vector space due to the lack of a field of scalars.
  • Some participants note that the text does not explicitly state the assumptions about the fields or vector spaces, leading to confusion about the conditions necessary for the theorem discussed.
  • One participant mentions their preference for more rigorous texts that clarify the assumptions and definitions, particularly regarding linear maps and the requirement for vector spaces to be over the same field.

Areas of Agreement / Disagreement

Participants express differing views on the implications of dimensionality and the necessity of defining vector spaces over the same field. While some agree on the definition of isomorphism, others remain uncertain about the assumptions made in the text and the validity of proposed counterexamples.

Contextual Notes

Participants highlight limitations in the text regarding explicit assumptions about fields and vector spaces, which may lead to misunderstandings. The discussion reflects a range of familiarity with abstract algebra concepts, impacting the clarity of the arguments presented.

TheOldHag
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I'm going through the text "Linear Algebra Done Right" 2nd edition by Axler. Made it to chapter 4 with one problem I'm unable to understand fully. The theory that two vector spaces are isomorphic if and only if they have the same dimension. I can see this easily in one direction, that is, isomorphic vector spaces will have the same dimension, but it seems I can imagine vector spaces having the same dimension but for which they are not isomorphic. Perhaps one vector space would be 2-tuples over the integers but the with modular operators limiting the number of elements in the space and another vector space of integer 2-tuples without modular operators. The latter space would have more element in it so how would any map from the former to the latter be surjective? And yet do they not have the same dimension?

I'm guessing he is making assumptions about the operations on the vector spaces and they are over R or C. However, this assumption is made on many of the theories this particular theory doesn't state V explicitly and so I'm not sure what part of this theory the assumptions fall under.

Any clarification on this would be appreciated.
 
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Let V and W be n-dimensional vector spaces over the same base field F. Fix bases {e1,...,en} and {f1,...,fn} for V and W respectively. Define a linear transformation φ:V→W by setting φek = fk and extending by linearity. This is an isomorphism.
 
TheOldHag said:
. Perhaps one vector space would be 2-tuples over the integers but the with modular operators limiting the number of elements in the space and another vector space of integer 2-tuples without modular operators. The latter space would have more element in it so how would any map from the former to the latter be surjective? And yet do they not have the same dimension?

I'm guessing he is making assumptions about the operations on the vector spaces and they are over R or C. However, this assumption is made on many of the theories this particular theory doesn't state V explicitly and so I'm not sure what part of this theory the assumptions fall under.

Any clarification on this would be appreciated.

It's a vector space, so it's a vector space over a field.. R, C, Q or any other random field will work. Both vector spaces have to be over the same field but that's the only requirement - note your attempt at a counterexample is not a vector space because there is no field of scalars ( well, when you mod out if it's by a prime number there is)
 
That answers it for me. Basically, I haven't gone over abstract algebra yet so I think in this case I just have to move forward and assume the notion of field will clear up that detail later. Thanks.
 
TheOldHag said:
That answers it for me. Basically, I haven't gone over abstract algebra yet so I think in this case I just have to move forward and assume the notion of field will clear up that detail later. Thanks.

Since Axler apparently does not introduce abstract fields, just read my post again with the first line changed to: "Let V and W be n-dimensional real or complex vector spaces." The argument is the same from there.
 
Your post has gotten me thinking about the very definition of liner map. I do better with more rigorous text only because they don't omit tedious and trivial details. For instance, he defines a linear map as having homogeneity and additivity and leaves it to the reader to deduce that V and W have to be vector spaces over the same field by the fact that the constant 'a' appears in both side of the equation of homogeneity. Yes, it should be obvious but I do better when it is spelled out. Perhaps it would have been more clear if he qualified that a linear map was a function between vector spaces over the same field.

Nevertheless at the beginning of each chapter he states the assumption that F is R or C and that V is a vector space over F. However, the theorem I was confused about didn't mention V or F at all.

From what I can tell though, this is a great book for self study.
 

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