Abstract algebra vector space problem

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SUMMARY

The discussion revolves around solving a vector space problem involving a bijection f: R² -> V, where V is defined by the basis span(v1, v2). The user seeks to utilize the inner product to derive the inverse map f⁻¹: V -> R² and form a matrix equation to find coefficients in R² for any vector v in V. Key insights include the realization that inner products can be assembled into a matrix, although the user initially struggles with the abstract nature of the inner product and its application beyond orthogonal bases.

PREREQUISITES
  • Understanding of vector spaces and their properties
  • Familiarity with inner product spaces and their axioms
  • Knowledge of matrix equations and linear transformations
  • Experience with bijections and their inverses in mathematical contexts
NEXT STEPS
  • Study the properties of inner products in vector spaces
  • Learn how to construct and manipulate matrices representing linear transformations
  • Explore the concept of orthogonal bases and their significance in inner product spaces
  • Investigate the application of the Gram-Schmidt process for obtaining orthogonal bases
USEFUL FOR

Students and educators in mathematics, particularly those focusing on linear algebra, vector spaces, and inner product theory. This discussion is beneficial for anyone looking to deepen their understanding of abstract algebra concepts and their applications.

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Homework Statement


We have a vector space (V, R, +, *) (R being Real numbers, sorry I couldn't get latex work..) with basis V = span( v1,v2). We also have bijection f: R² -> V, such as f(x,y) = x*v1+y*v2.

Assume you have inner-product ( . , . ): V x V -> R. ( you can use it abstractly and assume the axioms hold ). Now we can assemble the inverse map of the given bijection f, such as f⁻¹: V -> R². With the help of inner-product, form a matrix equation to find the coefficient pair f⁻¹(v) in R² for any arbitrary v in V.

The Attempt at a Solution


I have tried to assemble the matrix, but my problem is, I don't understand how to use the inner-product as an abstract object. I don't see how it helps me to know that i get a real number from the inner-product, since I fail to see what that real number expresses here. As far as I have understood, the inner-product can be defined the way the modeler/mathematician as long as the axioms still hold. Could someone give me any pointers in this? Should I just read definition of inner-products more carefully?
...
edit: I figured out something, which seems to be close to it, but it apparently is satisfactory only if basis is an orthogonal basis.

I figured that since we have inner-product, we also have norm, so we get
A=[[norm(v1) 0];[0 norm(v2)]],
X=[x y],
B=v,
when equation is A*X=B. I'm now struggling to get it work for all basis. Could someone atleast tell me have I got it right so far?
 
Last edited:
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[tex]<v,v_1>=<xv_1+yv_2,v_1>=x<v_1,v_1>+y<v_2,v_1>[/tex]
and
[tex]<v,v_2>=x<v_1,v_2>+y<v_2,v_2>[/tex]

If you know all the inner products how would you solve for x and y?

You can't really do something like what you're trying, because v isn't a vector in R2, and if you want to convert it to one the only way that you have is to get f-1(v), which is what the problem is in the first place
 
Office_Shredder said:
[tex]<v,v_1>=<xv_1+yv_2,v_1>=x<v_1,v_1>+y<v_2,v_1>[/tex]
and
[tex]<v,v_2>=x<v_1,v_2>+y<v_2,v_2>[/tex]

If you know all the inner products how would you solve for x and y?

You can't really do something like what you're trying, because v isn't a vector in R2, and if you want to convert it to one the only way that you have is to get f-1(v), which is what the problem is in the first place

I see, I went wrong trying to think in R² too much..
As for the solution, apparently I just have to assemble those inner-products into a matrix now. Could you tell me how you came up with those inner-products? Was it just because there wasn't anything else known? Or was it a sophisticated guess based on experience? I still can't figure out, if those inner-products have somekind of meaning, or are they there just because they happen to solve this particular problem?
 

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