Analogy question for algebraists

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SUMMARY

Polynomials with one variable and coefficients in the field K are analogous to finite dimensional K vector spaces, while polynomials in several variables over the field K relate to the tensor product of multiple vector spaces corresponding to the number of variables. This analogy is grounded in concepts from linear algebra, particularly as discussed in Axler's "Linear Algebra Done Right," which explores the implications of linear transformations and their relationship to eigenvalues and eigenvectors. The discussion seeks consensus among algebraists regarding this analogy.

PREREQUISITES
  • Understanding of polynomials and their properties in algebra.
  • Familiarity with vector spaces and their dimensions.
  • Knowledge of linear transformations and their effects on vectors.
  • Concepts of eigenvalues and eigenvectors as presented in linear algebra literature.
NEXT STEPS
  • Study the tensor product of vector spaces in detail.
  • Explore the relationship between linear transformations and polynomial equations.
  • Investigate the role of eigenvalues and eigenvectors in higher-dimensional spaces.
  • Read Axler's "Linear Algebra Done Right" for deeper insights into linear algebra concepts.
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Algebraists, mathematics students, and educators interested in the relationships between polynomials, vector spaces, and linear transformations.

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TL;DR
Polynomials with one variable and coefficients in the field K are to finite dimensional K vector spaces as polynomials in several variables over the field K are to ....?
An "analogy question":

Polynomials with one variable and coefficients in the field K are to finite dimensional K vector spaces as polynomials in several variables over the field K are to ....?

As a teenager, I recall taking tests that had "analogy questions" on them. The format was: Thing A is to thing B as Thing C is to ...what? They had objectively correct answers - at least in the mind of the people that posed them.

So I'm wondering if the above question has an answer that most algebraists would agree with. Thanks to Axler's book Linear Algebra Done Right, I can see that iterating a linear transformation ##T## applied to a particular vector ##v## leads to the existence of a (finite degree) polynomial in powers of ##Tv## that must equal to zero. That heads toward the topic of eigenvalues and eigenvectors. I don't know if there is some analogy to that situation that involves polynomials in several variables.
 
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... to the tensor product of as many vector spaces as there are variables.
 

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