Proving the Associative Property for Polynomials in Linear Algebra

In summary, the conversation discusses how to show that the axiom for polynomial addition holds for polynomials in the form of a_0 + a_1 x + a_2 x^2. The conversation also confirms that these polynomials can be treated as vectors for the purpose of this proof.
  • #1
TranscendArcu
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Homework Statement



Show that the axiom [itex]\vec{A} + (\vec{B} + \vec{C}) = (\vec{A} + \vec{B}) + \vec{C}[/itex] holds for polynomials of the form [itex]a_0 + a_1 x + a_2 x^2[/itex]

The Attempt at a Solution


I'm pretty new to writing proofs for linear algebra so my first question is should I be treating the polynomials as the vectors? That is, should I write something like,

[itex]a^A_0 + a^A_1 x + a^A_2 x^2 + (a^B_0 + a^B_1 x + a^B_2 x^2 + a^C_0 + a^C_1 x + a^C_2 x^2) = (a^A_0 + a^A_1 x + a^A_2 x^2 + a^B_0 + a^B_1 x + a^B_2 x^2) + a^C_0 + a^C_1 x + a^C_2 x^2[/itex]

?
I don't think this is correct since the polynomials aren't really vectors (right?). But I'm not sure how else to place these polynomials into the axioms.
 
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  • #2
Yes, the polynomials under their usual operations are vectors ( since they form a vector space, and this is what you are trying to show ). It's simple: any element of a space that is a vector space, is a vector.
The key point is that you are proving this with respect to a specific operation, and a specific set of objects ( you already know how to add and subtract these elements, you just have to show that they *also* satisfy these other vector space properties )
 
  • #3
effectively you can treat [itex] a_0 + a_1 x + a_2 x^2 [/itex] as [itex] (a_0,a_1,a_2)^T [/itex] as the polynomials 1,x,x^2 are linearly independent
 

FAQ: Proving the Associative Property for Polynomials in Linear Algebra

What is linear algebra?

Linear algebra is a branch of mathematics that deals with the study of vector spaces and linear transformations between them. It involves the use of algebraic methods and techniques to solve problems involving linear equations, matrices, and systems of equations.

What are the axioms of linear algebra?

The axioms of linear algebra are a set of fundamental rules that govern the behavior of vector spaces. They include the axioms of addition, scalar multiplication, and distributivity, among others. These axioms serve as the foundation for all calculations and operations in linear algebra.

Why are axioms important in linear algebra?

Axioms are important in linear algebra because they provide a set of consistent and logical rules that allow us to perform calculations and operations on vector spaces and matrices. Without axioms, there would be no clear rules or guidelines for solving problems in linear algebra, making it difficult to establish a solid understanding of the subject.

How do the axioms of linear algebra relate to real-world applications?

The axioms of linear algebra have numerous real-world applications, particularly in fields such as physics, engineering, and computer science. They are used to model and solve complex systems, such as electrical circuits, fluid dynamics, and quantum mechanics. Additionally, linear algebra is essential for data analysis and machine learning, making it a crucial tool in modern technology.

What are some common misconceptions about linear algebra axioms?

One common misconception about linear algebra axioms is that they are only applicable to two-dimensional or three-dimensional spaces. In reality, they can be applied to any number of dimensions and are not limited to a specific number of variables. Additionally, some may mistakenly believe that the axioms are rigid and cannot be altered, but they can be adapted and extended to fit different contexts and applications.

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