Vector Space: Fifth-Degree Polynomials

In summary, a vector space is a mathematical structure consisting of a set of objects called vectors that can be added and multiplied by scalars. It is related to fifth-degree polynomials and can be used to represent them, with the dimension of a vector space of fifth-degree polynomials being six. Examples of such vector spaces include those with real, complex, or binary coefficients. Vector spaces of fifth-degree polynomials have practical applications in fields such as signal processing, computer graphics, and physics, where they can be used to analyze and model data and solve problems.
  • #1
eyehategod
82
0
15. Determine wheter the set is a vector space.
The set of all fifth-degree polynomials with the standard operations.
AXIOMS
1.u+v is in V
2.u+v=v+u
3.u+(v+w)=(u+v)+w
4.u+0=u
5.u+(-u)=0
6. cu is in V
7.c(u+v)=cu+cv
8.(c+d)u=cu+cd
9.c(du)=(cd)u
10.1(u)=u

the axioms that fail are 1,4,5, and 6. I don't know why 4,5,and 6 fail. Can anyone help me?
 
Physics news on Phys.org
  • #2
How is the degree of a polynomial defined? Now, what is the additive identity, and is it a fifth-degree polynomial?
 
  • #3


A vector space is a mathematical structure that satisfies a set of axioms, which are a set of rules that define how the elements in the space behave. In order for a set to be a vector space, it must satisfy all of the axioms.

In this case, the set of all fifth-degree polynomials with the standard operations satisfies all of the axioms except for 4, 5, and 6. These axioms state that for any vector u in the set, there must exist a zero vector (0) and an additive inverse (-u) that also belong to the set, and that any scalar multiple of a vector in the set must also belong to the set.

In the set of fifth-degree polynomials, there is no zero vector (a polynomial with all coefficients equal to 0) and there is no additive inverse for every polynomial. Additionally, not all scalar multiples of a polynomial will result in a fifth-degree polynomial. For example, if we multiply a fifth-degree polynomial by 2, the resulting polynomial will have a degree of 10, which does not belong to the set. Therefore, this set does not satisfy the axioms and is not a vector space.

It is important to note that the axioms must hold for all possible vectors and scalars in the set, not just for a specific example. In this case, the failure of axioms 4, 5, and 6 means that the set is not closed under addition and scalar multiplication, which is a fundamental property of a vector space.
 

FAQ: Vector Space: Fifth-Degree Polynomials

What is a vector space?

A vector space is a mathematical structure that consists of a set of objects called vectors, which can be added together and multiplied by scalars (numbers). This set of vectors must satisfy certain properties, such as closure under addition and scalar multiplication, to be considered a vector space.

How is a vector space related to fifth-degree polynomials?

A vector space can be used to represent fifth-degree polynomials. In this case, the vectors would be the coefficients of the polynomial, and the scalars would be real numbers. The vector space would also have operations defined for addition and scalar multiplication, making it a suitable structure for representing polynomials.

What is the dimension of a vector space of fifth-degree polynomials?

The dimension of a vector space of fifth-degree polynomials is six. This is because a fifth-degree polynomial can be uniquely determined by six coefficients (one for each degree from 0 to 5).

What are some examples of vector spaces of fifth-degree polynomials?

Some examples of vector spaces of fifth-degree polynomials include the set of all fifth-degree polynomials with real coefficients, the set of all fifth-degree polynomials with complex coefficients, and the set of all fifth-degree polynomials with binary coefficients (0 or 1).

How are vector spaces of fifth-degree polynomials useful in real-world applications?

Vector spaces of fifth-degree polynomials have various real-world applications, such as in signal processing, computer graphics, and physics. They can be used to model and analyze data, such as sound waves or physical systems, and make predictions or solve problems based on the properties of the vector space.

Back
Top