Is V a Vector Space over the Field of Real Numbers?

In summary, the conversation discusses the process of showing that the set of complex-valued functions on the real line, with the operations of vector addition and scalar multiplication, is a vector space over the field of real numbers. The concept of complex conjugation and the properties of a vector space are discussed, including the need to show that vector addition is closed within the vector space.
  • #1
gotmilk04
45
0

Homework Statement


Let V be the set of all complex-valued functions, f, on the real line such that
f(-t)= f(t) with a bar over it, which denotes complex conjugation.
Show that V, with the operations
(f+g)(t)= f(t)+g(t)
(cf)(t)=cf(t)
is a vector space over the field of real numbers.

Homework Equations





The Attempt at a Solution


I don't know what complex conjugation means, so I have no idea where to start with this.
 
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  • #2
Let [itex]x,y=\in\mathbb{R}[/itex]. Then [itex]z=x+iy\in\mathbb{C}[/itex]. The complex conjugate of [itex]z[/itex] is [itex]\overline{z}=x-iy[/itex].

So you have a function [itex]f:\mathbb{R}\rightarrow\mathbb{C}[/itex] such that [itex]f(-t)=\overline{f(t)}[/itex]. You can rewrite [itex]f(t)[/itex] as [itex]f(t)=u(t)+iv(t)[/itex], where [itex]u,v[/itex] are real valued functions of a real variable [itex]t[/itex].

Chew on that and see if you don't know how to start.
 
  • #3
I'm still not sure what to do. I have to show all the properties of a vector space, right?
But I'm not sure how to write it out and everything.
Like, for vector addition, do I add another fuction g(t)=x(t)+iy(t) where x,y are real valued and then add f(t)+g(t) and show it equals g(t)+f(t)?
 
  • #4
Yes, you have to show that all the properties of a vector space hold. That f(t)+g(t)=g(t)+f(t) is obvious because the functions are complex valued. The real heart of the matter (as far as vector addition goes) is showing that f(t)+g(t) is even IN the vector space. That is, you have to show that (f+g)(-t)=(f+g)(t)-bar (sorry, Latex isn't working).
 

1. What is a vector space in linear algebra?

A vector space is a mathematical structure that consists of a set of vectors, along with operations of addition and scalar multiplication. These operations follow certain rules, such as closure, associativity, and distributivity, and the set must contain a zero vector and each vector must have an additive inverse. Vector spaces are used to model real-world phenomena and are an important concept in linear algebra.

2. What are the key properties of a vector space?

The key properties of a vector space include closure, associativity, commutativity, distributivity, existence of a zero vector, and existence of additive inverses. Closure means that the result of adding or multiplying two vectors in a vector space is also a vector in that same space. Associativity means that the order in which operations are performed does not affect the result. Commutativity means that the order in which vectors are added or multiplied does not affect the result. Distributivity means that scalar multiplication distributes over vector addition. The existence of a zero vector and additive inverses ensures that every vector can be added to or subtracted from another vector in the space.

3. What is the difference between a vector and a scalar?

A vector is a mathematical object that has both magnitude and direction, and can be represented geometrically as an arrow. It is often used to represent quantities such as velocity, force, or displacement. A scalar, on the other hand, is a mathematical object that has only magnitude and no direction. It is represented by a single number and is used to represent quantities such as mass, temperature, or time. In linear algebra, vectors are elements of a vector space, while scalars are used to scale the vectors in the space.

4. How do you determine if a set of vectors forms a vector space?

To determine if a set of vectors forms a vector space, you must check if the set satisfies all the properties of a vector space. These properties include closure, associativity, commutativity, distributivity, existence of a zero vector, and existence of additive inverses. If all of these properties are satisfied, then the set of vectors forms a vector space. If any of the properties are not satisfied, then the set does not form a vector space.

5. What is the importance of vector spaces in linear algebra?

Vector spaces are important in linear algebra because they provide a framework for understanding and solving many mathematical problems. They are used to model real-world phenomena and are essential in areas such as physics, engineering, and computer science. Vector spaces also provide a foundation for other important concepts in linear algebra, such as linear transformations, eigenvalues and eigenvectors, and matrix operations.

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