Why must inner product spaces be over the field of real or complex numbers?

In summary, Friedberg's Linear Algebra states that an inner product space must be over the field of real or complex numbers, but this is not always the case. There are other structures that can be used for an inner product, but they are not as interesting or nice as working with real or complex numbers. The concept of normalization is very important and is used in many different areas of mathematics.
  • #1
cavalier
29
0
Friedberg's Linear Algebra states in one of the exercises that an inner product space must be over the field of real or complex numbers. After looking at the definition for while, I am still having trouble seeing why this must be so. The definition of a inner product space is given as follows.

Let V be a vector space over F. An inner product on V is a function that assigns, to every ordered pair of vectors x and y in V, a scalar in F, denoted <x,y>, such that for all x, y, and z in V and all c in F, the following hold:
(a) <x+z, y>=<x,y> + <z,y>
(b) <cx,y>=c<x,y>
(c) <x,y>=[itex]\overline{<y,x>}[/itex]
(d) <x,x> > 0 if x[itex]\neq[/itex]0.

I can't convince myself that I could not contrive some vector space and some inner product such that the resulting inner product space would not use the whole number line.
 
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  • #2
The short answer is that it must not be over the field of real or complex numbers. It can be defined over more general structures as well (for example, over [itex]C^*[/itex]-algebras). This yields the notion of [itex]C^*[/itex]-modules

However, there are at least two reasons why we limit ourself to real or complex numbers:
1) The theory is nicer and easier of reals or complex numbers. For example, the theorem of Pythagoras mustn't hold in the more general case.

2) All the applications occur when working over the real or complex numbers. So looking at others structures is just not as interesting.
 
  • #3
fields have multplicative inverses and in this way for instance you can normalize your vectors. If the norm of your vector is |v| which is in your field then it has an inverse 1/|v|. So v/|v| exists and you get a normalized vector. So the inner product comes into the role by the fact that it gives the norm of your vectors as a value in your field.

The concept of normalization is of outmost importance in many applied areas first and mostly quantum mechanics. Existance of othonormal bases is also of great use.
 
  • #4
cavalier said:
Friedberg's Linear Algebra states in one of the exercises that an inner product space must be over the field of real or complex numbers. After looking at the definition for while, I am still having trouble seeing why this must be so. The definition of a inner product space is given as follows.

Let V be a vector space over F. An inner product on V is a function that assigns, to every ordered pair of vectors x and y in V, a scalar in F, denoted <x,y>, such that for all x, y, and z in V and all c in F, the following hold:
(a) <x+z, y>=<x,y> + <z,y>
(b) <cx,y>=c<x,y>
(c) <x,y>=[itex]\overline{<y,x>}[/itex]
(d) <x,x> > 0 if x[itex]\neq[/itex]0.

I can't convince myself that I could not contrive some vector space and some inner product such that the resulting inner product space would not use the whole number line.

You can definitely do this. But inner products are generally used to define angles and lengths. For this some concept of a continuum is natural.

However symmetric bilinear forms appear all over in mathematics and in the scalars do not even have to be in a field.
 
  • #5
the positive-definite property of an inner product only makes sense over fields of characteristic 0. conjugate-symmetry only makes sense for fields that possesses an automorphism that fixes an ordered subfield, that is also an involution.

this limits the possible choices for our underlying field. more choices than R and C are indeed possible, but not commonly used (one of the reasons C is so popular is that C is algebraically complete, so for a linear transformation of a complex vector space, we are guaranteed eigenvalues).
 

1. Why can't inner product spaces be over other fields, such as integers or rational numbers?

Inner product spaces require a notion of distance and angle, which can only be defined using real or complex numbers. Other fields, such as integers or rational numbers, do not have the necessary properties to define these concepts.

2. What makes the real or complex numbers special for inner product spaces?

The real and complex numbers have specific algebraic and geometric properties that make them suitable for defining distance and angle in inner product spaces. These properties include closure, associativity, commutativity, and the existence of inverses.

3. Can't other fields be extended to include these properties and be used for inner product spaces?

While other fields can be extended, they would no longer be the original field and would not have the same properties. Furthermore, the real and complex numbers have been extensively studied and have a wide range of applications in mathematics and science, making them the most suitable choice for inner product spaces.

4. Are there any practical reasons for using real or complex numbers for inner product spaces?

Yes, using real or complex numbers for inner product spaces allows for efficient and accurate calculations, as these numbers have well-defined operations and properties. It also allows for the use of geometric interpretations and visualizations, making it easier to understand and apply concepts in inner product spaces.

5. Can inner product spaces be defined over other fields for specific applications?

Yes, for certain specialized applications, it may be useful to define inner product spaces over other fields. However, the majority of applications and research in mathematics and science use real or complex inner product spaces due to their broad applicability and well-defined properties.

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