Inner Product Space, quick questions.

In summary, the conversation discusses the use of the identity ||u+v||^2=||u||^2+||v||^2+(u,v)+(v,u) and how it can be derived using the hermiticity property. The conversation also touches on finding an orthonormal basis for the orthogonal complement of a subspace and the use of complex inner product in calculations.
  • #1
binbagsss
1,317
11
1) Using the indentity:||u+v||^2=||u||^2+||v||^2+(u,v)+(v,u) - where (x,y) denotes the inner product .
Now if we let the second term = iv, my book gives the identity as then:
||u+iv||^2=||u||^2+||v||^2-i(u,v)+i(v,u) [1].

And I am struggling to derive this myself, here is my working:
||u+iv||^2=(u,u)+(u,iv)+(iv,u)+(iv,iv)
= ||u||^2+(u,iv)+i(v,u)+||iv||^2
Now the two terms I am struggling with are why ||iv||^2=||v||^2 and trying to get the (u,iv) to -i(u,v) as it is in [1].
My attempt was to use the hermiticity property to give (u,iv)=(iv,u)* - letting * denote the complex conugate - gives (u,iv)=(-iv,u)=-i(v,u), where the last equivalence follws from linearity in the first factor, rather than -i(u,v).

2) Is to find an orthornomal basis for the orthogonal complement of the subspace spanned by (2,1-i,0,1) and (1,0,i,3), under the standard inner product. Now I am ok with the main concepts of the strategy needed here: the orthogonal complement of the subspace is given by the space of solutions to
2a+(1-i)b+d=0 and,
a+ic+3d=0,
obtained by ensuring that any arbitarty vector that lies in this space (a,b,c,d) is orthogonal to the spanning vectors given of the subspace.
HOWEVER, my book gives these equations (1) and (2) as 2a+(1+i)b+d=0 and a-i+3d=0, and I can not see why the 'i's have been multipled by -1 compared to my workng.

Many Thanks for any assistance.
 
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  • #2
well, effectively, the idea is to find the components of a vector which gives zero inner product with the vectors that you have been given, right? So what is the proper way to do an inner product?
 
  • #3
Ahh thanks , the complex inner product of x and y = (x,y*), where y* is the complex conjugate . so letting a=(2,1-i,0,1) and b=(1,0,i,3) and z=(a,b,c,d) for a,b,c,d in ℝ, I can see where this comes from taking the inner products: (z,a*) and (z,b*), however not if I take the other order of these, i.e. (a*,z) and (b*,z) as z*=(a,b,c,d).
 
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  • #4
Well, you've got (a*,z)=0 or (z*,a)=0 Do these two statements disagree with each other?
 
  • #5
Sorry, the post above should read the other order as (a,z*) or (b,z*).
(z,a*) gives me the equation in line witht the equation: 2a+b(1+i)+d=0, and (a,z*) gives 2a+b(1-i)+d=0, which as far as I can see are not equivalent?
 
  • #6
well, you need to do a proper calculation to see if they are equivalent. The two equations are:
(z,a*) = 0 and (a,z*) = 0
Is there a way to re-write one equation, as the other equation?
 
  • #7
Ahh I see, thanks, by hermiticity the two are equivalent.
 
  • #8
yep, no worries, man
 

FAQ: Inner Product Space, quick questions.

What is an inner product space?

An inner product space is a vector space equipped with an operation called an inner product, which is a way of multiplying two vectors together to get a scalar. This operation also satisfies certain properties, such as linearity and symmetry.

What are the properties of an inner product?

The properties of an inner product include linearity, symmetry, and positive definiteness. Linearity means that the inner product of a vector with the sum of two other vectors is equal to the sum of the inner products of that vector with each individual vector. Symmetry means that the inner product of two vectors is the same regardless of the order in which they are multiplied. Positive definiteness means that the inner product of a vector with itself is always positive, unless the vector is the zero vector.

How is the inner product different from the dot product?

The inner product and dot product are similar in that they both take two vectors and return a scalar. However, the inner product is defined for any vector space, while the dot product is only defined for Euclidean spaces. Additionally, the inner product has more properties, such as linearity and symmetry, while the dot product only has the property of distributivity.

Can an inner product space have an infinite number of dimensions?

Yes, an inner product space can have an infinite number of dimensions. In fact, most commonly studied inner product spaces, such as the space of real or complex valued functions, are infinite dimensional. The inner product is still defined in the same way, but the vectors may have an infinite number of components.

What is the geometric interpretation of the inner product?

The inner product has a geometric interpretation as the length of the projection of one vector onto another vector. This means that the inner product can be used to measure the angle between two vectors, as well as their orthogonality. It also allows us to define concepts such as distance and orthogonality in more general vector spaces, not just in Euclidean spaces.

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