When is the Cauchy-Schwartz inequality an equality?

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In summary, if the vectors a and b are parallel, given by the equation a = \lambda b, then the Cauchy-Schwartz inequality |\braket{a}{b}|^2 \leq \braket{a}{a} \braket{b}{b} is an equality. This can be shown by expressing b as the sum of its projection onto the subspace generated by a (Pb) and a vector perpendicular to a (Qb). From there, it can be shown that if a and b are parallel, Qb must equal 0, making the inequality an equality. Additionally, it can be shown that if the inequality is an equality, then Qb must equal 0, proving
  • #1
Logarythmic
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I can show that if the vectors a and b are parallel,

[tex]a = \lambda b[/tex],

then the Cauchy-Schwartz inequality

[tex]
\newcommand{\braket}[2]{{<\!\!{#1|#2}\!\!>}}
|\braket{a}{b}|^2 \leq \braket{a}{a} \braket{b}{b}
[/tex]

is an equality.

But how do I show that it is an equality if and only if they are parallel?
 
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  • #2
You can write b=Pb+Qb, where Pb is the projection of b onto the subspace generated by a, ie, Pb is parellel to a, and Qb is perpendicular to a. Then a=lambda*b iff Qb=0. Plug the expansion of b into the inequality.
 
  • #3
Sorry, I don't get it. Can you give me more details?
 
  • #4
Do you know how to project one vector on another?
 
  • #5
In this case,

[tex]\hat{b} = \frac{b \cdot a}{a \cdot a} a[/tex]

right?
 
  • #6
Right, and b is equal to its projection onto a iff a and b are parellel. See if you can express (a,b) in terms of the projection of b onto a.
 
  • #7
Like

[tex]\hat{b} = \frac{b \cdot a}{a \cdot a} a = \lambda \frac{a \cdot a}{a \cdot a} a = \lambda a[/tex]

?
 
  • #8
That shows that b equals its projection if b=la, but not the converse.
 
  • #9
Then I'm stuck...
 
  • #10
Never mind, the converse is trivial. Ok, so you've shown that b is a multiple of a iff Qb=b-Pb=0, where Pb is the projection of b onto a. Now plug b=Pb+Qb into (a,b).
 
  • #11
I don't get it. If b = Pb, then

[tex]|<b|a>|^2 = <a|b> <b|a> = <a|Pb><Pb|a>[/tex]

and I want to show that this equals

[tex]<a|a><b|b>[/tex]

??
 
  • #12
Just in case you want to try a different path (because it may be easier):
If a and b are linearly independent, then [tex]a-\lambda b\not= 0[/tex] for all [itex]\lambda \in \mathbb{R}[/tex]. Now what you can you say about the inner product of [itex]a-\lambda b[/itex] with itself?
 
  • #13
I don't know, what can I say?

[tex]<a - \lambda b|a - \lambda b> = <a|a> - \lambda <a|b> - \lambda <b|a> + \lambda^2 <b|b>[/tex]

?
 
  • #14
That's a polynomial in lambda that has no real solutions. Look at the determinant.

Galileo's way is probably easier (and nicer, as it doesn't require a projection operator), but all I wanted you to do was plug in |<a,b>|^2=|<a,Pb+Qb>|^2=|<a,Pb>+<a,Qb>|^2=..., and you'll eventually end up with something like |<a,b>|^2+c||Qb||^2=||a||^2||b||^2, so that equality holds iff Qb is zero.
 
Last edited:
  • #15
Logarythmic said:
I don't know, what can I say?

[tex]<a - \lambda b|a - \lambda b> = <a|a> - \lambda <a|b> - \lambda <b|a> + \lambda^2 <b|b>[/tex]

?
True. Now, if v is a nonzero vector, what does that say about <v,v>?
(You have a vector v=a-Lb that is nonzero for EVERY L.)

Then look at your equation as a quadratic equation in L.
 
  • #16
So <v|v> is constant and I get an expression for [tex]\lambda[/tex]? My head is pretty messed up after this thread.
 
  • #17
No, <v,v> is not constant wrt lambda. It's a quadratic equation in terms of lambda, as you have shown.

The inner product has the property that:
[tex]\langle v,v \rangle \geq 0 \mbox{ with equality only if v=0}[/tex]

Since your v is not zero it is positive for any value of lambda. That means you have a quadratic equation which has no real roots. What does that tell you about its determinant?
 

1. What is the Cauchy-Schwartz inequality?

The Cauchy-Schwartz inequality, also known as the Cauchy-Bunyakovsky-Schwartz inequality, is a mathematical inequality that relates the inner product of two vectors to the norms (lengths) of the vectors. It states that the absolute value of the inner product of two vectors is less than or equal to the product of their norms. In other words, the length of the projection of one vector onto another is always less than or equal to the length of the two vectors multiplied together.

2. Why is the Cauchy-Schwartz inequality important?

The Cauchy-Schwartz inequality is important because it has many applications in mathematics and other fields such as physics, engineering, and statistics. It is also a fundamental inequality that is used to prove other important theorems and inequalities in mathematics.

3. How is the Cauchy-Schwartz inequality used in linear algebra?

In linear algebra, the Cauchy-Schwartz inequality is used to define the concept of an inner product, which is a generalization of the dot product in Euclidean space. It is also used to prove important theorems such as the Cauchy-Schwartz inequality for matrices and the triangle inequality for norms.

4. Can the Cauchy-Schwartz inequality be extended to more than two vectors?

Yes, the Cauchy-Schwartz inequality can be extended to any finite number of vectors. This is known as the generalized Cauchy-Schwartz inequality and it states that the sum of the products of the norms of any two vectors is less than or equal to the product of the norms of all the vectors.

5. Are there any variations of the Cauchy-Schwartz inequality?

Yes, there are several variations of the Cauchy-Schwartz inequality that involve different types of norms and inner products. Some examples include the Minkowski's inequality, Hölder's inequality, and the Cauchy-Schwartz-Poincaré inequality. These variations have important applications in different areas of mathematics and beyond.

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