Proof of Cauchy-Schwarz Inequality

In summary, the Cauchy-Schwarz inequality is a mathematical inequality that states the dot product of two vectors is less than or equal to the product of their magnitudes. It has many applications in mathematics, physics, and engineering and can be proved using various methods. It can also be extended to higher dimensions and is used in real-world problems such as data analysis, optimization, and algorithm convergence.
  • #1
Vespero
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0

Homework Statement



Let V be a vector space with inner product <x,y> and norm ||x|| = <x,x>^1/2.
Prove the Cauchy-Schwarz inequality <x,y> <= ||x|| ||y||.

Hint given in book: If x,y != 0, set c = 1/||x|| and d = 1/||y|| and use the fact that
||cx ± dy|| >= 0.

Here, the inner product is not necessarily the dot product, nor the norm the Euclidean norm. All that is necessary is that the two fulfill properties of inner products and norms.

For inner products, the given properties are
1. <x,y> = <y,x>
2. <x + y, z> = <x,y> + <x,z>
3. <cx,y> = c<x,y> = <x,cy>
4. <x,x> > 0 if x != 0.

For norms, the given properties are
1. ||x|| > 0 if x != 0
2. ||cx|| = |c|||x||
3. ||x + y|| <= ||x|| + ||y||

Homework Equations



The inequality ||cx ± dy|| >= 0 is given as true.

The Attempt at a Solution



I have attempted to solve the problem by starting with the Cauchy-Schwarz inequality and working towards the inequality given in the hint as true:

<x,y> >= ||x|| ||y||
-2<x,y> >= -2||x|| ||y||
-2cd<x,y> >= -2
1 - 2cd<x,y> + 1 >= 0
(c^2)||x||^2 - 2cd<x,y> + (d^2)||d||^2 >= 0
(c^2)<x,x> -cd<x,y> - cd<y,x> + (d^2)<y,y> >= 0
<cx,cx> + <cx, -dy> + <-dy, cx> + <dy,dy> >= 0
<cx - dy, cx - dy> >= 0
||cx - dy||^2 >= 0

Taking the square root here yields
||cx - dy|| >= 0 or ||cx - dy|| <= 0

but the norm of a vector is a non-negative number, so the right inequality simplifies to
||cx - dy|| = 0
The two inequalities can then be combined to yield
||cx - dy|| >= 0, which was given as a fact at the beginning of the problem.

Do you see any flaws in my logic, or any steps that could be simplified or added to make the proof more clear?
 
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  • #2
The path is essentially correct, but it really should go the other way around. Going from inequality to something obvious is good for devising the proof, but it's kind of "backward logic". Rewriting the steps in the opposite we can get nice chain of logical consequences.
That's just my point of view. But maybe I care about such things too much.
 
  • #3
losiu99 said:
The path is essentially correct, but it really should go the other way around. Going from inequality to something obvious is good for devising the proof, but it's kind of "backward logic". Rewriting the steps in the opposite we can get nice chain of logical consequences.
That's just my point of view. But maybe I care about such things too much.

Thanks for the reply, losiu. I actually began the proof the other way around, but ran into trouble, but I think I understand why. The hint say to use the fact that ||cx ± dy|| >= 0. The ± sign was throwing me off, as when I reached the end of the proof, I had something like
±<x,y> >= -||x|| ||y||.
The minus sign yields the Cauchy-Schwarz inequality, but the plus sign yields
<x,y> >= -||x|| ||y||
and I'm not sure what to do about it.

Is there a way to resolve this problem? Should the ± still be present by the end of the problem, or is there a way to get rid of it? Should I just take the case ||cx - dy|| >= 0,
which eventually directly yields the Cauchy-Schwarz, with no sign problem?
 
  • #4
The "minus" version is, as you noticed, sufficient for the proof. To be honest, I have no idea why ± is present in the hint. Just take the || cx - dy ||, factor everything and that's it.
 

Related to Proof of Cauchy-Schwarz Inequality

1. What is the Cauchy-Schwarz inequality?

The Cauchy-Schwarz inequality, also known as the Cauchy-Bunyakovsky-Schwarz inequality, is a mathematical inequality that states that the dot product (or inner product) of two vectors is less than or equal to the product of their magnitudes. It is one of the most important and widely used inequalities in mathematics.

2. What is the significance of the Cauchy-Schwarz inequality?

The Cauchy-Schwarz inequality has many applications in mathematics, physics, and engineering. It is used to prove other important theorems and inequalities, and it is also useful in optimization problems and in proving convergence of series and integrals.

3. How is the Cauchy-Schwarz inequality proved?

The Cauchy-Schwarz inequality can be proved using various methods, including geometric proofs, algebraic proofs, and proofs using the Cauchy-Schwarz inequality itself. One common proof method is to use the Cauchy-Schwarz inequality to prove the more general Hölder's inequality, and then use Hölder's inequality to prove the Cauchy-Schwarz inequality.

4. Can the Cauchy-Schwarz inequality be extended to higher dimensions?

Yes, the Cauchy-Schwarz inequality can be extended to higher dimensions. In fact, the inequality holds for any number of vectors in an inner product space. The generalization of the Cauchy-Schwarz inequality to multiple vectors is known as the Cauchy-Schwarz-Minkowski inequality.

5. How is the Cauchy-Schwarz inequality used in real-world problems?

The Cauchy-Schwarz inequality has many practical applications in areas such as statistics, economics, and computer science. It is used in data analysis and regression, optimization problems, and in proving the convergence of algorithms. In economics, it is used to prove the existence of solutions to certain optimization problems, and in computer science it is used in algorithms for data compression and pattern matching.

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