Cauchy-Schwarz Inequality Proof Question

Click For Summary
SUMMARY

The forum discussion centers on proving the Cauchy-Schwarz Inequality, which states that for any vectors \(\mathbf{x}\) and \(\mathbf{y}\) in \(\mathbb{R}^{n}\), the inequality \(|\mathbf{x} \cdot \mathbf{y}| \leq |\mathbf{x}||\mathbf{y}|\) holds. The proof involves manipulating the dot product and completing the square to demonstrate that the inequality is valid for all values of \(t\). The discussion also addresses the validity of selecting a specific \(t\) to minimize the right-hand side of the inequality, confirming that the inequality remains true for any chosen \(t\).

PREREQUISITES
  • Understanding of vector operations, specifically dot products.
  • Familiarity with the concept of inequalities in mathematics.
  • Knowledge of completing the square in algebra.
  • Basic grasp of real number properties in \(\mathbb{R}^{n}\).
NEXT STEPS
  • Study the geometric interpretation of the Cauchy-Schwarz Inequality.
  • Explore applications of the Cauchy-Schwarz Inequality in statistics and probability.
  • Learn about alternative proofs of the Cauchy-Schwarz Inequality using linear algebra.
  • Investigate related inequalities, such as the Triangle Inequality and Hölder's Inequality.
USEFUL FOR

Students of mathematics, particularly those studying linear algebra and inequalities, as well as educators looking for clear explanations of the Cauchy-Schwarz Inequality proof.

Moridin
Messages
694
Reaction score
3

Homework Statement



Prove the Cauchy-Schwarz Inequality.

Homework Equations



|\mathbf{x \cdot y}| \leq |\mathbf{x}||\mathbf{y}|, \forall \mathbf{x,y} \in \mathbb{R}^{n} (1)

The Attempt at a Solution



If x is equal to 0, then both sides are equal to 0. If x not equal to 0 the following applies. The dot product of a vector by itself is always greater or equal to 0. This means that the following holds:

\mathbf{0} \leq (t \mathbf{x} + \mathbf{y}) \cdot (t \mathbf{x} + \mathbf{y}) = t^{2} |\mathbf{x}|^{2} + 2t\mathbf{x} \cdot \mathbf{y} + |\mathbf{y}|^{2} (2)

Factoring |x|2 (which is not equal to zero) gives:

|\mathbf{x}|^{2} (t^{2} + 2 \frac{\mathbf{x} \cdot \mathbf{y}}{|\mathbf{x}|^{2}}t + \frac{|\mathbf{y}|^{2}}{|\mathbf{x}|^{2}}) (3)

Completing the square gives:

|\mathbf{x}|^{2} ( (t + \frac{\mathbf{x} \cdot \mathbf{y}}{|\mathbf{x}|^{2}})^{2} - \frac{(\mathbf{x} \cdot \mathbf{y})^{2}}{|\mathbf{x}|^{4}} + \frac{|\mathbf{y}|^{2}}{|\mathbf{x}|^{2}}) (4)

Expansion gives:

|\mathbf{x}|^{2}(t + \frac{\mathbf{x} \cdot \mathbf{y}}{|\mathbf{x}|^{2}})^2 - \frac{\mathbf{x} \cdot \mathbf{y}}{|\mathbf{x}|^{2}} + |\mathbf{y}|^{2} (5)

The parenthesis is equal to zero for an appropriate value of t, that is:

t = - \frac{\mathbf{x} \cdot \mathbf{y}}{|\mathbf{x}|^2} (6)

Then the following is true:

0 \leq |\mathbf{y}|^{2} - \frac{\mathbf{x} \cdot \mathbf{y}^{2}}{|\mathbf{x}|^{2}} (7)

Which, rearranged and the root taken of both sides, becomes:

|\mathbf{x \cdot y}| \leq |\mathbf{x}||\mathbf{y}| (8)

Analogous treatment for y. Q.E.D

My question regarding this attempt is with regards to the justification of moving from step 5 to 6 and 7. Is it valid just to pick a specific t, even though the first step does not fixate it? Or is that t that t which gives the lowest value of the RHS in the inequality, so all other t makes the RHS increase, so that if it is valid for the smallest possible RHS (which is the result of that t), then it is possible for all RHS larger (any other t)? The latter seems more intuitive, since the square cannot possible be negative, so the minimum it can get is 0?

Thank you for your time, have a nice day.
 
Last edited:
Physics news on Phys.org
It's true for all t, so what could be wrong with picking a specific t? You could have picked any other t and still gotten a valid inequality, it just wouldn't be Cauchy-Schwarz.
 
Right, since the inequality holds for all possible t, it must hold for any tn that is a possible t.

Thanks.
 

Similar threads

  • · Replies 3 ·
Replies
3
Views
2K
Replies
19
Views
3K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 2 ·
Replies
2
Views
1K
  • · Replies 1 ·
Replies
1
Views
973
  • · Replies 5 ·
Replies
5
Views
1K
  • · Replies 7 ·
Replies
7
Views
2K
  • · Replies 6 ·
Replies
6
Views
3K