Proof of the Cauchy-Schwarz Iequality .... Garling, Proposition 11.3.1 .... ....

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In summary, Peter was struggling to understand the proof of Proposition 11.3.1 in D. J. H. Garling's book A Course in Mathematical Analysis: Volume II: Metric and Topological Spaces, Functions of a Vector Variable, and needed help. Garling's proof goes as follows: \langle x, y \rangle^2 = \frac{ \langle x, y \rangle^2 }{ \mid \langle x, y \rangle \mid^2 } \frac{ \| x \|^2 }{ \| y \|^2 } \| y \|^2
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I am reading D. J. H. Garling's book: "A Course in Mathematical Analysis: Volume II: Metric and Topological Spaces, Functions of a Vector Variable" ... ...

I am focused on Chapter 11: Metric Spaces and Normed Spaces ... ...

I need some help to fully understand the proof of Proposition 11.3.1 ...

Garling's statement and proof of Proposition 11.3.1 reads as follows:View attachment 8956I need help with exactly how Garling concluded that with his substitution for \(\displaystyle \lambda\) ... we have

\(\displaystyle \lambda^2 \langle x, y \rangle = \frac{ \langle x, y \rangle^2 }{ \mid \langle x, y \rangle \mid^2 } \frac{ \| x \|^2 }{ \| y \|^2 } \| y \|^2 = \| x \|^2\) ... ... My problem is what sign (plus or minus) and value do we give to \(\displaystyle \langle x, y \rangle^2\) ... Garling seems to treat \(\displaystyle \langle x, y \rangle^2\) as if it were equal to \(\displaystyle \mid \langle x, y \rangle \mid^2\) ... and cancels with the denominator ... or so it seems ...?

But ... \(\displaystyle \langle x, y \rangle\) is a complex number, say \(\displaystyle z\) ... and so we are dealing with a complex number \(\displaystyle z^2 = \langle x, y \rangle^2\) ... and, of course, \(\displaystyle z^2\) is neither positive or negative ... ... ? ... so how do we end up with

\(\displaystyle \lambda^2 \langle x, y \rangle = \| x \|^2\)Hope that someone can help ...

Peter=========================================================================================It may help readers of the above post to have access to Garling's introduction to inner product spaces where he gives the relevant definitions and notation ... so I am providing access to the relevant text as follows:
View attachment 8957
View attachment 8958
Hope that helps ...

Peter
 

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  • Garling - 1 - Start of Secton 11.3 on Inner Product Spaces ... .PAGE 1 .png
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Peter said:
My problem is what sign (plus or minus) and value do we give to \(\displaystyle \langle x, y \rangle^2\) .
In fact, \(\displaystyle \langle x, y \rangle^2\) does not occur anywhere in Garling's proof. The proof contains the terms $\overline{\lambda}\langle x, y \rangle$ and $\lambda\langle y, x \rangle$. In each of those cases, $\langle x, y \rangle$ gets multiplied by its complex conjugate $\langle y,x \rangle$, so that the product is equal to $|\langle x, y \rangle|^2$.
 
  • #3
Opalg said:
In fact, \(\displaystyle \langle x, y \rangle^2\) does not occur anywhere in Garling's proof. The proof contains the terms $\overline{\lambda}\langle x, y \rangle$ and $\lambda\langle y, x \rangle$. In each of those cases, $\langle x, y \rangle$ gets multiplied by its complex conjugate $\langle y,x \rangle$, so that the product is equal to $|\langle x, y \rangle|^2$.
Hmmm ... yes ... you're right of course...

I should have been more careful when I was writing out the details of the proof ...

Thanks for the help ...

Peter
 

1. What is the Cauchy-Schwarz inequality?

The Cauchy-Schwarz inequality is a mathematical inequality that states that the dot product of two vectors is always less than or equal to the product of their magnitudes. In other words, it shows that the magnitude of the dot product of two vectors is always less than or equal to the product of their individual magnitudes.

2. How is the Cauchy-Schwarz inequality used in mathematics?

The Cauchy-Schwarz inequality is used in various areas of mathematics, such as linear algebra, analysis, and probability theory. It is a fundamental inequality that is often used in proofs and to derive other important mathematical results.

3. What is Proposition 11.3.1 in Garling's book?

Proposition 11.3.1 in Garling's book is a specific application of the Cauchy-Schwarz inequality. It states that for any two sequences of real numbers, the sum of the squares of their terms is always less than or equal to the product of the sums of their squares.

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

Yes, the Cauchy-Schwarz inequality can be extended to any number of vectors. This is known as the generalized Cauchy-Schwarz inequality and is often used in higher-level mathematics.

5. What are some real-world applications of the Cauchy-Schwarz inequality?

The Cauchy-Schwarz inequality has many applications in real-world problems, such as in physics, engineering, and economics. It is used to optimize functions, analyze data, and solve optimization problems. It is also used in machine learning and computer science algorithms.

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