Rudin 1.37 (d) is trivial to Rudin but hell for me

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Discussion Overview

The discussion revolves around the proof of the inequality $$|x \cdot y| \leqslant |x||y|$$ as presented in Theorem 1.37, part (d) of Rudin's Principles of Mathematical Analysis. Participants are exploring the connection between this inequality and the Cauchy-Schwarz Inequality, particularly addressing the steps involved in the proof and the notation used.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant expresses confusion about how the inequality $$|x \cdot y| \leqslant |x||y|$$ follows from the Cauchy-Schwarz Inequality, suggesting that their manipulation does not yield the expected result.
  • Another participant suggests that the difference in notation, specifically the use of conjugates, is merely a matter of making the formula compatible with complex spaces.
  • A participant clarifies that the right side of the inequality should involve $$|x_i|$$ instead of $$|x|$$, emphasizing that the absolute value notation is necessary for compatibility with complex numbers.

Areas of Agreement / Disagreement

Participants appear to have differing levels of understanding regarding the application of the Cauchy-Schwarz Inequality and the notation involved. There is no clear consensus on the steps leading to the proof, indicating that the discussion remains unresolved.

Contextual Notes

There are uncertainties regarding the manipulation of the inequality and the interpretation of the notation, particularly in the context of complex versus real numbers. Participants have not fully resolved these issues.

josueortega
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Hi everyone,

I am working on my own through Rudin's Principles of Mathematical Analysis and, after the demonstration of Cauchy - Schwarz Inequality, in Theorem 1.37, part (d), Rudin states:

$$|x \cdot y| \leqslant |x||y|$$

When he explains how to prove this, he simply states that this is an immediate consequence of Schwarz Inequality, which he defines as follows:

$$|\sum_{j=1}^{n}a_j \overline{b_j}|^2 \leqslant \sum_{j=1}^{n}|a_j|^2 \sum_{j=1}^{n}|b_j|^2$$

If someone can explain me how this two things are identical I would appreciate it a lot. My toughts so far:

$$|x \cdot y| \leqslant |x||y|$$ Take the square of this, which is:

$$ (x \cdot y)(x \cdot y) \leqslant \sum x_i^2 \sum y_i^2$$ and hence,

$$ (\sum x_iy_i)^2 \leqslant \sum x_i^2 \sum y_i^2$$ which is NOT the Schwarz Inequality!
 
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Sure it is? He just conjugates the [itex]b_j[/itex] to make the formula compatible with complex spaces. It's the same reason he slaps absolute value bars everywhere.
 
I understand the part of the conjugate, actually the whole part on the left is pretty clear to me. The problem is the right side of the inequality. I don't understand how

$$\sum x_i^2 \sum y_i^2 = \sum_{j=1}^{n} |x|^2 \sum_{j=1}^{n} |y|^2$$
 
You mean [itex]|x_i|[/itex] on the right, not [itex]|x|[/itex], right? Again, it's just slapping absolute value bars around to make the inequality compatible with complex spaces. For real numbers, there is no difference.
 

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