Proving M_1^2 ≤ 4M_0M_2 in Real Analysis

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SUMMARY

The discussion focuses on proving the inequality M_1^2 ≤ 4M_0M_2, where M_0, M_1, and M_2 represent the least upper bounds of |f(x)|, |f'(x)|, and |f''(x)| respectively for a twice-differentiable function f on the interval (a, ∞). The proof utilizes Taylor's Theorem, specifically the relationship between f'(x) and f(x) at distinct points, leading to the conclusion that |f'(x)| can be bounded by hM_2 + M_0/h. The key insight is to select an optimal value for h to finalize the proof.

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Homework Statement


Suppose a \in \mathbb{R}, f is a twice-differentiable real function on (a, \infinty) and M_0,M_1,M_2 are the least upper bound of |f(x)|,|f'(x)|,|f''(x)|, respectively on (a,\infinity). Prove that

M_1^2\leq 4 M_0 M_2

Homework Equations


The Attempt at a Solution


That is equivalent to showing that M_2 x^2 +M_1 x +M_0=0 has a real solution.

I was trying to use Taylor's Theorem which says that if \alpha and \beta are distinct points in (a,\infinity) then there exists x between \alpha and \beta that makes the following equation true:

f(\beta) = f(\alpha) + f'(\alpha)(\beta-\alpha) + f''(x) (\beta-\alpha)^2/2

I could take the absolute value of both sides and then use triangle inequality but I did not see how to get anywhere with that.
 
Last edited:
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Did you look at the hint given in rudin?
 
How was I supposed to know there was a hint on the next page? That is a serious question.
 
OK. The hint says:

If h>0, Taylor's theorem show that

f'(x) = \frac{1}{2h}[f(x+2h)-f(x)]-hf''(\xi)

for some \xi \in (x,x+2h). Hence

|f'(x)| \leq hM_2+M_0/h

I don't see how the last inequality is useful (even if you square it).
 
Square it and remember that it holds for ANY h > 0. There is a particular choice of h that will yield the result.
 

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