MHB Delta Epsilon Proof: An Overview

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The discussion provides a detailed explanation of the Delta Epsilon proof for the limit of the function f(x) = 1/x^2 as x approaches infinity, demonstrating that this limit equals 0. It establishes that for any ε > 0, there exists an N such that if x > N, then |f(x) - L| < ε, where L is the limit. The proof outlines the steps to find a suitable N, specifically N = 1/√ε, ensuring that for x greater than this value, the condition |1/x^2 - 0| < ε holds true. The approach emphasizes the importance of correctly applying the definitions of limits in calculus. This methodical breakdown clarifies the often confusing aspects of Delta Epsilon proofs.
karush
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these proofs are always confusing but here's my take on it..

since $x\rightarrow +\infty$ we don't need absolute values and since
$
\displaystyle
\frac{1}{10^2}=0.01
$
then we could use $N=10$ letting $L=0$ since it is a horz asymptote then we have

$
\displaystyle
\left[\frac{1}{x^2}-0\right]<0.01
$
by observation if $x>10$ this would be true.
also, if $\delta$ is the distance between $N$ and $x$

sure this isn't the full story.
 
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To prove that $\displaystyle \begin{align*} \lim_{x \to \infty} f(x) = L \end{align*}$, you have to show that for all $\displaystyle \begin{align*} \epsilon > 0 \end{align*}$ there exists an N such that $\displaystyle \begin{align*} x > N \implies \left| f(x) - L \right| < \epsilon \end{align*}$.

So in your case, to show $\displaystyle \begin{align*} \lim_{x \to \infty} \frac{1}{x^2} = 0 \end{align*}$, you need to show that $\displaystyle \begin{align*} x > N \implies \left| \frac{1}{x^2} - 0 \right| < \epsilon \end{align*}$.

So the scratch work to find a suitable N:

$\displaystyle \begin{align*} \left| \frac{1}{x^2} - 0 \right| &< \epsilon \\ \left| \frac{1}{x^2} \right| &< \epsilon \\ \frac{1}{x^2} &< \epsilon \\ 1 &< \epsilon \, x^2 \\ \frac{1}{\epsilon} &< x^2 \\ x^2 &> \frac{1}{\epsilon} \\ |x| &> \frac{1}{\sqrt{\epsilon}} \end{align*}$

and since we want $\displaystyle \begin{align*} x \to \infty \end{align*}$ we can assume x is some big positive number, giving $\displaystyle \begin{align*} x > \frac{1}{\sqrt{\epsilon}} \end{align*}$. So that means we can set $\displaystyle \begin{align*} N = \frac{1}{\sqrt{\epsilon}} \end{align*}$.

The actual proof will be to start with setting $\displaystyle \begin{align*} N = \frac{1}{\sqrt{\epsilon}} \end{align*}$ and using that to show that if $\displaystyle \begin{align*} x > \frac{1}{\sqrt{\epsilon}} \end{align*}$ then $\displaystyle \begin{align*} \frac{1}{x^2} < \epsilon \end{align*}$ (which should be pretty easy considering that every step in the scratch work is reversible)...
 
There are probably loads of proofs of this online, but I do not want to cheat. Here is my attempt: Convexity says that $$f(\lambda a + (1-\lambda)b) \leq \lambda f(a) + (1-\lambda) f(b)$$ $$f(b + \lambda(a-b)) \leq f(b) + \lambda (f(a) - f(b))$$ We know from the intermediate value theorem that there exists a ##c \in (b,a)## such that $$\frac{f(a) - f(b)}{a-b} = f'(c).$$ Hence $$f(b + \lambda(a-b)) \leq f(b) + \lambda (a - b) f'(c))$$ $$\frac{f(b + \lambda(a-b)) - f(b)}{\lambda(a-b)}...

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