Is ##\delta##-steady needed in this proof, given ##\epsilon##-steady

In summary, Tao's Analysis 1, Lemma 5.3.6 states that a sequence is not only epsilon-steady for all positive epsilon values, but also epsilon/2-steady. The question is raised as to why the statement on delta is necessary when it can be obtained from the statement on epsilon. It is suggested that the author may have used delta to distance epsilon and reframe the definition in terms of delta in order to show that epsilon/2 also fulfills the condition.
  • #1
yucheng
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TL;DR Summary
Is ##\delta##-steady needed in this proof, given ##\epsilon##-steady for all ##\epsilon>0##?
In Tao's Analysis 1, Lemma 5.3.6, he claims that "We know that ##(a_n)_{n=1}^{\infty}## is eventually ##\delta##-steady for everyvalue of ##\delta>0##. This implies that it is not only ##\epsilon##-steady, ##\forall\epsilon>0##, but also ##\epsilon/ 2##-steady."

My question is, why do we need the statement on ##\delta## when we already have ##\epsilon##-steady, ##\forall\epsilon>0##, which immediately follows that the sequence is ##\epsilon /2##-steady since ##\epsilon>0 \implies \epsilon /2>0##? Is this just his style, or is it logically necessary?
 
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  • #2
yucheng said:
when we already have ##\epsilon##-steady
Don't you get that from ##\delta##? I don't have the book so maybe the context is relevant, but you need to start with some knowledge to conclude anything.
 
  • #3
mfb said:
Don't you get that from ##\delta##? I don't have the book so maybe the context is relevant, but you need to start with some knowledge to conclude anything.
Clarification: the 'knowledge' is ##\forall\epsilon>0##... For whatever reason, the author used ##\delta>0##... in the proof instead, then only brought ##\epsilon## in later.

Is it to distance the ##\epsilon##, I mean the definition for a Cauchy sequence already uses ##\epsilon##, so if I want to say ##\epsilon /2## fulfils the condition, I can reframe the definition in terms of ##\delta >0##, then point out that ##\epsilon >0## also fulfils the condition, i.e. (##\epsilon\in \{x:x = \delta\}##) it, then ##\epsilon /2>0## also fulfils it, i.e. ##\exists\epsilon /2: \epsilon /2\in \{x:x = \epsilon\} \subset \{x:x = \delta\}##?

I apologize if I am abusing, if not misusing notation!
 

1. What does it mean for a proof to be ##\delta##-steady?

A proof is said to be ##\delta##-steady if it is valid for all values of ##\delta##. This means that the proof holds true regardless of how small or large ##\delta## is.

2. Why is ##\delta##-steady needed in a proof?

##\delta##-steady is needed in a proof to ensure that the result holds true for all possible values of ##\delta##. This helps to strengthen the validity and reliability of the proof.

3. How is ##\delta##-steady related to ##\epsilon##-steady?

##\delta##-steady and ##\epsilon##-steady are closely related concepts in mathematical proofs. ##\delta##-steady refers to the range of values for which the proof is valid, while ##\epsilon##-steady refers to the precision or accuracy of the result. Both are important in ensuring the overall validity of the proof.

4. Can a proof be ##\epsilon##-steady without being ##\delta##-steady?

No, a proof cannot be ##\epsilon##-steady without being ##\delta##-steady. In order for a proof to be ##\epsilon##-steady, it must also be valid for all values of ##\delta##. Otherwise, there may be cases where the proof is not accurate or precise enough to be considered valid.

5. How can one determine if a proof is ##\delta##-steady?

To determine if a proof is ##\delta##-steady, one must carefully examine the assumptions and steps taken in the proof. It is important to consider the range of values for which the proof is valid and whether there are any potential limitations or exceptions. Additionally, seeking feedback from other experts in the field can also help to determine the ##\delta##-steadiness of a proof.

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