Undergrad Dense set equivalent definitions

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SUMMARY

This discussion focuses on the equivalence of two definitions of dense sets in metric spaces, specifically within the context of real analysis as presented in Rudin's "Principles of Mathematical Analysis" (POMA). The first definition states that a set E is dense in a metric space X if every point of X is a limit point of E, or E equals X, or both. The second definition asserts that E is dense if the intersection of E with every non-empty open set of X is non-empty. The participants clarify that the second definition is more accurate, particularly when considering specific examples, such as the set X consisting of points defined by the series and the number 2.

PREREQUISITES
  • Understanding of metric spaces and their properties
  • Familiarity with limit points and open sets in topology
  • Knowledge of real analysis concepts as presented in Rudin's POMA
  • Basic comprehension of set theory and intersections
NEXT STEPS
  • Study the concept of limit points in metric spaces
  • Explore the differences between various definitions of dense sets
  • Review alternative real analysis texts, such as works by George Simmons or Sterling Berberian
  • Examine the free topology book available on AMS OpenMathNotes for additional insights
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Undergraduate students studying real analysis, educators teaching metric spaces, and anyone interested in the foundational concepts of topology and analysis.

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Hello all, I am an undergraduate student who is studying real analysis from Rudin's POMA and I am trying to prove that these two definitions that I have for dense sets are equivalent:
1) Given a metric space X and E ⊂ X ; E is dense in X iff every point of X is a limit point of E or E = X or both of these are true.
2) Given a metric space X and E ⊂ X; E is dense in X iff the intersection of E and every non-empty open set of X is non-empty.
In an attempt to prove the equivalence I have encountered an example which I can't get my head around it.
Given the set X such that X consists of all points ##s_n## , where ##s_n = \sum_{k=0}^n (1/2)^n## for all n ≥ 0, and 2 as well. Now define the metric for such a set to be the same as that of ℝ. Then X is a metric space. Now according to definition (1) the only dense set in X is X itself, but according to (2) the set V = X - {2} is a dense set in X besides X as well. However we should not have such a problem. So could you please point out what I am doing wrong. Thank you.
 
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I prefer the definition, ##E## is dense, iff ##\bar{E}=X##, which is definition one.

I had difficulties to correct definition two, as it is a bit of a sloppy notation for limit points. Maybe it's better to write it with open neighborhoods ##U_x## of a point ##x## and require ##E \cap (U_x-\{x\}) \neq \emptyset##, but that's basically definition one.
 
Last edited:
fresh_42 said:
I prefer the definition, ##E## is dense, iff ##\bar{E}=X##, which is definition one.

I had difficulties to correct definition two, as it is a bit of a sloppy notation for limit points. Maybe it's better to write it with open neighborhoods ##U_x## of a point ##x## and require ##E \cap (U_x-\{x\}) \neq \emptyset##, but that's basically definition one.

You mean basically definition 2.
 
Have I confused something? I'm used to define points of a set as automatically limit points. That's why it is better to define ##E\subseteq X## is dense, if ##\bar{E} =X##, which avoids this special case. So let's see, what we get for ##E=X-\{2\}##. With my definition it is dense in ##X##.

Now if ##\{1\} \in E## is no limit point, because without ##x=1## there are no small non-empty open sets around it, then according to definition 1) ##E## wasn't dense, which is wrong.

On the other hand, in definition 2) we have ##E \cap \{1\} = \{1\}## as an intersection of ##E## with an open non-empty set which is non-empty, so the points of ##E## are included. This is correct.

So, yes, you are right, I confused the two. The second definition is right and the first one is not. Thanks for the correction.
 
This may not be of interest, since I don't know why you are using POMA, but when I hear that, my first reaction is to suggest you read a different book, like anything by George Simmons or Sterling Berberian, if you want a book tnat teaches you something in a user friendly way. Or if you stick with Rudin but have difficulty understanding at least remember it isn't necessarily your fault. I myself learned metric spaces from lectures by George Mackey and never needed to read any book on it afterwards, since they were so clear. He wrote a book on complex variables with an introductory chapter on metric spaces and elementary topology that might be useful. Also Dieudonne' has a great book on Foundations of modern analysis with a chapter on metric spaces but he is not easy reading. In my opinion your choice of book is making things harder unnecessarily, but anyway good luck. It is of course a standard and well respected by many professional analysts.
 
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