Is Pugh's Use of Geometry in Proving Uncountability Rigorous?

  • Thread starter Gyroid
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In summary, Pugh proves the uncountability of a closed interval of real numbers using a geometric construction which pairs each point on the line segment [a,b] with a point on a unit circle which is then paired with a unique point on the real number line. However, the proof relies on the fact that the real numbers are complete, and this may not be obvious to some.
  • #1
Gyroid
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Hi PFers,

What I'm referring to is on p. 32 of Pugh's Real Mathematical Analysis. (trying to begin study early for this class as I've heard it's a toughie)

Basically, Pugh proves the uncountability of a closed interval [a,b] of real numbers using a geometric construction which pairs each point on the line segment [a,b] with a point on a unit circle which is then paired with a unique point on the real number line.

So, since the reals are uncountable, it follows that the reals on the interval [a,b] are uncountable as well (because a bijection has been defined between them.)

Now, my question is not about the content of the proof, per se. What troubles me is the reliance of this proof on geometry. Is this rigorous? The notion of the real numbers being represented as points on a line is certainly intuitive, and the proof definitely makes sense in that regard, but I always thought part of the purpose of this course was to clean up the fuzzy intuition regarding the real number line that is common to calculus students. Now here I see this fuzzy intuition being used as a tool for proof!

Now I am totally cool with the dedekind construction of the real numbers, but what I am not cool with is the (apparent) equivalence between the real numbers (in the sense of the dedekind construction) and the points on the geometric line. Again, it certainly makes sense, and perhaps I am being a bit pedantic here, but is the equivalence just so screamingly obvious that it can be used as a tool for proof with no comments, or am I missing something here? Thanks guys, awesome forum.
 
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  • #2
I'm not clear why you think it is "fuzzy intuition" that there is a one-to-one mapping from the set of real numbers to the line. That follows from the fact that set of real numbers is "complete". Perhaps the proof of that is what you want. (And it is not "screamingly obvious" but it is true.)
 
  • #4
Like any "axiom" it depends upon your starting point. If you take the real numbers as "given", then yes, completeness (in any of several equivalent forms) is taken as an axiom. If you define the real numbers, from the rationals, using Dedekind cuts, then the least upper bound property (one form of "completeness") can be proved easily. If you use "equivalence classes of increasing sequences of real numbers" instead, then it is easy to prove "monotone convergence", another form of "completeness". If you use "equivalence classes of Cauchy" sequences, then you can prove the Cauchy criterion.
 

FAQ: Is Pugh's Use of Geometry in Proving Uncountability Rigorous?

What is a Pugh - fuzzy bijection?

A Pugh - fuzzy bijection is a mathematical concept that describes a one-to-one correspondence between two sets, where the elements of one set are mapped to elements of the other set in a fuzzy or imprecise manner.

How is a Pugh - fuzzy bijection different from a regular bijection?

A regular bijection is a one-to-one correspondence between two sets where the mapping is precise and exact. A Pugh - fuzzy bijection, on the other hand, allows for some degree of fuzziness or imprecision in the mapping.

What are the applications of Pugh - fuzzy bijections?

Pugh - fuzzy bijections have applications in various fields such as computer science, data analysis, and linguistics. They can be used to model uncertain or imprecise information and to handle data that is not easily categorized or classified.

How are Pugh - fuzzy bijections used in computer science?

In computer science, Pugh - fuzzy bijections are used for data clustering, pattern recognition, and information retrieval. They can also be used in fuzzy logic and artificial intelligence algorithms to handle uncertainty and imprecision in decision-making processes.

Are there any limitations to Pugh - fuzzy bijections?

Like any mathematical concept, Pugh - fuzzy bijections have their limitations. They may not be suitable for all types of data and may not always provide accurate results. Additionally, the degree of fuzziness or imprecision in the mapping can be subjective and may vary depending on the individual or application using it.

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