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NNTP-Posting-Date: Sun, 29 Dec 2024 04:15:59 +0000
Subject: Re: Incompleteness of Cantor's enumeration of the rational numbers
 (extra-ordinary, effectively)
Newsgroups: sci.math
References: <vg7cp8$9jka$1@dont-email.me> <vjufr6$29khr$3@dont-email.me>
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 <bce1b27d-170c-4385-8938-36805c983c49@att.net> <vk693m$f52$2@dont-email.me>
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From: Ross Finlayson <ross.a.finlayson@gmail.com>
Date: Sat, 28 Dec 2024 20:15:28 -0800
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On 12/28/2024 07:54 PM, Ross Finlayson wrote:
> On 12/28/2024 04:22 PM, Jim Burns wrote:
>> On 12/28/2024 5:36 PM, Ross Finlayson wrote:
>>> On 12/28/2024 11:17 AM, Richard Damon wrote:
>>
>>>> [...]
>>>
>>> Consider
>>> a random uniform distribution of natural integers,
>>> same probability of each integer.
>>
>> A probability.measure maps events
>> (such as: the selection of an integer from set S)
>> to numbers in real.interval [0,1]
>>
>> For each x ∈ (0,1]
>> there is a finite integer nₓ: 0 < ⅟nₓ < x
>>
>> ⎛ Assume a uniform probability.measure
>> ⎜ P: 𝒫(ℕ) -> [0,1]
>> ⎜ on ℕ the non.negative integers.
>> ⎜ ∀j,k ∈ ℕ: P{j} = P{k} = x
>> ⎜ x ∈ [0,1]
>> ⎜
>> ⎜ If x = 0, Pℕ = ∑ᵢ₌᳹₀P{i} = 0 ≠ 1
>> ⎜ P isn't a probability.measure.
>> ⎜
>> ⎜ If x > 0,  0 < ⅟nₓ < x
>> ⎜ P{0,…,nₓ+1} > (nₓ+1)/nₓ > 1
>> ⎝ P isn't a probability.measure.
>>
>> Therefore,
>> there is no uniform probability.measure on
>> the non.negative integers.
>>
>>> Now, you might aver
>>> "that can't exist, because it would be
>>> non-standard or not-a-real-function".
>>
>> I would prefer to say
>> "it isn't what it's describe to be,
>> because what's described is self.contradictory".
>>
>>> Then it's like
>>> "no, it's distribution is non-standard,
>>> not-a-real-function,
>>> with real-analytical-character".
>>
>> Which is to say,
>> "no, it isn't what it's described to be"
>>
>>
>
> You already accept that the "natural/unit
> equivalency function" has range with
> _constant monotone strictly increasing_
> has _constant_ differences, _constant_,
> that as a cumulative function, for a
> distribution, has that relating to
> the naturals, as uniform.
>
> And that they always add up to 1, ....
>
>
> That most certainly is among the definitions
> of a distribution, the probabilities even
> range between 0 and 1.
>
> So, even though you refuse that this is
> a real function, because it's not, yet
> it's also a distribution, which it is.
>
> "Standardly as a limit of functions"
> if you won't, like Dirac's unit impulse
> function, never actually so esxcept its completion,
> yet necessarily actually so in the derivations
> that depend on it, like Fourier-style analysis,
> "real analytical character", say.
>
> Then also that it really is "a continuous
> domain" and "a discrete distribution",
> just keeps pointing out how special it is,
> "the natural/unit equivalency function".
>
>
> One of at least three set-theoretic accounted
> models of continuous domains, and establishing
> that there are non-Cartesian functions via
> an anti-anti-diagonal-argument.
>
>

So that ZF isn't internally inconsistent
with respect to real numbers, ....

.... and continuous domains.


Of course one could always just write it
in some otherwise equi-interpretable
"theory of one relation" yet it's so
that ZF and ZFC are the most well-known
and well-explored axiomatic set theories.


"Pick either: get both."