Exploring Number Line Density: Constant or Variable? Mathematical Proof?

In summary, density is a cardinality of a set that can be described with a rule. It is related to fractals and conventional space. It is greater than zero for fractals of D>1 and less than one for fractals of D=1.
  • #1
Loren Booda
3,125
4
Is the number density of the number line constant or variable?

Can either be proved mathematically?
 
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  • #2
Well, since no new numbers come into the line, nor any existing number jumps out, I'd call it constant... notwithstanding the fact that I have no idea on how to define 'number density' in the first place.
 
  • #3
Loren Booda said:
Is the number density of the number line constant or variable?
I guess Loren is free to define "number density" in any way he likes. And until he does so, it will be hard to give a sensible answer.
Can either be proved mathematically?
The wording of this question comes up quite often by non-mathemticians, and I always wonder what they mean with that last word.
 
  • #4
Is the number density of the number line constant or variable?

"Real number" lines have a variable density where they and their well-defined operations do not complete the intervals (-oo, +oo).
 
  • #5
Okay, so please tell us what you mean by "number line density"!
 
  • #6
Thanks, Hurkyl.

Consider the real number line with number distances conserved relative to each other.

Now, for instance, distort the positive ray so that the distance between its whole numbers is doubled relative to those of the negative ray. The number line density of the positive numbers has become half that of the negative numbers.

A distortion of relative number distances on the real number line corresponds to a change in the real number line density. There exist other operations which can cause a relative change in the real number line density.
 
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  • #7
Loren Booda said:
Thanks, Hurkyl.

Consider the real number line with number distances conserved relative to each other.

Now, for instance, distort the positive ray so that the distance between its whole numbers is doubled relative to those of the negative ray. The number line density of the positive numbers has become half that of the negative numbers.

Actually that's not true. Even if you stretch the number line, the stretched version is just as dense as the original. You can even stretch a finite interval into the entire infinitely-long real line, and both the finite interval and the entire real line are equally dense.

That's what they mean by calling it a continuum.
 
  • #8
SteveL27,

You're quite right.

However, "number density" as described next relies on infinite sets changing on similar scales:

Might different infinite cardinals vary in "number densities" (infinitely discontinuous) or are they all necessarily continuous (density one)?

Also, might discontinuous fractals describe "number densities" related to their dimensionalities D (here approximately a line, where 0 < D < 1)?
 
  • #9
Loren Booda said:
"number density" as described next [...]

Unfortunately, what follows next are two more questions, not a definition.

It seems to me that you struggle to put your finger on a concept which is hard to grasp and which you are passionate to investigate about. If that is the case, your first task should be to arrive at a definition of your new concept. Try some, even if temporarily or tentatively. Something precise, of the form "density is the cardinality of the set constructed this way..." or "density is a function from a set to the reals with the following rule...". To what objects can you apply your concept of density, besides the real line? To intervals? To sets in general, or which kind of sets? To other objects? These questions may help you complete parts of your definition. You really need to make the attempt to nail it down, as flying around with a concept between quotes will leave you nowhere (or anywhere, which is the same).
 
  • #10
Number line density can be defined generally for fractal dimensions D[>=]1.

The fractal range 0<D<1 represents singular "dust" of number density zero, and D>1 includes continuous or discontinuous, single or multiple structures.

Conventional space of whole number dimensions have number density equal to one.

A conventional, continuous line thus has number density equal to one.

Since the fractal line (or line fragments) of D=1 extend into a second dimension, their number density is diluted to less than one, but greater than zero.

Number density can be more accurately calculated with the relation N=S^D, where S is the scaling factor, D the dimension, and N the ratio between the size of a fundamental fractal fragment to a scaled-up fractal fragment.

Knowing this, the number density can be defined approximately as N/S=S^(D-1).
 
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1. What is number line density?

Number line density refers to the spacing or distribution of numbers on a number line. It is a measure of how closely or sparsely numbers are placed on a number line.

2. Is number line density constant or variable?

This is a debated topic in mathematics. Some argue that number line density is constant, meaning that the spacing between numbers on a number line remains the same, while others argue that it is variable, meaning that the spacing can change based on the numbers being represented.

3. Can you provide a mathematical proof for number line density?

Yes, there are several mathematical proofs that have been proposed to support the arguments for both constant and variable number line density. These proofs typically involve concepts from number theory, such as prime numbers and divisibility.

4. How does number line density relate to fractions and decimals?

Number line density plays a crucial role in understanding fractions and decimals. For example, on a number line with constant density, fractions and decimals that are closer to each other will have a smaller difference in value compared to those that are farther apart.

5. What are the implications of the debate on number line density?

The debate on number line density has implications for our understanding of mathematical concepts, such as infinity and continuity. It also has practical applications in fields like computer science and physics, where precise measurements and calculations are necessary.

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