Defining Randomness: Is It Based on Algorithms or Physics?

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Discussion Overview

The discussion revolves around the nature of randomness, questioning whether it is fundamentally based on algorithms or physical processes. Participants explore the implications of randomness in mathematical definitions, computational generation, and physical theories, considering both theoretical and practical aspects.

Discussion Character

  • Debate/contested
  • Conceptual clarification
  • Mathematical reasoning
  • Technical explanation

Main Points Raised

  • Some participants suggest that true randomness may require a physical process, such as quantum phenomena, rather than being solely algorithmic.
  • Others argue that randomness is difficult to define and may depend on the context, with some asserting that computers can only produce pseudo-random sequences.
  • A few participants claim that the existence of a specific set of numbers in a defined order negates randomness, proposing that even "randomly generated" sequences could follow a predictable pattern.
  • There is mention of algorithmic randomness (Kolmogorov complexity) and statistical randomness, with some questioning whether true randomness can be defined mathematically.
  • Concerns are raised about the independence of outputs from random number generators and whether they can be considered truly random.
  • Some participants assert that randomness cannot be fundamentally defined, although it can be applied in probability theory and statistical tests.
  • A radical viewpoint suggests that randomness only exists within infinite sets, challenging the concept of randomness in finite contexts.
  • There is a discussion about the relationship between physical processes and the definition of random variables, questioning how these concepts interact.

Areas of Agreement / Disagreement

Participants express a range of views on the definition and existence of true randomness, with no consensus reached. Disagreements persist regarding the nature of randomness in finite versus infinite contexts and the role of algorithms versus physical processes.

Contextual Notes

The discussion highlights limitations in defining randomness, including the dependence on specific definitions and the unresolved nature of mathematical proofs regarding random number generators.

SW VandeCarr
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If I use a simple algorithm to generate all the numbers from 000,000,000 to 999,999,999, is there a rule for determining how many of these digit sequences are "random"? Slightly more complex algorithms generate the irrational numbers. Are these digit sequences random? For any finite length of the digit sequence of an irrational number, the next digit is determined, not random.

It would appear that a true random number generator must be based on something that can be safely said to be not determined by any algorithm, such as a quantum level physical process. Does this take the notion of a "random variable" from mathematics to physics?
 
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It's my understanding that randomness is a pretty hard concept to nail down, and I believe there is still debate as to whether there even exists true randomness - it depends on your definition, which bring us back to your question.

I believe computers can only generate pseudo-randomness, and for the reasons you mention. You might take a que from MATLAB as to how to possibly quantify randomness, as the uniformity of the distribution of the numbers output from some function.

Pretty interesting stuff.
 
There is no such thing as a "random sequence". The fact that you have a specific set of numbers in a specific order means it is NOT random. You can have "randomly generated" sequences depending on how the order is generated. But it is quite possible that such a "randomly generated" sequence might turn out to be 1, 2, 3, 4, ...!
 
HallsofIvy said:
There is no such thing as a "random sequence". The fact that you have a specific set of numbers in a specific order means it is NOT random. You can have "randomly generated" sequences depending on how the order is generated. But it is quite possible that such a "randomly generated" sequence might turn out to be 1, 2, 3, 4, ...!

I agree. But how do you know a generator is truly a random generator? Is this a question of mathematics or physical theory (referring to my OP)? In other words, is there any way to mathematically prove a generator is truly a random generator?
 
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Hey, that wasn't part of the question! It's not my department!
 
HallsofIvy said:
Hey, that wasn't part of the question! It's not my department!

You responded just as I was editing my last post. Can there be any mathematical proof that a given number sequence generator is a random number generator? Based on your response it appears the answer is 'no' and random number generators can only be defined in terms of physical theory. Is this correct?
 
There are definitions of randomness -- see http://en.wikipedia.org/wiki/Algorithmically_random_sequence" . However, that's not really "true" randomness. You can also test statistically whether a sequence follows any particular random distribution. But you can't really define true randomness mathematically
 
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gel said:
There are definitions of randomness -- see http://en.wikipedia.org/wiki/Algorithmically_random_sequence" . However, that's not really "true" randomness. You can also test statistically whether a sequence follows any particular random distribution. But you can't really define true randomness mathematically

I agree. I'm aware of algorithmic (Kolmogorov) randomness regarding non-compressible algorithms and statistical randomness based on probability distributions. If a physical process such as quantum process is needed to define a truly random (non-algorithmic) generator, how does this relate to the notion of a random variable? We can define a random variable in terms of a mapping from a probability space into an event space, but can we define how this function actually works?

I can specify the required parameters of a distribution and a random generator will output a series of 'n' values which will converge to these parameters as 'n' grows large. However, computer based random generators are really pseudo-random. I cannot know if each unit of output is statistically independent of any other unit of output.

To me this introduces an unusual feature to Probability Theory and other theories which utilize probability, in that it ultimately seems to depend on the undefined notion of randomness, or have missed something here?
 
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I agree that ultimately you can't define what randomness is. You can mathematically define the notion of a probability space, and apply it to real-world problems. However, you can't prove at a fundamental level that it really does apply -- although you can perform statistical tests.

I don't think that this is an unusual feature of probability theory though. Maths deals with abstractions, and any applications rely on ultimately undefinable concepts as to what it actually means. But it does correspond with what we experience (hopefully).
 
  • #10
The only way a sequence could possibly be random is if it were part of an infinite set.
There is no such thing as random in a finite universe.
 
  • #11
netometry said:
The only way a sequence could possibly be random is if it were part of an infinite set.
There is no such thing as random in a finite universe.

That's pretty radical. For one thing the digit sequences of the irrational numbers are infinite and some think they are random. I disagree since they are produced by an algorithm which will always repeat the exact same sequence up to any n every time it is invoked. In my view quantum level physical processes are our best, probably only, example of true (non- algorithmic) random number generators.

I don't know what this has to do with the size of the universe.
 

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