Do Irrational Numbers Provide Reliable Seeded Random Number Streams?

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Discussion Overview

The discussion revolves around the effectiveness of irrational numbers as seeded random number input streams, examining their properties in terms of randomness, normality, and distribution. Participants explore theoretical implications and computational aspects related to the use of irrationals in random number generation.

Discussion Character

  • Exploratory
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • Some participants propose that irrational numbers could be effective for seeded random number streams, citing properties like non-repeating sequences and even distribution of values.
  • Others argue that while almost all numbers are expected to have properties conducive to randomness, proving that specific irrational numbers are normal (a requirement for reliable random number generation) is challenging.
  • A participant expresses skepticism about the statement that "almost all" irrationals have the desired properties, noting the existence of non-normal irrationals as counterexamples.
  • There is a discussion about the implications of normality, suggesting that if irrationals are normal, the occurrence of specific bit patterns would also approach infinity as more digits are calculated.
  • Some participants highlight the need for a defined distribution to make probabilistic statements about the randomness of bit streams derived from irrationals.
  • Concerns are raised about the computational complexity of irrationals and their suitability as pseudo-random number generators.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the effectiveness of irrational numbers as random number generators. There are competing views regarding the properties of irrationals, particularly concerning normality and the implications for randomness.

Contextual Notes

Participants acknowledge the limitations in proving normality for specific irrational numbers and the complexities involved in defining distributions for randomness. The discussion reflects uncertainty about the relationship between irrational numbers and their utility in random number generation.

Chris Miller
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Are irrationals effective (seeded) random number input streams? E.g., here's 171/2 to 2496 (8K bits) decimal places:

4.123105625617660549821409855974077025147199225373620434398633573094954346337621593587863650810684296684544040939214141615301420840415868363079548145746906977677023266436240863087790567572385708225521380732563083860309142749804671913529322147978718167815796475906080565496973900766721383689212106708921029005520264976997227788461399259924591373145657819254743622377232515783073400662476891460894993314102436279443386280552637475060905080869257482675403757576927464631666351033096817122919874195864431971054705958485725931943603620656058152613585046428067872150064104914222367522243486737258047037771274998566571218570432100303602606506487154690698281546846459564503441849930597639509078619959043334207783036732466105002383305603648597891517738125149725101393295630516977396156134483704021469549517283774775128332086775432479301964503858945967736521957022356481292823232373091650044755709460165721749143175547451122718361635317492475624065195560022755934398822460451518623945769412122844523427764255912670433259808358492948699826803953313743117174259527446589487487995234588945341405362382216244897199383951723677736924815737740851390093874931215463256061131831025557439033296612065618997712372326637094637265748287231103821317707944772530780064797150678855818398908582322952162045692531561131920561778167348673892987498555458433124657440601285674187836856748287375368481499912380912509688262497561558561564648512481411215339812008301990104085930861062338067167258928822842126024770742381463219000159897259624750259093195821477134731917698441102319595010755969064406071469393642506505486427451376148387657994040157094448093988829687785599616740434885132269481081155527404578852192449351277914392107618272900599754897954312002170599256849466159387615532763790999551021418146407027743000792920490048243451252056874608711185472125959950450945481146458616792396812655520824304951486086333901135640630166910365347510269977305391756449457931367201466774922328035237350342552906155151563822733055685642499595284430373695550870606523686673143876906178092044034814292694187010803880108829021799880687696158697329126877696593420355145932219374892438065025680057784508087680163993195284779117186081306592021305623343958242917631701153763240709357137139143819622153188015764287100179012418273573753050688530502962200477947919154553842693338844717836001761469185048394692345476131766736808878375874811980697221956669693993181703367244994221297365315344095040553005626348185982780376611654361701359383702910820779

It seems to satisfy randomness: e.g., .5 bit on/off probability, (provably) non-repeating, values evenly distributed; but will this continue to be the case as it's taken to infinite decimal places?
 
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Probably. Almost all numbers have this property.
 
We don't know. As one of the requirements to serve as random number generator you would want a number to be normal. While most real numbers are normal, it is very hard to prove this property for specific numbers. The numbers where we have this proof are not suitable for a pseudo-RNG.
 
Thank you, mathman. "Probably"? Interesting choice of words. All irrationals probably have this property? But no others. Both sets (i.e., reals that have this property and reals that don't) are infinite. So I have some trouble with "almost all."

Thanks, mfb. I love a good "We don't know." One of those things that can neither be proved nor disproved? Would you agree that irrationals tend to be slow to compute, but work as pseudo-RNGs as far as we've calculated any of them? What blows my mind a little (doesn't take a lot) is that, if they are "normal" (thanks for the link and term), then as their bits are calculated to infinity, the number of consecutive on (or off, or any other arrangement of) bits we would eventually (and infinitely) encounter also approaches infinity with a probability that approaches 1.
 
Chris Miller said:
All irrationals probably have this property?
Not all irrationals are normal. Only "most". A classic example of a non-normal irrational is 0.101001000100001...

In order to make a statement about probability, one would need to come up with a distribution first.
 
Right, one could construct infinite abnormal irrational's with non-repeating patterns.

Any distribution (bit stream) for which the probability of bit change is 0.5 (as in a coin toss). Like if one were (somehow able) to examine infinite coin flips, there should be infinite junctures at which the number of consecutive heads approached infinity with a probability approaching 1.
 
My understanding: unit interval with uniform distribution - almost all (i.e. probability = 1) numbers are normal.
 

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