Irrationals as seeded randoms

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  • Thread starter Chris Miller
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In summary, irrationals are potentially effective as seeded random number input streams, as they seem to satisfy randomness and evenly distributed values. However, it is not known if this property continues to hold as the number of decimal places approaches infinity. While most irrationals are normal, it is difficult to prove this property for specific numbers, making it challenging to determine if a given irrational is suitable as a pseudo-random number generator. Additionally, not all irrationals are normal, as seen in the example of non-normal irrational numbers constructed with non-repeating patterns.
  • #1
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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  • #2
Probably. Almost all numbers have this property.
 
  • #3
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.
 
  • #4
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.
 
  • #5
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.
 
  • #6
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.
 
  • #7
My understanding: unit interval with uniform distribution - almost all (i.e. probability = 1) numbers are normal.
 

1. What are "Irrationals as seeded randoms"?

"Irrationals as seeded randoms" refer to a method of generating random numbers using irrational numbers as the seed or starting point. These numbers are used to create a sequence of seemingly random values.

2. How are irrationals used to generate random numbers?

Irrational numbers, such as pi or the square root of 2, are used as the starting point or seed for a random number generator. The decimals of these numbers are then used to calculate a sequence of random values.

3. Why are irrationals used instead of whole numbers?

Irrational numbers are used because they are considered to be truly random, unlike whole numbers which follow a predictable pattern. This makes the resulting random numbers more unpredictable and useful in applications such as cryptography and simulations.

4. Can irrationals be used for any type of random number generation?

Yes, irrationals can be used for any type of random number generation, including both pseudo-random and true random number generation. However, they may be more commonly used for pseudo-random number generation as they are easier to work with and can still produce highly unpredictable sequences.

5. Are there any limitations to using irrationals as seeded randoms?

One limitation of using irrationals as seeded randoms is that the resulting sequence may not be truly random due to the limitations of computer algorithms and the fact that the decimals of irrational numbers are still finite. Additionally, some applications may require a specific range of values which may be difficult to achieve using irrationals as the seed.

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