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# Nature of Randomness in Mechanical SystemsPrev TopicNext Topic

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• us
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November 8, 2022
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Dynamics of Gambling: Origins of Randomness in Mechanical Systems

if you want a good understanding of exactly how randomness arises in coin flipping, dice throwing, and the roulette wheel.   In particular, Chapter 5, entitled Nature of Randomness in Mechanical Systems

The authors model mechanical systems in high detail to allow them to calculate the bounds on initial condition uncertainties needed to allow correct prediction.   They do not model a lotto ball picking machine.

Could you model a lotto ball picking machine in sufficient detail in computer simulations on modern computers to reveal the initial condition bound uncertainties guaranteeing accurate prediction?   Yes, you could.

The importance of ball collisions creating piecewise smooth systems is key to understanding how pseudorandomness arises in lotto ball selection machines.    Without the collisions, the system could be well modeled smoothly, vastly reducing the pseudorandomness.

The authors claim that grazing collisions are the ones most responsible for pseudorandomness in mechanical systems.    Here, grazing means the state space trajectory is nearly parallel with the non-smooth subspace of one lower dimension embedded in the state space.

If the grazing collision claim is true, then all it takes is one or two dozen such grazing collisions to get the random shuffling model to guarantee a random ordering after those grazing collisions.

• Missouri
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Do PRNG's graze?  Sounds like the title of a Philip K. Dick book...

• it
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Hey Wavepack,

I think you got one fundamental point about the possible prediction of lottery outcomes. And how do you assume to know about the starting grazing collisions? It'll be all a matter of knowing that initial state.

• LAS VEGAS
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Random ???

"There are no coincidences, ( i.e. random) only synchronicities."

The words of the eminent founder of

Analytical Psychology, Dr Carl Jung, Switzerland

• Texas
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August 28, 2019
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The notion that collisions of balls in a lotto machine can be predicted such that some advantage can be gained in a fair game is utterly nonsensical. It defies all logic and reason. Now, if there were to be fraud, such that certain balls intentionally had heavier weights, that's a different story. However, I have never heard of that been shown to happen in any State-run lottery, ever.

• California
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June 27, 2015
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Quote: Originally posted by Wavepack on Jan 14, 2024

Dynamics of Gambling: Origins of Randomness in Mechanical Systems

if you want a good understanding of exactly how randomness arises in coin flipping, dice throwing, and the roulette wheel.   In particular, Chapter 5, entitled Nature of Randomness in Mechanical Systems

The authors model mechanical systems in high detail to allow them to calculate the bounds on initial condition uncertainties needed to allow correct prediction.   They do not model a lotto ball picking machine.

Could you model a lotto ball picking machine in sufficient detail in computer simulations on modern computers to reveal the initial condition bound uncertainties guaranteeing accurate prediction?   Yes, you could.

The importance of ball collisions creating piecewise smooth systems is key to understanding how pseudorandomness arises in lotto ball selection machines.    Without the collisions, the system could be well modeled smoothly, vastly reducing the pseudorandomness.

The authors claim that grazing collisions are the ones most responsible for pseudorandomness in mechanical systems.    Here, grazing means the state space trajectory is nearly parallel with the non-smooth subspace of one lower dimension embedded in the state space.

If the grazing collision claim is true, then all it takes is one or two dozen such grazing collisions to get the random shuffling model to guarantee a random ordering after those grazing collisions.

Sounds pretty good

Do they factor in the human element.  Like the guy  person that handles the balls?

• Pennsylvania
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Pennsylvania, April 24th, 1980. Nick Perry, then the host of the lottery drawings at WTAE in Pittsburgh, and lottery official Edward Plevel recruited WTAE art director Joseph Bock to inject a small amount of latex paint into the lottery balls that were not 4's or 6's. Reducing the 1:1,000 odds down to 1:8. They then played 7,000 tickets of each of the 8 combinations for a payday of \$3,500,000 when 6-6-6 was drawn. There were other co conspirators who bought the tickets. They were eventually caught and convicted.

So there is precedent for such shenanigans.

Have an EXCELlent day!

• LAS VEGAS
United States
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November 22, 2006
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Quote: Originally posted by Wavepack on Jan 14, 2024

Dynamics of Gambling: Origins of Randomness in Mechanical Systems

if you want a good understanding of exactly how randomness arises in coin flipping, dice throwing, and the roulette wheel.   In particular, Chapter 5, entitled Nature of Randomness in Mechanical Systems

The authors model mechanical systems in high detail to allow them to calculate the bounds on initial condition uncertainties needed to allow correct prediction.   They do not model a lotto ball picking machine.

Could you model a lotto ball picking machine in sufficient detail in computer simulations on modern computers to reveal the initial condition bound uncertainties guaranteeing accurate prediction?   Yes, you could.

The importance of ball collisions creating piecewise smooth systems is key to understanding how pseudorandomness arises in lotto ball selection machines.    Without the collisions, the system could be well modeled smoothly, vastly reducing the pseudorandomness.

The authors claim that grazing collisions are the ones most responsible for pseudorandomness in mechanical systems.    Here, grazing means the state space trajectory is nearly parallel with the non-smooth subspace of one lower dimension embedded in the state space.

If the grazing collision claim is true, then all it takes is one or two dozen such grazing collisions to get the random shuffling model to guarantee a random ordering after those grazing collisions.

When #3 @ the18,354 hz frequency, musical note D natural combines with #9 frequency  43,654, music note F = 43,311 hz which does not exactly the predict 43,654 hz #18 frequency because of other variable  involved but blending #3, #9, #18 predicts the vibration rate #26. Furthermore this also indicates

#3-9-18-26 rates predict #37 which have a natural affinity to play together in natural harmony.

These creative forces are in cyclical order of all things. Random is only  a false, sometimes manipulative, ILLUSION.

BOTTOM LINE: All the information to predict is available; we just need to connect the dots…..or musical notes

"There are no coincidences, ( i.e. random) only synchronicities."

The words of the eminent founder of Analytical Psychology, Dr Carl Jung, Switzerland

• LAS VEGAS
United States
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November 22, 2006
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Numerology could be essentially the "math behind ouour existence?"

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