If you take the original values used to determine the final “random number” and run them through the same sequence of calculations, you will always reach the same value.
We rely on the fact that the inputs are so numerous and/or difficult to replicate to deem the final value “random”. But that doesn’t mean that the value cannot be reached by a second party given perfect knowledge of the original state of all inputs.
True randomness, on the other hand, is impossible to calculate even with that perfect knowledge, because we aren’t relying on the state of inputs running through a calculation.
But that’s my point: just because you apply deterministic steps to a truly random input doesn’t make the output not truly random. You use real entropy as your starting point, which is literally exactly what you call “true randomness”. This means the output has the same level of “true randomness” as your “truly random” input, because you mathematically don’t lose entropy along the way.
The input is not truly random though. If it was, we could just use that input, with no other steps, and have a truly random output. You’re confusing an unknown state with randomness.
No, it actually and literally is truly random. You’d need to know everything about the hardware itself and the environment around it in incredible detail (incl. the temperature of every individual small patch of material, air flow and the state of air in and around the case) to reliably predict the initial entropy for a given modern system, since tiny changes in e.g. temperature will completely change the input.
It’s only a small bit of entropy, but enough to kick-start the RNG in a way that can reliably create high-quality entropy.
KairuByte@lemmy.dbzer0.com 11 months ago
If you take the original values used to determine the final “random number” and run them through the same sequence of calculations, you will always reach the same value.
We rely on the fact that the inputs are so numerous and/or difficult to replicate to deem the final value “random”. But that doesn’t mean that the value cannot be reached by a second party given perfect knowledge of the original state of all inputs.
True randomness, on the other hand, is impossible to calculate even with that perfect knowledge, because we aren’t relying on the state of inputs running through a calculation.
FooBarrington@lemmy.world 11 months ago
But that’s my point: just because you apply deterministic steps to a truly random input doesn’t make the output not truly random. You use real entropy as your starting point, which is literally exactly what you call “true randomness”. This means the output has the same level of “true randomness” as your “truly random” input, because you mathematically don’t lose entropy along the way.
KairuByte@lemmy.dbzer0.com 11 months ago
The input is not truly random though. If it was, we could just use that input, with no other steps, and have a truly random output. You’re confusing an unknown state with randomness.
FooBarrington@lemmy.world 11 months ago
No, it actually and literally is truly random. You’d need to know everything about the hardware itself and the environment around it in incredible detail (incl. the temperature of every individual small patch of material, air flow and the state of air in and around the case) to reliably predict the initial entropy for a given modern system, since tiny changes in e.g. temperature will completely change the input.
It’s only a small bit of entropy, but enough to kick-start the RNG in a way that can reliably create high-quality entropy.