Potential Flux

the algorithm, in calculating the maximum and minimums, turned out to be zero-sum.

obviously, as the algorithm is completely bijective (meaning it is a means of rearranging the information, without any loss of the original information), this is the most optimal case.

generally, any number is recomposed into the base where the digital stream is compared for maximum and minimums in terms of how the digits relate to each other.

a concise, ‘best case’ example:

1,000,000 = “one million” in base 10. 

1,000,000 = “sixty four” in base 2.

by utilizing a different base, the same digits can be used to store vastly different amounts of information.

1,010,101 would also be a ‘best case’ example as it still only uses ones and zeros.

in this best case example, the total ‘cost’ of the re-expression is:

 

“base: 10″ 1001 = ‘10′

“from base: 2″ 0001 = ‘2′

“digital stream: ” = 1000000

 

re-expressed stream is:

100100011000000

 

compared to one million in binary, which is:

11110100001001000000

 

which is five bits less.

now of course you’d need byte alignment for the stream as well, so the minimum number possible re-expression is much greater than one million, but there is a definite minimum.

 

for potential, there would be correspondences such as 1000000 in base ten trillion.

 

all in all, this algorithm determines, base by base, which would be the best re-expression.