A related point is comparing x^y vs y^x, for 1 < x < y.
It can be easily shown that the "radix economy" described in the article is identical to this formulation by simply taking the logarithm of both expressions (base 10 as described in the article, but it doesn't really matter, as it's just a scaling factor; this doesn't change the inequality since log x is monotonically increasing for x > 0): y log x vs x log y. Or, if you want to rearrange the terms slightly to group the variables, y / log y vs x / log x. (This doesn't change the direction of the inequality, as when restricted to x > 1, log x is always positive.) If you minimize x / log x for x > 1, then you find that this minimum value (i.e. best value per digit) is achieved at x=e.
(Choosing the base = e for calculation purposes: take a derivative and set to zero -- you get (ln x - 1) / (ln x)^2 = 0 => ln x - 1 = 0 => ln x = 1 => x = e.)
For some intuition:
For small x and y, you have that x^y > y^x (consider, for instance, x=1.1 and y=2 -- 1.1^2 = 1.21, vs 2^1.1 is about 2.14). But when x and y get large enough, you find the exact opposite (3^4 = 81 is larger than 4^3 = 64).
You might notice that this gets really close for x=2 and y=3 -- 2^3 = 8, which is just barely smaller than 3^2 = 9. And you get equality in some weird cases (x=2, y=4 -- 2^4 = 4^2 = 16 is the only one that looks nice; if you consider 3, its pairing is roughly 2.47805).
It turns out that what really matters is proximity to e (in a weird sense that's related to the Lambert W function). You can try comparing e^x to x^e, or if you want, just graph e^x - x^e and observe that's greater than 0 for x != e.
It can be easily shown that the "radix economy" described in the article is identical to this formulation by simply taking the logarithm of both expressions (base 10 as described in the article, but it doesn't really matter, as it's just a scaling factor; this doesn't change the inequality since log x is monotonically increasing for x > 0): y log x vs x log y. Or, if you want to rearrange the terms slightly to group the variables, y / log y vs x / log x. (This doesn't change the direction of the inequality, as when restricted to x > 1, log x is always positive.) If you minimize x / log x for x > 1, then you find that this minimum value (i.e. best value per digit) is achieved at x=e.
(Choosing the base = e for calculation purposes: take a derivative and set to zero -- you get (ln x - 1) / (ln x)^2 = 0 => ln x - 1 = 0 => ln x = 1 => x = e.)
For some intuition:
For small x and y, you have that x^y > y^x (consider, for instance, x=1.1 and y=2 -- 1.1^2 = 1.21, vs 2^1.1 is about 2.14). But when x and y get large enough, you find the exact opposite (3^4 = 81 is larger than 4^3 = 64).
You might notice that this gets really close for x=2 and y=3 -- 2^3 = 8, which is just barely smaller than 3^2 = 9. And you get equality in some weird cases (x=2, y=4 -- 2^4 = 4^2 = 16 is the only one that looks nice; if you consider 3, its pairing is roughly 2.47805).
It turns out that what really matters is proximity to e (in a weird sense that's related to the Lambert W function). You can try comparing e^x to x^e, or if you want, just graph e^x - x^e and observe that's greater than 0 for x != e.
https://www.wolframalpha.com/input?i=min+e%5Ex-x%5Ee