In analysis and its applications, the L^2 norm is also rather special.

My hot take is that it should be called the L^(1/2) norm. Many theorems and formulas become a lot easier to state if you redefine L^p as L^(1/p).

For instance, under this notation, the dual of L^p is just L^(1-p). And Littlewood’s interpolation inequality is a lot easier to remember, since the exponents used come directly from the coefficients in the convex combination:

If r = ap + bq, where a and b are nonnegative and sum to 1, then |f|_r <= (|f|_p)^a (|f|_q)^b

You should join the folks at the tau-not-pi club.

And going off on a tangent: in thermodynamics, we should measure coldness (coldness ~ 1 / temperature). It makes all the math come out nicer.

See https://en.wikipedia.org/wiki/Coldness

Coldness handles 'negative temperatures' much better. As Wikipedia puts it:

> Though completely equivalent in conceptual content to temperature, β [= coldness] is generally considered a more fundamental quantity than temperature owing to the phenomenon of negative temperature, in which β is continuous as it crosses zero whereas T has a singularity.[7]

i.e. the first information-encoding base.

I'm not sure. The Fibonacci numbering system has a smaller effective base.

(And there's always unary.)

See https://en.wikipedia.org/wiki/Fibonacci_coding