Click on the image to enlarge, or better in its full vectorised glory!

Mathematics has this funny way of treating you.

You slog for hours to understand a single concept, wrestling with the
mental acrobatics performed by what you swear is the most hideous proof
you've seen (a title to be bested tomorrow), but still feeling compelled
to toil on. Hours pass, and then suddenly, a switch clicks, the pieces
fall in place, and you "get it".

Proofs are hard to assemble, and to the new learner, cannot be discussed
in the terms directed at the learned. The newbie must instead re-invent
the mental constructs needed for the proof using the cryptic words of
the author. But once the proof is assembled once, the mind is clear, and
it can be so obviously disassembled and reassembled again.

That's the reward for the long hours of toil, and anybody who has
wrestled with those weird symbols can attest to the euphoria at the end
of it. Unfortunately, it lasts for about a day, and then the dread of
another task comes crashing down.

Still, we have the drive to carry on, not only because of some abstract
notion of understanding at the end of the journey, but also because of
the joys of applying this new knowledge to problems. This active doing
of Math, is probably one of the quickest ways to get to a Flow
State, and it's no wonder
our brains like the exercise.

But while toy problems serve for quick bouts of fun, they certainly
aren't the driving force for further learning. Instead, it's the times
when we get a sneak peek out of the ludic context - when we apply our
Math in a piece of software, when we teach somebody and watch as their
minds open with new insight, when we create value - that we realise that
the honeymoon with Math really does have it's perks.

You think differently. You see new patterns. You find truth. There is
now an acceptance towards Math, just like there is an acceptance towards
life - as something with truth that you'll never understand, but whose
joy will be realised upon coming full circle. It feels complete.

Math helps you understand that completeness, but is itself, never
complete.