### Archive

Archive for September, 2011

## OpArt

OpArt is, by definition, a style of visual art based upon optical illusions. Let it be a painting, a photograph or any other mean, the objective of this style is to play with the interaction of what you see, and what it really is. A classical OpArt piece involves confusion by giving impression of movement, impossible solids, hidden images, conflicting patterns, warping, etc. And of course, Mathematics is a perfect vehicle to study—and even perform—this form of art.

In this post I would like to show an example of how to use trivial mathematics to implement a well-known example (shown above) in $\LaTeX$ with the tikz package, and leave as homework another more interesting example.

Observe first the image above: the optical effect arises when conflicting concentric squares change the direction of their patterns. You may think that the color is the culprit of this effect but, as you will see below, it is only the relationship between the pure black-and-white patterns what produces the impression of movement.

## So you want to be an Applied Mathematician

The way of the Applied Mathematician is one full of challenging and interesting problems. We thrive by association with the Pure Mathematician, and at the same time with the no-nonsense, hands-in, hard-core Engineer. But not everything is happy in Applied Mathematician land: every now and then, we receive the disregard of other professionals that mistake either our background, or our efficiency at attacking real-life problems.

I heard from a colleague (an Algebrist) complains that Applied Mathematicians did nothing but code solutions of partial differential equations in Fortran—his skewed view came up after a naïve observation of a few graduate students working on a project. The truth could not be further from this claim: we do indeed occasionally solve PDEs in Fortran—I give you that—and we are not ashamed to admit it. But before that job has to be addressed, we have gone through a great deal of thinking on how to better code this simple problem. And you would not believe the huge amount of deep Mathematics that are involved in this journey: everything from high-level Linear Algebra, Calculus of Variations, Harmonic Analysis, Differential Geometry, Microlocal Analysis, Functional Analysis, Dynamical Systems, the Theory of Distributions, etc. Not only are we familiar with the basic background on all those fields, but also we are supposed to be able to perform serious research on any of them at a given time.

My soon-to-be-converted Algebrist friend challenged me—not without a hint of smugness in his voice—to illustrate what was my last project at that time. This was one revolving around the idea of frames (think of it as redundant bases if you please), and needed proving a couple of inequalities involving sequences of functions in $L_p$—spaces, which we attacked using a beautiful technique: Bellman functions. About ninety minutes later he conceded defeat in front of the board where the math was displayed. He promptly admitted that this was no Fortran code, and showed a newfound respect and reverence for the trade.

It doesn’t hurt either that the kind of problems that we attack are more likely to attract funding. And collaboration. And to be noticed in the press.

Alright, so some of you are sold already. What is the next step? I am assuming that at his point you own your Calculus, Analysis, Probability and Statistics, Linear Programming, Topology, Geometry, Physics and you are able to solve most known ODEs. From here, as with any other field, my recommendation is to slowly build a Batman belt: acquire and devour a sequence of books and scientific articles, until you are very familiar with their contents. When facing a new problem, you should be able to recall from your Batman belt what technique could work best, in which book(s) you could get some references, and how it has been used in the past for related problems.

Following these lines, I have included below an interesting collection with the absolutely essential books that, in my opinion, every Applied Mathematician should start studying:

## Smallest Groups with Two Eyes

Today’s riddle is for the Go player. Your task is to find all the smallest groups with two eyes and place them all together (with the corresponding enclosing enemy stones) in a single $19 \times 19$ board. Let me give you some tips first: