As usual, post solutions in ROT13.
I did some Aversion Factoring and found that my main aversion to writing math is the terrible LaTeX support on WordPress. For now, I’ll try writing things up offline and posting PDFs.
HPMoE is a sequence on the entropy method in combinatorics. It should be fun to think about for anyone interested in information theory and probability as well.
Please post solutions to the exercises in ROT13.
If only it were all so simple! If only there were evil people somewhere insidiously committing evil deeds, and it were necessary only to separate them from the rest of us and destroy them. But the line dividing good and evil cuts through the heart of every human being. And who is willing to destroy a piece of his own heart?
― Aleksandr Solzhenitsyn,
Solzhenitsyn states that the line dividing good and evil cuts through every human heart. This can’t literally be true – human hearts are somewhat evenly distributed around the globe.
The first question we might ask is: instead of a line, what’s the simplest surface we can draw that cuts through the heart of every human being? But simply cutting through is a boring interpolation question. If you’re an idealist like me, you’d think every human heart is exactly half good and half evil. So the real question is: what’s the simplest surface that bisects every human heart?
I have compiled my solutions to exercises of the first 9 chapters of Alon and Spencer’s excellent book The Probabilistic Method (second edition). Hopefully in the future I will fill out the solutions to the remaining chapters. Here they are: solutions_compilation. Please send comments/corrections to firstname.lastname@example.org.
I recently gave a talk (here is an outline) about the work of K. F. Roth on the famous triangle problem of Heilbronn, and was shocked and saddened to discover that Roth passed away that same day. Terry Tao wrote a great post about some of Roth’s most important results in analytic number theory.
Today I will discuss the general approach of Roth, later refined by Komlos, Pintz, and Szemeredi, in proving upper bounds for the Heilbronn Triangle Problem. At the end of the day, the most interesting step comes from a quasi-orthogonality property between indicator functions of bounded strips in the plane. Let be a pair of points in the plane and let be the indicator function of the strip of points at most away from the line through . We cut off these functions outside some convex region, say the unit circle – call this the cutoff region. Then, it is natural to consider the “expansion function”
which measures the weighted difference between two strips of different widths , around the same line. The point is that if we integrate this expansion function against the indicator function of a given set of points in the plane, then counts the change in the density of points when we expand from a strip of width to a strip of width .
A primitive set is a set of positive integers such that no pair of distinct elements satisfies .
A square-primitive set is a set of positive integers such that no pair of distinct elements has ratio equal to an square integer.
In the following writeup, I show how to construct square-primitive sets with very short gaps . This relies on dividing the poset ordered by divisibility into antichains consisting of all numbers in with exactly (not necessarily distinct) prime factors, and then picking one randomly.