In the second part, I introduce random k-SAT and the satisfiability conjecture, and give some moment-method based proofs of bounds on the satisfiability threshold. When most of the particles in a block of iron have correlated spins, then on a macroscopic scale we observe this correlation as the phenomenon of magnetism or ferromagnetism if we want to be technically correct.
This is called the Ising model, and it is one of the more canonical models in statistical physics.
As the temperature increases, the kinetic energy also increases, and we will begin to see more anomalies. In fact, magnetization exhibits a phase transition: For example, we may think of the atoms as being arranged in a 3D cubic lattice, and then would be the 3D cubic lattice graph. These are topics for which the traditional theoretical CS approaches seem ill-suitedwhile on the other hand statistical physics has supplied a rich albeit not always mathematically rigorous theory.
From what I was able to gather on Wikipediathis is because the unpaired electrons in the distinct iron atoms repel each other, and if two nearby iron atoms have the same spins, then this allows them to be in a physical configuration where the atoms are further apart in space, which results in a lower energy state because of the repulsion between electrons.
It is meant to serve as an introduction to statistical physics, and is composed of two parts: Suppse that we have iron atoms, and that their interactions are described by the for simplicity unweighted graph with adjacency matrix. We give each atom a label inand we associate with each atom a spin For each choice of spins or state we associate the total energy.
Statistical physics is the first topic in the seminar course I am co-teaching with Boaz this fall, and one of our primary goals is to explore this theory.
From particle interactions to macroscopic behaviors In statistical physics, the goal is to understand how materials behave on a macroscopic scale based on a simple model of particle-particle interactions.
This blog post is a re-working of a lecture I gave in class this past Friday. For example, consider a block of iron.
To this end we define the Boltzmann distribution, with density function: We also introduce a temperature parameter. This phase transition is in contrast to the alternative, in which the iron would gradually lose its magnetization as it is heated.Port Manteaux churns out silly new words when you feed it an idea or two.
Enter a word (or two) above and you'll get back a bunch of portmanteaux created by jamming together words that are conceptually related to your inputs.
For example, enter "giraffe" and you'll get. A recent work of Chattopadhyay et al. (CCC ) introduced a new framework for the design of pseudorandom generators for Boolean functions.
It works under the assumption that the Fourier tails of the Boolean functions are uniformly bounded for all levels by an exponential function.Download