Michael Kosterlitz, Duncan Haldane, and David J. Thouless are the laureates of Nobel Prize in Physics 2016, “for theoretical discoveries of topological phase transitions and topological phases of matter.” Before Thouless, topology was not known to the physics community. It is a basic knowledge nowadays, however.

I am particularly familiar with Berezinskii-Kosterlitz-Thouless phase transition. What is it? Before that, phase transitions had been studied through the framework of spontaneous symmetry breaking, employing the tools in functional field theory and renormalization group. Matter can be in either disordered state that the symmetry is not broken, or ordered state that a particular continuous symmetry is broken. Near the critical point, many observables found to exhibit long-range order, with $C(r) \sim \frac{1}{r}$, which are so universal that all physical systems described by the same Landau-Ginzburg-Wilson (LGW) model are found to obey it. But in lower dimensions such as d=2, proved by Mermin, Wagner, and Hohenberg, an ordered state is not stable because of its huge fluctuation.

The absence of an ordered state does not exclude the possibility of a phase transition. Berezinskii in 1971, and Kosterlitz and Thouless in 1973, suggested a phase transition that concerns the proliferation of topological objects. While the correlation must be short-ranged, i.e., $C(r) \sim e^{-\frac{r}{\xi}}$, a normal description using LGW model in d=2 does not permit that, unless vortices are considered. However, below a certain temperature, due to energy configuration, it is better for these vortices to be bounded. Then the material exhibits quasi-long-range order, i.e., $C(r) \sim \frac{1}{r^{\alpha}}$. This change in correlation function is a phase transition different from that induced by spontaneous symmetry breaking, but the proliferation of isolated topological solitons.

Their work started the study of topology in condensed matter system. Not long after this work, there was the study of topological defects in various condensed matter system, and then fractional quantum Hall effect, topological insulators, topological quantum computing, A phase in liquid crystals and helimagnets etc. “Topological” is the buzzword in condensed matter physics community nowadays. Recently, there is a preprint article connecting machine learning and topological physical state. (See: arXiv:1609.09060.)

In machine learning, deep learning is the buzzword. However, to understand how these things work, we may need a theory, or we may need to construct our own features if a large amount of data are not available. Then, topological data analysis (TDA) becomes important in the same way as condensed matter physics.

Leo Kadanoff passed away on October 26, 2015.

Leo Kadanoff is an American physicist in University of Chicago. His most prominent work is the idea of block spin and coarse-graining in statistical physics. [Kadanoff 1966] His work has an enormous impact on second-order phase transition and critical phenomena, based on the knowledge of scale and universality. His idea was further developed into renormalization group (RG), [Wilson 1983] which leads to Ken Wilson awarded with Nobel Prize in Physics in 1982.

The concept of RG has also been used to explain how deep learning works, [Mehta, Schwab 2014] which you can read more about from my previous blog entry and their paper. While only the equivalence between RG and Restricted Boltzmann Machine was rigorously proved, it sheds a lot of insights about how it works, in a way that I believe it is roughly what happens. Without the concept that Kadanoff developed, it is impossible for Mehta and Schwab to make such a connection between critical phenomena and neural network.

He has other contributions such as computational physics, urban planning, computer science, hydrodynamics, biology, applied mathematics and geophysics. He has been awarded with the Wolf Prize in Physics (1980), Elliott Cresson Medal(1986), Lars Onsager Prize (1998), Lorentz Medal (2006), and Isaac Newton Medal (2011).

His work has a significant impact on statistical physics, including problems of second-order phase transition, percolation, various condensed matter systems (such as conventional superconductors, superfluids, low-dimensional systems, helimagnets), quantum phase transition, self-organized criticality etc. To learn more about it, I highly recommend Shang-keng Ma’s Modern Theory of Critical Phenomena [Ma 1976] and Mehran Karder’s Statistical Physics of Fields. [Karder 2007]

Rest In Peace!