Renormalization group (RG) ideas are all the rage in physics these days, and one of my goals for graduate school is to become more familiar with this framework. Here are my thoughts so far.
The renormalization group is an extremely powerful tool that can be used to determine which microscopic aspects of a system are relevant to its macroscopic behavior. It exploits the crucial property that macroscopic systems are — for mathematical purposes — effectively infinite, and that there is a huge range of scales between the microscopic picture and the resolution at which finite-size effects start to manifest themselves.
The critical point
In its simplest application, RG also requires the system to be at a so-called critical point, which can be defined in the following way. Imagine that the system in question can be fully specified by a finite number of knobs or parameters
and that as we tune one of the knobs there is a critical point where some extensive macroscopic observable becomes multivalued. In other words, when we tune through in different copies of the system, individual copies end up with different values of . Since is extensive, we know it can be written as the average of some local quantity
where is called the order-parameter. It gives the local value of the multivalued macroscopic observable at different points within the system. Typically, we define so that its numerical value in the single-valued region is zero.
Thus, with some precision we can now say that a critical point is a point in parameter space where the system average of some order parameter becomes nonzero and multi-valued. Since the entire (effectively infinite) system chooses a particular value of , this requires that the local order parameter is correlated over infinitely large regions. In other words, its correlation length diverges:
More to come…