Glossary
- average
- Universality
- Ubiquitous: appearing everywhere; omnipresent.
- Order parameter – thermodynamic function that is different in each phase and hence can be used to distinguish between them.
- Continuous
- Correlation
- Correlation Length
- Density: mass (stuff, e.g. kilograms) per unit volume (e.g. cubic meters).
- Discrete
- Distribution: by distribution, we mean the way the probability (likelihood) of encountering a certain outcome is spread among all of the outcomes. For example, flipping a coin is a random experiment, and is characterized by a uniform probability distribution over the possible outcomes (head or tails) because the probability (likelihood) of encountering either outcome is the same (50%). Two different coins have the same probability distribution; every coin flip has the same probability distribution. This doesn't mean that every outcome is the same; it only means that the likelihood of one outcome or the other is the same.
- Scattering
- Critical Opalescence
- Critical Exponent
- Ising Model
- Fractal
- Scale
- Scale Invariance
- Reflection
- Refraction
- Scattering
- Supercritical Phase
- Fractality (see scale invariance)
- Medium (plural: media)
- Paramagnetic
- Ferromagnetic
- Recursion
- Phase Transition
- Phase: Think of a phase as a “flavor” of something. Water, for example, comes in several “flavors” – ice, liquid, and gas (steam). All three are made from the same thing (H2O), but they’re definitely different from one another in that they have different properties (for example, ice is hard, but you can walk through steam – different mechanical properties).
- Critical Point – For water: Mix of temperature and pressure at which difference between liquid and gas disappears (374 degrees deg;C, 218 atm). In general: when the natural length scale of correlations becomes infinite
- Uniform – the same everywhere.
- Statistical Self Similarity: in our context, something with statistical self similairty has the property that as you change the scale you are looking at, micrometers or milimeters or meters or kilometers, statistical quantities stay the same. Imagine you're at a giant trash heap from a helicopter - from far away, the trash looks like a bunch of pieces of junk and specs of dirt, maybe with a certain distribution of sizes or colors. Now, you land your helicopter right in the trash heap! Up close, it looks kind of like it did far away - like a bunch of pieces of junk and specs of dirt. If the trash heap has statistical self similarity, then you should see about the same distribution of really big, medium big, small, and tiny pieces of trash that you did from the helicopter. Or maybe the same percentage of red-, green-, blue-, yellow-, mauve-, and cyan-colored junk. The point is that the trash heap doesn't look exactly the same up close or far away, but there's something about the statistics of its building blocks that is the same at different size scales.