The 2021 Nobel Prize in Physics
The subfield of physics often known as “Complexity” is still a bit hard to nail down. Models of self-organized criticality have taught us a great deal about how systems behave. Often, the hallmark of complex systems is that small scale physics manifests nontrivially at large scales.
In particle physics this bit is easy to model: at tiny scales we often just rescale the electric charges and the masses. In more complicated systems - like huge collections of interacting magnets, turbulent fluids or even just the weather, organizing principles are few and far between.
Mercifully there are some, and a subset of these ideas have been award this year’s Nobel Prize in Physics.
Spin Glasses and Complex Systems
Half the prize when to Italian Physicist Giorgio Parisi for his diverse body of work, including parton evolution equations in QCD to disordered arrangements in a lattice of magnetic dipoles. “Frustrated” disorder is more than simple randomness. It’s the inability of nature to settle into a comfortable pattern. A crystal structure that “almost fits”, like mismatched IKEA furniture parts that results in a duct tape solution. Modeling how nature manifests this behavior led to a bit of applied mathematics that, to quote the Nobel Prize Committee
“... make it possible to understand and describe many different and apparently entirely random materials and phenomena, not only in physics but also in other, very different areas, such as mathematics, biology, neuroscience and machine learning.”
Climatology FTW
The other half of this year’s Nobel Prize in Physics was awarded to climatologists Suki Manabe and Klaus Hasselmann.
If the weather weren’t complex enough, studying how it evolves in time for decades to centuries adds another dimension to each of the complex input variables. Manabe and Hasselmann both modeled the climate numerically.
Manabe’s foundational work on 1970’s era computers - a heroic feat in itself - essentially gave birth to the field. He and colleague Tony Broccoli recount these early days of climate modeling in their recent book (for a context filled review - and some historical photos - check out this book review at Physics Today).
Hasselmann’s contributions afforded a link between the short-term phenomena of “weather” with the long-term evolution of the “climate”. Using statistical techniques to combine data points into observable fingerprints - essentially data mining - Hasselmann was able to isolate and quantify the human contribution to climate change.
