Sitabhra Sinha

**Class Schedule:**

**4/8/17: Introduction**

**Steven N. Durlauf, "How can statistical mechanics contr ibute to social science?", Proc. Natl. Acad. Sci. USA, 96: 10582, 1999 (4/8/17)**

See also the video lecture by Steven N. Durlauf on Statistical Mechanics as a Tool for Economic Theory in YouTube.

**Philip Ball, "The Physical
Modelling of Human Social Systems", Complexus, 1:190, 2003 (4/8/17)**

You may also want to see the book-length treatment by Philip Ball,

**7/8/17: Enumeration and Probabilities**

See Linda E. Reichl, *A Modern Course in Statistical Physics* (Wiley-VCH, 2016), Chapter 2.

**9/8/17: Probabilities and their Distribution: Bayes Rule, the Monty Hall problem, Moments and all that**

**Wikipedia entry on the "Monty Hall Problem" (7/8/17)**

You may also want to see the book-length treatment by Jason Rosenhouse, *The Monty Hall Problem: The Remarkable Story of Math's Most Contentious Brainteaser* (Oxford University Press, 2009).

To see how the Normal distribution can be obtained from the Binomial distribution in the limit of large *N* (number of trials) and large *N p* (*p* being the probability of a particular outcome), refer to Reichl, Appendix A.1.3

For Shockley's derivation of the log-normal distribution from a multiplicative random process and applying it to explain how research productivity varies across individual scientists, see **William Shockley, "On the statistics of individual variations of productivity in research laboratories", Proc. IRE 45: 279, 1957.**

For a nice treatment of the pendulum as a dynamical system in phase space, see **Steven Strogatz, Nonlinear Dynamics and Chaos, pp. 176-181.**

Unfortunately it is not always possible to associate an energy function with dynamical systems - only when we are dealing with conservative systems. See

The ergodic theorem was proved in a mathematical tour-de-force by G. D. Birkhoff in 1931 - for a relatively simpler (but still daunting to the mathematically uninitiated) exposition see **G. D. Birkhoff, "What is the Ergodic Theorem ?", American Mathematical Monthly 49(4): 222 (1942).**

There is a nice brief discussion about Bortkiewicz's fitting of the Poisson distribution to the number of soldiers dying in the Prussian army from horse kicks in **
Andy Cheshire's blogpost: "No Horsing Around with the Poisson Distribution, Troops"**

**18/8/17: Simple model of polymer, Ideal gas (equation of state) and the maximum entropy principle**

What happens when there are interactions of some kind between the different parts of a polymer ? A nice example is the self-avoiding walk where a walker cannot visit a site already visited before. See the article **"Self-avoiding walks" by Gordon Slade, Mathematical Intelligencer 16(1): 29 (1994).**

For more on maximum entropy principle see **"The principle of maximum entropy" by
Silviu Guiasu and Abe Shenitzer, Mathematical Intelligencer 7(1): 42 (1985).**

Also see **E. T. Jaynes, "Information Theory and Statistical Mechanics", Physical Review 106(4): 620 (1957).**

**21/8/17: Shannon's measure of information entropy; Introduction to the Ising model**

An accessible derivation of the form of the information entropy from first principles is given in Mario Rasetti, *Modern Methods in Equilibrium Statistical Mechanics* (World Scientific, 1986), pp 280-289.

A very readable introduction to the quirks of the Ising model is **Brian Hayes, "The World in a Spin", American Scientist, Sept-Oct 2000 (14/8/17)**

**22/8/17: Condition probability vs likelihood (the German tank problem); Exact solution of the Ising chain**

The German tank problem which demonstrates that likelihood is not a probability distribution as the total may diverge is discussed in detail in Wikipedia - see **Wikipedia: The German Tank Problem**

The related problem of determining the size of the alphabet from a small sample of writing is discussed in **Alan Mackay, ``On the type-fount of the Phaistos disc", Statistical Methods in Linguistics 4: 15 (1964). **

For the exact solution of the 1-dimension spin chain, see Plischke and Bergersen.

**1/9/17: Peierls argument for spontaneous magnetization in the 2-dimensional Ising model**
The argument by Peierls can be found in **Rudolf Peierls, ``On Ising's model of ferromagnetism'', Mathematical Proceedings of the Cambridge Philosophical Society 32: 477 (1936).**

In class however I used the cleaner statement of the argument given later by

**6/9/17: Dynamical systems, Codimension-2 bifurcation and the P-V-T & H-M-T surfaces of fluids & magnetic systems; Spin-correlation function in the Ising chain; Behavior arpund the critical point: Critical exponents alpha, beta, gamma, delta, eta and nu**

See the section in Strogatz on **Pitchfork bifurcation** and **Imperfect bifurcations and catastrophes.**

**13/9/17: Landau phenomenological theory of phase transitions: first order and second order**

**13/10/17: Renormalization group for 1-dimensional Ising model**

**16/10/17: Wilson RG; Relating eigen properties of RG with critical exponents**

**17/10/17: Differential form of RG transformation**

**18/10/17: Renormalization group for 2-dimensional triangular lattice Ising model**

**27/10/17: Fractals: Introduction**

For a nice introduction to fractals see Steven Strogatz, *Nonlinear Dynamics and Chaos*, pp. 398-413.

The analysis of Jackson Pollock paintings using fractals is discussed in Alison Abbott, ``Fractals and art: In the hands of a master'', *Nature* 439: 648 (2006).

The original article of Richard Taylor *et al* is available at ``Fractal analysis of Pollock's drip paintings", *Nature* 399: 422 (1999).

Note that this analysis has been challenged by Katherine Jones-Smith and Harsh Mathur, ``Fractal Analysis: Revisiting Pollock's drip paintings", *Nature* 444: E9 (2006)

**30/10/17: Fractals: Similarity and Box-counting dimensions; Frenkel-Kontorova model**

**31/10/17: Ising spins on the fractal Koch curve**

**2/11/17: Percolation: Introduction; Forest fire model**

**10/11/17: Percolation in 1-dimensional lattice**

**15/11/17: Percolation in Bethe lattice**

**16/11/17: Heisenberg and XY spin model; Vortices and anti-vortices in the XY model**

**17/11/17 (morning): XY spin model: Topological phase transition**

A brief discussion on how to simulate the XY model is given in Planar model

**17/11/17 (afternoon): Disorderd systems: Spin glass; Hopfield model**

**Assignments**

**Assignment 1 (due on 16/08/2017)**

**Assignment 2 (due on 31/08/2017)**

**Examinations**

**Mid-term take-home examination (due on 12/10/2017)**

**End-term examination question paper (29/11/2017)**

**Additional Readings**

**Textbooks:**

There is, unfortunately, no one book that everyone agrees on as the best text on statistical mechanics of interacting systems and critical phenomena.

We will consult

Michael Plischke and Birger Bergersen, *Equilibrium Statistical Physics*,

which covers most of the topics in equilibrium phenomena that we will deal with in this course - but probably is not that good from a pedagogical point of view.

A book which is close to perfect in terms of approaching the subject matter (IMHO) but is possibly too terse for students is

James P. Sethna, *Entropy, Order Parameters and Complexity*.

A compromise is the book by Linda E. Reichl, *A Modern Course in Statistical Physics* (4th revised edition, 2016).

For renormalization group theory, I will mostly use

Finn Ravndal, *Scaling and Renormalization Groups:
Introductory Lectures*.

In later part of the course we will consult for the topic of networks

Mark Newman, *Networks: An Introduction*,

possibly the best textbook on the subject.

There is a strong connection between the concepts of advanced statistical mechanics and the concepts in the theory of dynamical bifurcations, and for the latter you can consult

Steven H Strogatz, * Nonlinear Dynamics and Chaos*,

a pedagogical marvel (I wish there was a Strogatz equivalent for advanced statistical mechanics).

For non-equilibrium systems (specfically for pattern formation in such systems), a very good non-technical book is

Philip Ball, *The Self-Made Tapestry*.

For a more technical introduction see

Malte Henkel, Haye Hinrichsen and Sven Lubeck, *Non-Equilibrium Phase
Transitions* (Springer, 2008)

A very concise version of the above is Haye Hinrichsen,
**"Non-equilibrium phase transitions"**, Lecture notes for International Summer School on
Problems in Statistical Physics XI, 2005.

**Web resources for Advanced Statistical Mechanics:**
**
Michael Cross's three semester course on Statistical Physics, CalTech, 2006**
**
Michael Cross's course on Collective Effects in Equilibrium and Nonequilibrium Physics, Beijing Normal University, 2008**
**
Gareth Alexander's course on Statistical Mechanics of Complex Systems, University of Warwick, 2011**
**David Tong's course on Statistical Mechanics and Thermodynamics, University of Cambridge, 2012**