Difference between revisions of "CSSS 2008 Santa Fe-Readings"
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* [http://www-personal.umich.edu/~mejn/nbook/ <i>Monte Carlo Methods in Statistical Physics.</i> Newman and Barkema. Oxford University Press (1999).] | * [http://www-personal.umich.edu/~mejn/nbook/ <i>Monte Carlo Methods in Statistical Physics.</i> Newman and Barkema. Oxford University Press (1999).] | ||
* [http://citeseer.ist.psu.edu/andrieu03introduction.html "An Introduction to MCMC for Machine Learning." Andrieu, de Freitas, Doucet and Jordan. <i>Machine Learning</i> <b>50</b>, 5-43 (2003).] | * [http://citeseer.ist.psu.edu/andrieu03introduction.html "An Introduction to MCMC for Machine Learning." Andrieu, de Freitas, Doucet and Jordan. <i>Machine Learning</i> <b>50</b>, 5-43 (2003).] | ||
+ | |||
+ | ===Dan Stein: Disordered Systems, Quenched Order === | ||
+ | |||
+ | This course is designed to introduce the participant to the study of systems with quenched disorder, which are fascinating systems in their own right but which also helped introduce many of the ideas and concepts that have become central to complexity studies. These ideas have found applications to problems from fields as diverse as biology, computer science, and economics, and we will explore some of these as well. | ||
+ | |||
+ | The course presupposes no prior knowledge of physics or statistical mechanics, and math will be kept to a minimum. If you'd like a flavor of some of the things we'll be discussing, you can take a look at D.L. Stein, ``Spin Glasses'', Scientific American v. 261, pp. 52--59 (1989). Despite the passage of time, many of the issues and questions discussed in that article remain open! | ||
+ | |||
+ | For those who would like to access the subject on a more technical level (which is unnecessary for this course), here are some references: | ||
+ | |||
+ | K. Binder and A.P. Young, ``Spin Glasses'', Rev. Mod. Phys. v. 58, p. 801 (1986). | ||
+ | |||
+ | M. Mezard, G. Parisi, and M. Virasoro, ``Spin Glass Theory and Beyond'' | ||
+ | (World Scientific, 1986). | ||
+ | |||
+ | J.A. Hertz and K.H. Fischer, ``Spin Glasses'' (Cambridge, 1989). | ||
+ | |||
+ | C.M. Newman and D.L. Stein, ``Topical Review: Ordering and Broken Symmetry in Short-Ranged Spin Glasses'', Journal of Physics: Condensed Matter 15, R1319--R1364 (2003). | ||
+ | |||
+ | The last of these can be accessed from my [http://www.physics.nyu.edu/~ds1752/techpubs18.html/ <i> Web page </i>] |
Revision as of 01:13, 20 May 2008
CSSS Santa Fe 2008 |
Contents
Week One: Modeling/Nonlinear Dynamics
Liz Bradley: Non-Linear Dynamics I-IV
Nonlinear Dynamics
Owen Densmore & Steve Guerin: Modeling
Before the modeling class (afternoon the first day!) you should:
- Download the most recent versions of both NetLogo and NetLogo 3D from http://ccl.northwestern.edu/netlogo/
- Run some of the Model Library examples for both NetLogo and NetLogo 3D:
- Start the application
- Click Model Library in the File menu, try these:
- NetLogo: Art > Diffusion Graphics
- NetLogo 3D: 3D > Sample Models > Raindrops 3D
Note: move the 3D raindrop world by click & drag - To run most of the models, click "Setup" then "Go"
- To see the code, click on the Procedures tab
- Start the application
- Finally, under the "Help" menu, click "User Manual" and explore!
Week Two: Ecology/Evolution/Molecular Biology/Disordered Systems
Aaron Clauset: MCMC for Simulation and Inference
The following three references cover a wide variety of details related to Markov chain Monte Carlo (MCMC) methods. The second and third are general references, written for physics and machine learning audiences. (The Newman and Barkema book should be available through the SFI Library.) The first shows an application of MCMC methods in the context of learning the large-scale structure of networks.
- "Hierarchical structure and the prediction of missing links in networks." Clauset, Moore and Newman. Nature 453, 98-101 (2008).
- Monte Carlo Methods in Statistical Physics. Newman and Barkema. Oxford University Press (1999).
- "An Introduction to MCMC for Machine Learning." Andrieu, de Freitas, Doucet and Jordan. Machine Learning 50, 5-43 (2003).
Dan Stein: Disordered Systems, Quenched Order
This course is designed to introduce the participant to the study of systems with quenched disorder, which are fascinating systems in their own right but which also helped introduce many of the ideas and concepts that have become central to complexity studies. These ideas have found applications to problems from fields as diverse as biology, computer science, and economics, and we will explore some of these as well.
The course presupposes no prior knowledge of physics or statistical mechanics, and math will be kept to a minimum. If you'd like a flavor of some of the things we'll be discussing, you can take a look at D.L. Stein, ``Spin Glasses, Scientific American v. 261, pp. 52--59 (1989). Despite the passage of time, many of the issues and questions discussed in that article remain open!
For those who would like to access the subject on a more technical level (which is unnecessary for this course), here are some references:
K. Binder and A.P. Young, ``Spin Glasses, Rev. Mod. Phys. v. 58, p. 801 (1986).
M. Mezard, G. Parisi, and M. Virasoro, ``Spin Glass Theory and Beyond (World Scientific, 1986).
J.A. Hertz and K.H. Fischer, ``Spin Glasses (Cambridge, 1989).
C.M. Newman and D.L. Stein, ``Topical Review: Ordering and Broken Symmetry in Short-Ranged Spin Glasses, Journal of Physics: Condensed Matter 15, R1319--R1364 (2003).
The last of these can be accessed from my Web page