[LA-SiGMA-TESC] TESC (Technologies of Extreme Scale Computing) seminar on Thursday (12/3)

[Wei P Feinstein]

Dear all,

The group of Technologies of Extreme Scale Computing (TESC) will have a seminar this Thursday (12/3) at 12:00pm-1:00pm in 1034 Digital Media Center.

KaMing Tam, a postdoctoral researcher at CCT and Physics department, will be presenting.  The title of his talk is "Gaining new insight of statistical mechanics of random systems by large data set analysis".

Abstract: We discuss what new opportunities large data set analytics provide for the study of classic problems in statistical mechanics. Statistical mechanics concerns the explanation of thermodynamics from the statistical properties of microscopic processes. The recent boom in "big data analytics" presents a good platform for uncovering structures in the large data set generated in the numerical simulations of statistical mechanics. We focus on the notoriously difficult randomly disordered systems. Unlike clean systems, the procedure required in averaging over disorder realizations poses a great challenge for theoretical calculations. The so-called replica trick which identifies the logarithmic function ln(x) with the algebraic function (x^n-1)/n in the limit of n tends to zero comes to the rescue. We will review some different physical scenarios derived from taking the limit of the above identity. While the physics is rather generic for many random systems, we will focus on the archetypal example--spin glass model. Analyzing the phase space sampled by Monte Carlo simulation is a direct method to discern different scenarios proposed for the spin glass phase. We discuss how patterns in the large data set generated from Monte Carlo simulation can be unveiled within the context of taxonomy. Concepts and techniques used in big data analytics such as hierarchical clustering method can be used to generate dendrograms for the study of the sampled phase space. The goal is to unleash the power of the big data analytics as a useful tool to understand the nature of random systems at low temperature.

Attention:
Remote broadcasting will be changed to Google hangouts. The meeting will be recorded and stored on youtube.

Please contact Christopher Cano (ccano at cct.lsu.edu, 225-242-9949) for details of remotely joining the seminar.

PIZZA AND DRINK WILL BE PROVIDED.
Presentation time: 12:00PM~1:00PM CST
Location: 1034 Digital Media Center

Best,
Wei

Wei Feinstein, Ph.D.
High Performance Computing
Louisiana State University
337 Frey Computing Services Center
Baton Rouge, LA  70803
Office 225-578-0582 | Mobile 251-599-3814
wfeinstein at lsu.edu<mailto:wfeinstein at lsu.edu> | lsu.edu<http://lsu.edu> | hpc.lsu.edu<http://hpc.lsu.edu>

TESC mailing list
LASiGMA-gpu at loni.org<mailto:LASiGMA-gpu at loni.org>
https://mail.loni.org/mailman/listinfo/lasigma-gpu
wiki: https://wiki.cct.lsu.edu/la-sigma/
http://www.institute.loni.org/lasigma/lasigma-gpu.php

-------------- next part --------------
An HTML attachment was scrubbed...
URL: https://mail.loni.org/mailman/private/lasigma-gpu/attachments/20151201/04ed37ec/attachment.html