Page 1 |
Save page Remove page | Previous | 1 of 162 | Next |
|
small (250x250 max)
medium (500x500 max)
large ( > 500x500)
Full Resolution
All (PDF)
|
This page
All
|
APPLICATIONS OF LOOP CLOSURE AND STOCHASTIC POTENTIAL
SWITCHING TO MONTE CARLO SIMULATIONS OF LARGE SYSTEMS
by
Arunkumar Sharma
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Ful llment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(CHEMISTRY)
August 2011
Copyright 2011 Arunkumar Sharma
Object Description
| Title | Applications of loop closure and stochastic potential switching to Monte Carlo simulations of large systems |
| Author | Sharma, Arunkumar Kishanlal |
| Author email | aksharma@usc.edu;aham.arunsharma@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Chemistry |
| School | College of Letters, Arts And Sciences |
| Date defended/completed | 2011-06-16 |
| Date submitted | 2011-07-06 |
| Date approved | 2011-07-06 |
| Restricted until | 2011-07-06 |
| Date published | 2011-07-06 |
| Advisor (committee chair) | Mak, Chi |
| Advisor (committee member) |
Qin, Peter Haas, Stephan |
| Abstract | Simulations of many body systems suffer from a myriad of problems; the complexity of interactions, the number of interacting units, the length scale at which interactions happen, etc. It is a challenge to devise methods that can sample phase space efficiently for such systems and accurately estimate equilibrium properties. The present work focuses on the construction and application of two distinct techniques for the simulation of such systems. These methods involve large-scale changes in the system configuration and have the potential to be applicable to a variety of systems. These methods were used to study the critical behavior in a Sine-Gordon lattice model and for achieving enhanced conformational sampling in an all-atom model of proteins. ❧ A novel switching algorithm is described in which a reverse Monte Carlo method is implemented. Here, the potential is stochastically modified before the system configuration is moved. This new algorithm facilitates a generalized formulation of cluster-type Monte Carlo methods, and the generalization makes it possible to derive cluster algorithms for systems with both discrete and continuous degrees of freedom. This Reverse Monte Carlo has been applied to study the roughening transition in the Sine-Gordon model and high-accuracy simulations for system sizes up to 1024X1024 were carried out to examine the logarithmic divergence of the surface roughness above the transition temperature. This logarithmic divergence is a clear evidence that the transition belongs to the Kosterlitz-Thouless type. ❧ Proteins and other biomolecules like RNAs are extremely difficult systems to simulate because of the large system sizes involved and the complexity of interactions present. The time-scales over which interesting phenomena occur also makes it difficult for Molecular Dynamics techniques to do full justice in such systems. A loop closure Monte Carlo algorithm is derived and implemented for simulation of proteins at ambient temperatures. The loop closure method generates alternative structures for an internal segment of a chain when atomic coordinates of the atoms outside the segment are fixed. The formulation makes use of a novel representation of boundary constraints and allows the loop closure problem to be reduced in complexity from a 6-variable 6-constraint problem to a 4-variable 4-constraint problem. The proposed method is no longer limited to small loops, but can be used to close loops of arbitrarily large sizes. This brings to life the possibility to facilitate very large conformational sampling with each move. |
| Keyword | Monte Carlo; proteins; stochastic potential switching; sine gordon; critical slowing down; loop closure |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m |
| Contributing entity | University of Southern California |
| Rights | Sharma, Arunkumar Kishanlal |
| Access conditions | The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given. |
| Repository name | University of Southern California Digital Library |
| Repository address | USC Digital Library, University of Southern California, University Park Campus MC 7002, 106 University Village, Los Angeles, California 90089-7002, USA |
| Repository email | cisadmin@usc.edu |
| Archival file | uscthesesreloadpub_Volume71/etd-SharmaArun-54.pdf |
Description
| Title | Page 1 |
| Contributing entity | University of Southern California |
| Full text | APPLICATIONS OF LOOP CLOSURE AND STOCHASTIC POTENTIAL SWITCHING TO MONTE CARLO SIMULATIONS OF LARGE SYSTEMS by Arunkumar Sharma A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Ful llment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (CHEMISTRY) August 2011 Copyright 2011 Arunkumar Sharma |
