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  • TITLE
  • DEDICATION
  • CERTIFICATE
  • DECLARATION
  • ACKNOWLEDGEMENT
  • GLOSSARY OF TERMS
  • CONTENTS
  • 1. Introduction
  • 1.1 Nature of polymer molecules in solution
  • Fig.1. Schematic representation of polymer molecules in dilute solutions.
  • 1.2 Excluded volume
  • 1.3 Theta point
  • 1.4 Radius of gyration
  • Fig.1.2. Schematic representation of (C.G.) centre of gravity.
  • 1.5 End-to-end distance
  • Fig.1.3. Schematic representation of skeletal atoms of a polymer chain and end-to-end distance.
  • 2. Self-Avoiding Walk on Lattices: A Review
  • 2.1 The random flight model
  • 2.2 Freely rotating chains
  • 2.3 Chains with restricted rotation and independent bond rotation potential
  • 2.4 Restricted rotation with interdependent rotation potentials
  • Fig.2.2. Minimum energy conformations for (a) ethane (b) methanol.
  • Fig.2.3. The potential energy E (φ2) of rotation about the central C-C bond in butane.
  • 2.5 Random walks, restricted walks and self-avoiding walks
  • 2.6 Methods of investigating self-avoiding walks
  • 2.6.1 Rigorous analysis
  • 2.6.2 Monte Carlo method
  • 2.6.3 Exact enumeration
  • 2.6.4 Transition matrix
  • 2.7 Properties of self-avoiding walks
  • 2.7.1 Number of walks of n-steps, Cn
  • 2.7.2 Number of polygonal closures of n-steps, qn
  • 2.7.3 Mean square length ( (0, 2)
  • 2.7.4 Probability distribution of the end points fn (x) dx
  • 2.7.5 Mean square radius of Gyration (Sn)
  • 2.8 Analogy with the Ising model
  • 3. Random Walks: Basic Notions and Notations
  • Fig.3.1. IUustrating the positive paths in a one-dimensional random walk.
  • 3.1 Returns to origin
  • 3.2 Relation between fen and Urn
  • 3.3 Theory of one dimensional random walk
  • 3.3.1 Reflection principle
  • 3.3.2 Statement of the reflection principle
  • Fig. 3.2. IUustmtion of the reflection principle
  • 3.3.3 The Ballot theorem
  • Fig.3.3 Illustration of the refledion principle
  • 3.3.4 The main Lemma
  • 3.3.5 Probability of first return to origin-F2,
  • 3.4 Multidimensional random walk
  • 3.5 Probability as a measure
  • 3.5.1 Rings and algebras
  • 3.5.2 Measure on rings
  • 3.5.3 A measurable space
  • 3.5.4 Probability
  • 3.6 The classification of random walk
  • 3.6.1 Transition function
  • 3.6.2 Recurrent and transient random walks
  • 4. Method of Computation
  • 4.1 Number systems
  • 4.2 Representation of a number in different number systems
  • 4.3 Generation of simple random walk
  • 4.4 Returns to origin
  • 4.5 Walks that avoid back-tracking
  • Table 4.1. Returns to origin in random walks which avoid back tracking in two dimension.
  • Table 4.2. Returns to origin in random walks which avoid back tracking in three dimension.
  • Table 4.3. Returns to origin in random walks which avoid back tracking in four dimension.
  • Table 4.4. Mean square end-to-end distance in random walk which avoid back tracking in various dimensions.
  • Fig.4.1. Plot of mean square length of walks that avoid back tracking against the number of steps in different dimensions.
  • Fig.4.2. Plot of the characteristic ratios of walks that avoid badc-tracking against the chain length for different dimensions.
  • Table 4.5. Lst of the characteristic ratios of walks that avoid back-tracking invarious dimensions.
  • 4.6 Self-avoiding walk
  • Table 4.6. Number of walks with at Least one self-avoiding polygonal closure in two dimension.
  • Table 4.7. Number of walks with at least one self-avoiding polygonal closurein three dimension
  • Table 4.8. Number of walks with at least one polygonal closure in four dimension.
  • Table 4.9. Number of walks with at least one polygonal closure in five dimension.
  • 4.7 Mean square end-to-end distance
  • Fig.4.3. Distribution of end-to-end distance square of 4-step simple random walks in different dimensions.
  • Fig.4.4. Distribution of end-to-end distance square of 5-step simple random walk in different dimensions.
  • Fig.4.5. Distribution of end-to-end distance square of 6-step simple random walks in different dimensions.
  • Fig.4.6. Distribution of end-to-end distance square of 4-step self-avoiding random waIks in different dimensions.
  • Fig.4.7. Distribution of end-to-end distance square of 5step self-avoiding randorn walks in different dimensions.
  • Fig.4.8. Distribution of end-to-end distance square of 6-step self-avoiding random walk in different dimensions.
  • Fig.4.9. Distribution of end-to-end distance square of 7-step simple and self avoiding random walks in different dimensions.
  • Fig.4.10. Dishibution of end-to-end distance square of 8-step simple and self avoiding randonr walks in different dimensions.
  • Fig.4.11. Distribution of end-to-end distance square of 9-step simple and self avoiding random walks in different dimensions.
  • Fig.4.12. Distribution of end-to-end distance square of 10-step simple and self avoiding random walks in different dimensions.
  • Fig.4.13. Distribution of end-to-end distance square of 11-step two dimensional simlple and self-avoiding random walks.
  • Fig. 4.14. Distribution of end-to-end distance square of 12-step two dimensional simple and self-avoiding random wak.
  • Fig.4.15. Distribution of end-to-end distance square of 13-step two dimensional simple and self-avoiding random walks.
  • Table 4.10. Number of self avoiding walks and its mean square lengths in two dimension.
  • Table 4.11. Number of self avoiding walk and its mean square lengths in three dimension.
  • Table 4.12. Number of self avoiding walks and its mean lengths in four dimension.
  • Table 4.13. Number of self avoiding walks and its mean lengths in five dimension.
  • Table 4.14. Number of self avoiding walks and its mean lengths in six dimension.
  • Table 4.15. Number of self avoiding walks and its mean lengths in seven dimension.
  • Table 4.16. Number of self avoiding walks and its mean lengths in eight dimension.
  • Table 4.17. Number of self avoiding walks and its mean square lengths in nine dimension.
  • Table 4.18. Number of self avoiding walks and its mean square lengths in ten dimension.
  • Fig. 4.16. Plot of mean square length of SAW against number of steps for 2-5 dimensions.
  • Fig.4.17. Plot of mean square length of SAW against number of steps for 6-10 dimensions.
  • Fig. 4.18. Plot of chamderstic ratios of SAW against number of steps for 2-5 dimensions.
  • Fig.4.19. Plot of characteristic ratios of SAW against number of steps for 6-10 dimensions.
  • 4.8 The traps
  • Table 4.19. Number of walks in two dimension which will be trapped in thesucceeding step.
  • Fig.4.20. All possible walks of a 7-step trap in two dimensional SAW.
  • Fig. 4.21. The four different walks of an 8-step trap in a two-dimensional SAW
  • Fig. 4.22. An eleven step self-avoiding walk in three dimension which form a trap at the 11th step.
  • 5. Results and Discussion
  • 5.1. Introduction
  • 5.2 Theory and notation
  • 5.3 Evaluation of A; (for n up to 13), R, (for n up to 12) and P; (for 2n up to 14)
  • 5.4 Comparison with exact enumeration data
  • Fig.5.1. Plot of the ratio R/A against the number of steps.
  • 6. Conclusions and Scope for Further Work
  • 6.1 Conclusions
  • 6.2 Scope for further work
  • References
  • APPENDICES
  • APPENDIX 1 List of decimal numbers corresponding to walks with at least one SAP
  • APPENDIX 2 Exact enumeration data of the distribution of the end-toend distance square of simple random walks
  • APPENDIX 3 Exact enumeration data of the distribution of the end-to-end distance square of SAW
  • APPENDIX 4 List of decimal numbers corresponding to walks that give traps
  • APPENDIX 5 Algorithms