Front Cover -- Understanding Molecular Simulation: From Algorithms to Applications -- Copyright Page -- Contents -- Preface to the Second Edition -- Preface -- List of Symbols -- Chapter 1. Introduction -- Part I: Basics -- Chapter 2. Statistical Mechanics -- 2.1 Entropy and Temperature -- 2.2 Classical Statistical Mechanics -- 2.3 Questions and Exercises -- Chapter 3. Monte Carlo Simulations -- 3.1 The Monte Carlo Method -- 3.2 A Basic Monte Carlo Algorithm -- 3.3 Trial Moves -- 3.4 Applications -- 3.5 Questions and Exercises -- Chapter 4. Molecular Dynamics Simulations -- 4.1 Molecular Dynamics: The Idea -- 4.2 Molecular Dynamics: A Program -- 4.3 Equations of Motion -- 4.4 Computer Experiments -- 4.5 Some Applications -- 4.6 Questions and Exercises -- Part II: Ensembles -- Chapter 5. Monte Carlo Simulations in Various Ensembles -- 5.1 General Approach -- 5.2 Canonical Ensemble -- 5.3 Microcanonical Monte Carlo -- 5.4 Isobaric-Isothermal Ensemble -- 5.5 Isotension-Isothermal Ensemble -- 5.6 Grand-Canonical Ensemble -- 5.7 Questions and Exercises -- Chapter 6. Molecular Dynamics in Various Ensembles -- 6.1 Molecular Dynamics at Constant Temperature -- 6.2 Molecular Dynamics at Constant Pressure -- 6.3 Questions and Exercises -- Part III: Free Energies and Phase Equilibria -- Chapter 7. Free Energy Calculations -- 7.1 Thermodynamic Integration -- 7.2 Chemical Potentials -- 7.3 Other Free Energy Methods -- 7.4 Umbrella Sampling -- 7.5 Questions and Exercises -- Chapter 8. The Gibbs Ensemble -- 8.1 The Gibbs Ensemble Technique -- 8.2 The Partition Function -- 8.3 Monte Carlo Simulations -- 8.4 Applications -- 8.5 Questions and Exercises -- Chapter 9. Other Methods to Study Coexistence -- 9.1 Semigrand Ensemble -- 9.2 Tracing Coexistence Curves -- Chapter 10. Free Energies of Solids -- 10.1 Thermodynamic Integration -- 10.2 Free Energies of Solids.

10.3 Free Energies of Molecular Solids -- 10.4 Vacancies and Interstitials -- Chapter 11. Free Energy of Chain Molecules -- 11.1 Chemical Potential as Reversible Work -- 11.2 Rosenbluth Sampling -- Part IV: Advanced Techniques -- Chapter 12. Long-Range Interactions -- 12.1 Ewald Sums -- 12.2 Fast Multipole Method -- 12.3 Particle Mesh Approaches -- 12.4 Ewald Summation in a Slab Geometry -- Chapter 13. Biased Monte Carlo Schemes -- 13.1 Biased Sampling Techniques -- 13.2 Chain Molecules -- 13.3 Generation of Trial Orientations -- 13.4 Fixed Endpoints -- 13.5 Beyond Polymers -- 13.6 Other Ensembles -- 13.7 Recoil Growth -- 13.8 Questions and Exercises -- Chapter 14. Accelerating Monte Carlo Sampling -- 14.1 Parallel Tempering -- 14.2 Hybrid Monte Carlo -- 14.3 Cluster Moves -- Chapter 15. Tackling Time-Scale Problems -- 15.1 Constraints -- 15.2 On-the-Fly Optimization: Car-Parrinello Approach -- 15.3 Multiple Time Steps -- Chapter 16. Rare Events -- 16.1 Theoretical Background -- 16.2 Bennett-Chandler Approach -- 16.3 Diffusive Barrier Crossing -- 16.4 Transition Path Ensemble -- 16.5 Searching for the Saddle Point -- Chapter 17. Dissipative Particle Dynamics -- 17.1 Description of the Technique -- 17.2 Other Coarse-Grained Techniques -- Part V: Appendices -- A Lagrangian and Hamiltonian -- A.1 Lagrangian -- A.2 Hamiltonian -- A.3 Hamilton Dynamics and Statistical Mechanics -- B Non-Hamiltonian Dynamics -- B.1 Theoretical Background -- B.2 Non-Hamiltonian Simulation of the N,V,T Ensemble -- B.3 The N,P,T Ensemble -- C Linear Response Theory -- C.1 Static Response -- C.2 Dynamic Response -- C.3 Dissipation -- C.4 Elastic Constants -- D Statistical Errors -- D.1 Static Properties: System Size -- D.2 Correlation Functions -- D.3 Block Averages -- E Integration Schemes -- E.1 Higher-Order Schemes -- E.2 Nosé-Hoover Algorithms -- F Saving CPU Time.

F.1 Verlet List -- F.2 Cell Lists -- F.3 Combining the Verlet and Cell Lists -- F.4 Efficiency -- G Reference States -- G.1 Grand-Canonical Ensemble Simulation -- H Statistical Mechanics of the Gibbs Ensemble -- H.1 Free Energy of the Gibbs Ensemble -- H.2 Chemical Potential in the Gibbs Ensemble -- I Overlapping Distribution for Polymers -- J Some General Purpose Algorithms -- K Small Research Projects -- K.1 Adsorption in Porous Media -- K.2 Transport Properties in Liquids -- K.3 Diffusion in a Porous Media -- K.4 Multiple-Time-Step Integrators -- K.5 Thermodynamic Integration -- L Hints for Programming -- Bibliography -- Author Index -- Index.