Holdings: Bridging time scales

Bridging time scales: molecular simulations for the next decade

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Bibliographic Details
Format:	Book
Language:	English
Published:	Berlin [u.a.] Springer 2002
Series:	Lecture notes in physics 605
Subjects:	Física Chemistry, Physical and theoretical -- > Computer simulation Chemistry, Physical and theoretical > Computer simulation Molecular dynamics -- > Computer simulation Molecular dynamics > Computer simulation Molecules -- > Computer simulation Molecules > Computer simulation Proteinfaltung Statistische Physik Kondensierte Materie Molekulardynamik Monte-Carlo-Simulation Konferenzschrift > 2002 > Konstanz
Online Access:	Inhaltsverzeichnis
Physical Description:	XXVI, 500 S. Ill., graph. Darst.
ISBN:	3540443177

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adam_text	TABLE OF CONTENTS PART I PROTEIN FOLDING 1 SIDECHAIN DYNAMICS AND PROTEIN FOLDING EDO KUSSELL, JUN SHIMADA, EUGENE I. SHAKHNOVICH .................. 3 1.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.3 DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 1.4 METHODS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 PART II APPLICATIONS OF STATISTICAL MECHANICS TO BIOLOGICAL SYSTEMS 2 A COARSE GRAIN MODEL FOR LIPID MONOLAYER AND BILAYER STUDIES STEVE O. NIELSEN, MICHAEL L. KLEIN ................................ 27 2.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.2 CHALLENGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 2.3 MODELS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.3.1 PREVIOUS WORK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 2.3.2 TOWARDS THE CURRENT CG MODEL . . . . . . . . . . . . . . . . . . . . . . . . 32 2.3.3 A FIRST ATTEMPT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 2.4 APPLICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 2.4.1 FLUCTUATION MODES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 2.4.2 BULK ALKANE AND WATER SURFACE TENSION . . . . . . . . . . . . . . . . . 43 2.4.3 SELF-ASSEMBLY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 2.4.4 TRANSMEMBRANE PEPTIDE INDUCED DOMAIN FORMATION . . . . . . 46 2.4.5 TRANSMEMBRANE PEPTIDE INDUCED L * TO H II PHASE TRANSITION . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 2.4.6 BUCKLING INSTABILITIES IN LANGMUIR MONOLAYERS . . . . . . . . . . . . 54 2.5 FUTURE PERSPECTIVES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 XIV TABLE OF CONTENTS PART III POLYMER STRUCTURE AND DYNAMICS 3VARIABLE-CONNECTIVITY MONTE CARLO ALGORITHMS FOR THE ATOMISTIC SIMULATION OF LONG-CHAIN POLYMER SYSTEMS DOROS N. THEODOROU ............................................. 67 3.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 3.2 THE BRIDGING CONSTRUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3.3 MONTE CARLO ALGORITHMS BASED ON THE BRIDGING CONSTRUCTION . . . . 77 3.3.1 CONCERTED ROTATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 3.3.2 DIRECTED INTERNAL BRIDGING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 3.3.3 END-BRIDGING IN THE NNµ * PT ENSEMBLE . . . . . . . . . . . . . . . . 81 3.3.4 DIRECTED END-BRIDGING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 3.3.5 SAMPLING OF ORIENTED CHAINS: NNBT µ * * MC SIMULATIONS . . 90 3.3.6 SCISSION AND FUSION ALGORITHMS FOR PHASE EQUILIBRIA . . . . . . 92 3.3.7 DOUBLE BRIDGING AND INTRAMOLECULAR DOUBLE REBRIDGING . . . 96 3.3.8 CONNECTIVITY-ALTERING MONTE CARLO AND PARALLEL TEMPERING 100 3.4 APPLICATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 3.4.1 STRUCTURE AND VOLUMETRIC PROPERTIES OF LONG-CHAIN POLYETHYLENE MELTS . . . . . . . . . . . . . . . . . . . . . . 103 3.4.2 SIMULATIONS OF POLYPROPYLENE MELTS OF VARIOUS TACTICITIES . . 107 3.4.3 SIMULATION OF POLYDIENES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 3.4.4 PREDICTION OF MELT ELASTICITY . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 3.4.5 SORPTION EQUILIBRIA OF ALKANES IN POLYETHYLENE . . . . . . . . . . . 119 3.4.6 POLYMERS AT INTERFACES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 3.5 CONCLUSIONS AND OUTLOOK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 4 BRIDGING THE TIME SCALE GAP: HOW DOES FOLDABLE POLYMER NAVIGATE ITS CONFORMATION SPACE? ALEXANDER GROSBERG ............................................. 129 4.1 INTRODUCING THE CHARACTERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 4.2 SETTING UP THE STAGE: CONFORMATION SPACE AND REACTION COORDINATE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 4.2.1 CONFORMATION SPACE: LATTICE POLYMER . . . . . . . . . . . . . . . . . . . 130 4.2.2 CONFORMATION SPACE: OFF-LATTICE POLYMER . . . . . . . . . . . . . . . . . 131 4.2.3 REACTION COORDINATE PROBLEM . . . . . . . . . . . . . . . . . . . . . . . . . . 132 4.3 UNFOLDING THE DRAMA: COMMITOR, P FOLD , AND THE REACTION COORDINATE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 4.3.1 COMMITOR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 4.3.2 DIRECT CURRENT ANALOGY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 4.3.3 DIFFUSION EQUATION AND CONTINUOUS (OFF-LATTICE) MODELS . . . . 136 4.3.4 STATIONARY AND TRANSIENT REGIMES . . . . . . . . . . . . . . . . . . . . . . . 137 TABLE OF CONTENTS XV 4.3.5 DIRECT CURRENT FORMULATION OF THE FIRST RETURN PROBLEM: CASINO PROBLEM AND ITS EASY SOLUTION . . . . . . . . . . . . . . . . . . . 138 4.3.6 DIRECT CURRENT FORMULATION OF THE COMMITOR . . . . . . . . . . . . . 139 4.3.7 DIRECT CURRENT FORMULATION OF THE LANDSCAPE . . . . . . . . . . . . . 139 4.4 CULMINATION: SO WHAT? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 5 MULTISCALE COMPUTER SIMULATIONS FOR POLYMERIC MATERIALS IN BULK AND NEAR SURFACES CAMERON ABRAMS, LUIGI DELLE SITE, KURT KREMER .................... 143 5.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 5.2 LENGTH AND TIME SCALES FOR POLYMER SIMULATIONS . . . . . . . . . . . . . . . 144 5.3 DUAL-SCALE MODELLING ANSATZ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 5.3.1 MESOSCOPIC MODELS IN BULK AND NEAR SURFACES . . . . . . . . . . . . 148 5.3.2 SYSTEMATIC MOLECULAR COARSE-GRAINING . . . . . . . . . . . . . . . . . . . 153 5.3.2.1 MAPPING SCHEMES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 5.3.2.2 COARSE GRAINED LIQUID STRUCTURE . . . . . . . . . . . . . . . . . 154 5.4 SPECIFIC SURFACE EFFECTS: BPA-PC NEAR A NI SURFACE. . . . . . . . . . . . . 156 5.5 OTHER APPROACHES: AUTOMATIC COARSE-GRAINING . . . . . . . . . . . . . . . . . 159 5.6 CONCLUSIONS, OUTLOOK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 PART IV COMPLEX AND MESOSCOPIC FLUIDS 6 EFFECTIVE INTERACTIONS FOR LARGE-SCALE SIMULATIONS OF COMPLEX FLUIDS JEAN-PIERRE HANSEN, HARTMUT L¨ OWEN .............................. 167 6.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 6.2 EFFICIENT COARSE-GRAINING THROUGH EFFECTIVE INTERACTIONS. . . . . . . . . 168 6.3 ELECTRIC DOUBLE-LAYERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 6.4 SIMULATING THE POLARIZATION OF DIELECTRIC MEDIA . . . . . . . . . . . . . . . . . 174 6.5 COARSE-GRAINING LINEAR POLYMER SOLUTIONS . . . . . . . . . . . . . . . . . . . . . 176 6.6 STAR POLYMERS AND DENDRIMERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178 6.7 COLLOIDS AND POLYMERS: DEPLETION INTERACTIONS . . . . . . . . . . . . . . . . . . 183 6.8 BINARY COLLOIDAL ALLOYS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 6.9 FROM COLLOIDAL TO NANOSCALES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 6.10 CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192 XVI TABLE OF CONTENTS PART V SLOW DYNAMICS AND REACTIVITY 7 SIMULATION OF MODELS FOR THE GLASS TRANSITION: IS THERE PROGRESS? KURT BINDER, J¨ ORG BASCHNAGEL, WALTER KOB, WOLFGANG PAUL .......... 199 7.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 7.2 TOWARDS THE SIMULATION OF REAL GLASSY MATERIALS: THE CASE OF SIO 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 7.3 PARALLEL TEMPERING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 7.4 AN ABSTRACT MODEL FOR STATIC AND DYNAMIC GLASS TRANSITIONS: THE 10-STATE MEAN FIELD POTTS GLASS . . . . . . . . . . . . . . . . . . . . . . . . . 212 7.5 THE BEAD-SPRING MODEL: A COARSE-GRAINED MODEL FOR THE STUDY OF THE GLASS TRANSITION OF POLYMER MELTS . . . . . . . . . . 217 7.6 THE BOND FLUCTUATION MODEL APPROACH TO GLASSFORMING POLYMER MELTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 7.7 CAN ONE MAP COARSE-GRAINED MODELS ONTO ATOMISTICALLY REALISTIC ONES? . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222 7.8 CONCLUDING REMARKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226 PART VI LATTICE MODELS 8 MONTE CARLO METHODS FOR BRIDGING THE TIMESCALE GAP NIGEL WILDING, DAVID P. LANDAU .................................. 231 8.1 GENERAL INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231 8.2 PROBLEMS AND CHALLENGES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232 8.2.1 INTRODUCTION TO METROPOLIS IMPORTANCE SAMPLING . . . . . . . . . . 232 8.2.2 ORIGIN OF TIME-SCALE PROBLEMS. . . . . . . . . . . . . . . . . . . . . . . . . . 234 8.2.3 TRADITIONAL COMPUTATIONAL SOLUTIONS . . . . . . . . . . . . . . . . . . . . 235 8.3 SOME RECENT DEVELOPMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236 8.3.1 SECOND ORDER TRANSITIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236 8.3.1.1 CLUSTER FLIPPING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236 8.3.1.2 THE N-FOLD WAY AND EXTENSIONS . . . . . . . . . . . . . . . . . 237 8.3.1.3 WANGLANDAU* SAMPLING . . . . . . . . . . . . . . . . . . . . . . 239 8.3.2 FIRST ORDER TRANSITIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240 8.3.2.1 FREE ENERGY COMPARISON: THE STATISTICAL MECHANICS PERSPECTIVE . . . . . . . . . . . . 241 8.3.2.2 MULTICANONICAL MONTE CARLO . . . . . . . . . . . . . . . . . . . . . 244 8.3.2.3 TRACKING PHASE BOUNDARIES: HISTOGRAM EXTRAPOLATION . . . . . . . . . . . . . . . . . . . . . . . . 245 8.3.2.4 PHASE SWITCH MONTE CARLO . . . . . . . . . . . . . . . . . . . . . . 247 TABLE OF CONTENTS XVII 8.3.2.5 FIRST ORDER TRANSITIONS AND WANGLANDAU SAMPLING . . . . . . . . . . . . . . . . . . . . 253 8.3.3 SYSTEMS WITH COMPLEX ORDER . . . . . . . . . . . . . . . . . . . . . . . . . . . 256 8.3.4 DYNAMIC* BEHAVIOR: SPIN DYNAMICS WITH DECOMPOSITIONS OF EXPONENTIAL OPERATORS . . . . . . . . . . . 258 8.4 SUMMARY AND OUTLOOK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 9 GO-WITH-THE-FLOW LATTICE BOLTZMANN METHODS FOR TRACER DYNAMICS CHRISTOPHER P. LOWE, SAURO SUCCI ................................. 267 9.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267 9.2 LBE SCHEMES WITH TRACER DYNAMICS . . . . . . . . . . . . . . . . . . . . . . . . . . 269 9.2.1 EXTRA-DIMENSIONAL METHODS . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 9.2.2 HYBRID GRIDGRID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 9.2.3 HYBRID GRIDPARTICLE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270 9.2.4 GO-WITH-THE-FLOW KINETIC METHODS . . . . . . . . . . . . . . . . . . . . . . 270 9.3 HYDRODYNAMIC DISPERSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270 9.3.1 THE MOMENT PROPAGATION METHOD . . . . . . . . . . . . . . . . . . . . . . 272 9.3.2 GALILEAN INVARIANCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 276 9.3.3 VARYING THE PECLET NUMBER. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 276 9.3.4 THE VACF AT INFINITE TIME . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277 9.3.5 GENERALIZATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278 9.4 APPLICATIONS OF THE MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279 9.4.1 DISPERSION IN A TUBE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279 9.4.2 DISPERSION IN CUBIC PERIODIC ARRAYS . . . . . . . . . . . . . . . . . . . . . 282 9.5 CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284 PART VII MULTISCALE MODELLING IN MATERIALS SCIENCE 10 ATOMISTIC SIMULATIONS OF SOLID FRICTION MARTIN H. M¨ USER ................................................ 289 10.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289 10.1.1 THE RELEVANCE OF DETAILS: A SIMPLE CASE STUDY . . . . . . . . . . 291 10.2 SOLID FRICTION VERSUS STOKES FRICTION . . . . . . . . . . . . . . . . . . . . . . . . . . 294 10.3 DRY FRICTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 297 10.3.1 RIGID WALLS AND GEOMETRIC INTERLOCKING . . . . . . . . . . . . . . . . . 297 10.3.2 ELASTIC DEFORMATIONS: ROLE OF DISORDER AND DIMENSIONS . . . 298 10.3.3 EXTREME CONDITIONS AND NON-ELASTIC DEFORMATIONS . . . . . . . . 299 10.4 LUBRICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301 10.4.1 BOUNDARY LUBRICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303 10.4.2 HYDRODYNAMIC LUBRICATION AND ITS BREAKDOWN. . . . . . . . . . . . 305 XVIII TABLE OF CONTENTS 10.5 SETTING UP A TRIBOLOGICAL SIMULATION . . . . . . . . . . . . . . . . . . . . . . . . . 305 10.5.1 THE ESSENTIAL INGREDIENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305 10.5.2 PHYSO-CHEMICAL PROPERTIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307 10.5.3 INITIAL GEOMETRY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308 10.5.4 DRIVING DEVICE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310 10.5.5 THERMOSTATING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 10.5.6 METHODS TO TREAT THE WALLS ELASTICITY . . . . . . . . . . . . . . . . . . 311 10.5.7 CALCULATION OF THE FRICTION FORCE . . . . . . . . . . . . . . . . . . . . . . . . 313 10.5.8 INTERPRETATION OF TIME SCALES AND VELOCITIES . . . . . . . . . . . . . . 313 10.6 CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 314 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 316 PART VIII METHODOLOGICAL DEVELOPMENTS IN MD AND MC 11 BRIDGING THE TIME SCALE GAP WITH TRANSITION PATH SAMPLING CHRISTOPH DELLAGO, DAVID CHANDLER ................................ 321 11.1 WHY TRANSITION PATH SAMPLING IS NEEDED . . . . . . . . . . . . . . . . . . . . . 321 11.2 HOW TRANSITION PATH SAMPLING WORKS . . . . . . . . . . . . . . . . . . . . . . . . 323 11.2.1 PROBABILITIES OF TRAJECTORIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323 11.2.2 DEFINING THE TRANSITION PATH ENSEMBLE . . . . . . . . . . . . . . . . . . 324 11.2.3 SAMPLING THE TRANSITION PATH ENSEMBLE . . . . . . . . . . . . . . . . . 325 11.3 WHAT TRANSITION PATH SAMPLING CAN DO . . . . . . . . . . . . . . . . . . . . . . 326 11.3.1 THE RARE EVENT PROBLEM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327 11.3.2 SOLVING THE RARE EVENT PROBLEM WITH TRANSITION PATH SAMPLING . . . . . . . . . . . . . . . . . . . . . . . . . 327 11.3.3 INTERPRETING THE ENSEMBLE OF HARVESTED PATHS . . . . . . . . . . . . 329 11.3.4 RATE CONSTANTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330 11.4 WHAT TRANSITION PATH SAMPLING CANNOT DO (YET) . . . . . . . . . . . . . . 330 11.4.1 ONE AND TWO POINT BOUNDARY PROBLEMS . . . . . . . . . . . . . . . . . 330 11.4.2 CHAINS OF STATES WITH LONG TIME STEPS . . . . . . . . . . . . . . . . . . 331 11.4.3 PATTERN RECOGNITION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332 12 THE STOCHASTIC DIFFERENCE EQUATION AS A TOOL TO COMPUTE LONG TIME DYNAMICS RON ELBER, AVIJIT GHOSH, ALFREDO C´ ARDENAS ......................... 335 12.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335 12.2 MOLECULAR DYNAMICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335 12.2.1 INITIAL VALUE FORMULATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336 12.2.2 A BOUNDARY VALUE FORMULATION IN TIME . . . . . . . . . . . . . . . . . 336 12.2.3 A BOUNDARY VALUE FORMULATION IN LENGTH . . . . . . . . . . . . . . . . 340 12.3 THE STOCHASTIC DIFFERENCE EQUATION . . . . . . . . . . . . . . . . . . . . . . . . . . . 341 TABLE OF CONTENTS XIX 12.3.1 STOCHASTIC DIFFERENCE IN TIME: DEFINITION . . . . . . . . . . . . . . . . . 341 12.3.2 A STOCHASTIC MODEL FOR A TRAJECTORY . . . . . . . . . . . . . . . . . . . . . 345 12.3.3 STABILIZING* LONG TIME TRAJECTORIES, OR FILTERING HIGH FREQUENCY MODES . . . . . . . . . . . . . . . . . . . . . . 347 12.3.4 WEIGHTS OF TRAJECTORIES AND SAMPLING PROCEDURES . . . . . . . . . 350 12.3.5 MEAN FIELD APPROACH, FAST EQUILIBRATION AND MOLECULAR LABELING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353 12.3.6 STOCHASTIC DIFFERENCE IN LENGTH . . . . . . . . . . . . . . . . . . . . . . . . . 355 12.3.7 FRACTAL REFINEMENT OF TRAJECTORIES PARAMETERIZED BY LENGTH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358 12.4 NUMERICAL EXPERIMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 360 12.5 CONCLUDING REMARKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363 13NUMERICAL SIMULATIONS OF MOLECULAR SYSTEMS WITH LONG RANGE INTERACTIONS DOMINIQUE LEVESQUE ............................................ 367 13.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367 13.2 3-D SYSTEMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367 13.3 CONFINED SYSTEMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373 13.4 CONCLUSION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 PART IX PERPECTIVES IN AB INITIO MD 14 NEW DEVELOPMENTS IN PLANE-WAVE BASED AB INITIO CALCULATIONS GLENN J. MARTYNA, MARK E. TUCKERMAN ............................ 381 14.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381 14.2 METHODS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 382 14.2.1 CLUSTERS, SURFACES AND SOLIDS/LIQUIDS . . . . . . . . . . . . . . . . . . . . 382 14.2.1.1 SOLIDS/LIQUIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383 14.2.1.2 CLUSTERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384 14.2.1.3 SURFACES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 386 14.2.1.4 WIRES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 388 14.2.1.5 SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389 14.2.1.6 APPLICATION TO EWALD SUMMATION . . . . . . . . . . . . . . . . 390 14.2.1.7 APPLICATION TO PLANE-WAVE BASED DENSITY FUNCTIONAL THEORY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391 14.2.2 DUAL LENGTH SCALE APPROACH . . . . . . . . . . . . . . . . . . . . . . . . . . . 392 14.3 RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399 14.3.1 CLUSTERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 400 14.3.1.1 HARTREE AND LOCAL PSEUDOPOTENTIAL ENERGIES FOR A MODEL DENSITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . 400 XX TABLE OF CONTENTS 14.3.1.2 WATER MOLECULE AND HYDRONIUM ION . . . . . . . . . . . . . . 400 14.3.2 SURFACE EWALD SUMMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 14.3.2.1 MODEL BCC SURFACE . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401 14.3.2.2 ICE SURFACE WITH A DEFECT . . . . . . . . . . . . . . . . . . . . . . . 403 14.3.3 MIXED AB INITIO /EMPIRICAL FORCE FIELDS . . . . . . . . . . . . . . . . . . 405 14.3.3.1 NEAT WATER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 405 14.3.3.2 HCA II IN WATER. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 407 14.4 CONCLUSION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 410 15 TIME AND LENGTH SCALES IN AB INITIO MOLECULAR DYNAMICS URSULA R¨ OTHLISBERGER, MICHIEL SPRIK, J¨ URG HUTTER .................... 413 15.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 413 15.2 OVERCOMING THE TIME SCALE BARRIER: ENHANCED SAMPLING TECHNIQUES FOR AB INITIO MOLECULAR DYNAMICS SIMULATIONS . . . . . . . . 414 15.2.1 TIME SCALE LIMITATIONS IN AB INITIO MOLECULAR DYNAMICS SIMULATIONS . . . . . . . . . . . . . 414 15.2.2 THE USE OF CLASSICAL FORCE FIELDS AS BIAS POTENTIALS FOR AN ENHANCED SAMPLING OF CONFORMATIONAL TRANSITIONS . . 415 15.2.3 FINITE ELECTRONIC TEMPERATURES AS ELECTRONIC BIAS POTENTIALS . . . . . . . . . . . . . . . . . . . . . . . . . . . 417 15.3 COMPUTATION OF ACID DISSOCIATION CONSTANTS . . . . . . . . . . . . . . . . . . 419 15.3.1 TIME AND LENGTH SCALES IN AQUEOUS CHEMISTRY . . . . . . . . . . 419 15.3.2 DETERMINATION OF FREE ENERGY PROFILES . . . . . . . . . . . . . . . . . . . 420 15.3.3 STATISTICAL THERMODYNAMICS OF GAS-PHASE EQUILIBRIA . . . . . . 421 15.3.4 REVERSIBLE WORK AND EQUILIBRIUM CONSTANTS . . . . . . . . . . . . . 422 15.3.5 CONTROLLED DISSOCIATION IN A SMALL BOX . . . . . . . . . . . . . . . . . . 424 15.3.6 COMPUTATION OF THE WATER DISSOCIATION CONSTANT . . . . . . . . . 425 15.3.7 APPLICATION TO WEAK ACIDS AND EVALUATION OF METHOD . . . . . 427 15.4 LINEAR SCALING ELECTRONIC STRUCTURE METHODS FOR AB INITIO MOLECULAR DYNAMICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . 428 15.4.1 KOHNSHAM MATRIX CALCULATION . . . . . . . . . . . . . . . . . . . . . . . . 429 15.4.2 WAVEFUNCTION OPTIMIZATION; SOLVING THE KOHNSHAM EQUATIONS . . . . . . . . . . . . . . . . . . . . . . 434 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 440 PART X QUANTUM SIMULATIONS 16 A STATISTICAL MECHANICAL THEORY OF QUANTUM DYNAMICS IN CLASSICAL ENVIRONMENTS RAYMOND KAPRAL, GIOVANNI CICCOTTI ............................... 445 16.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 445 16.2 QUANTUM DYNAMICS AND STATISTICAL MECHANICS . . . . . . . . . . . . . . . . . 446 TABLE OF CONTENTS XXI 16.2.1 MIXED REPRESENTATION OF QUANTUM STATISTICAL MECHANICS . . . 448 16.3 QUANTUM-CLASSICAL WORLD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451 16.4 NATURE OF QUANTUM-CLASSICAL DYNAMICS . . . . . . . . . . . . . . . . . . . . . . . 453 16.5 TIME EVOLUTION OF DYNAMICAL VARIABLES . . . . . . . . . . . . . . . . . . . . . . . 458 16.5.1 EQUATIONS FOR CANONICAL VARIABLES . . . . . . . . . . . . . . . . . . . . . . . 461 16.6 QUANTUM-CLASSICAL EQUILIBRIUM DENSITY . . . . . . . . . . . . . . . . . . . . . . . 462 16.7 QUANTUM-CLASSICAL TIME CORRELATION FUNCTIONS . . . . . . . . . . . . . . . . 463 16.8 SIMULATION SCHEMES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 467 16.8.1 SPINBOSON MODEL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 468 16.9 CONCLUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 470 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471 17 THE COUPLED ELECTRONICIONIC MONTE CARLO SIMULATION METHOD DAVID CEPERLEY, MARK DEWING, CARLO PIERLEONI ...................... 473 17.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 473 17.2 THE COUPLED ELECTRONIC-IONIC MONTE CARLO METHOD . . . . . . . . . . . . . 476 17.3 THE PENALTY METHOD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 477 17.4 ENERGY DIFFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 478 17.4.1 DIRECT DIFFERENCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 17.4.2 REWEIGHTING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 479 17.4.3 IMPORTANCE SAMPLING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 480 17.5 CHOICE OF TRIAL WAVE FUNCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 480 17.6 TWIST AVERAGE BOUNDARY CONDITIONS . . . . . . . . . . . . . . . . . . . . . . . . . . 482 17.7 FLUID MOLECULAR HYDROGEN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483 17.8 THE ATOMICMETALLIC PHASE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 486 17.8.1 TRIAL WAVE FUNCTION AND OPTIMIZATION . . . . . . . . . . . . . . . . . . 486 17.8.2 COMPARISON WITH PIMC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 491 17.8.3 HYDROGEN EQUATION OF STATE AND SOLIDLIQUID PHASE TRANSITION OF THE PROTONS . . . . . . . . . 494 17.9 CONCLUSIONS AND OUTLOOK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499
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genre	(DE-588)1071861417 Konferenzschrift 2002 Konstanz gnd-content
genre_facet	Konferenzschrift 2002 Konstanz
id	DE-604.BV014811653
illustrated	Illustrated
indexdate	2024-07-09T19:07:28Z
institution	BVB
isbn	3540443177
language	English
oai_aleph_id	oai:aleph.bib-bvb.de:BVB01-010022256
oclc_num	50810614
open_access_boolean
owner	DE-355 DE-BY-UBR DE-19 DE-BY-UBM DE-384 DE-703 DE-11
owner_facet	DE-355 DE-BY-UBR DE-19 DE-BY-UBM DE-384 DE-703 DE-11
physical	XXVI, 500 S. Ill., graph. Darst.
publishDate	2002
publishDateSearch	2002
publishDateSort	2002
publisher	Springer
record_format	marc
series	Lecture notes in physics
series2	Lecture notes in physics
spelling	Bridging time scales molecular simulations for the next decade P. Nielaba ... (eds.) Berlin [u.a.] Springer 2002 XXVI, 500 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Lecture notes in physics 605 Física larpcal Chemistry, Physical and theoretical -- Computer simulation Chemistry, Physical and theoretical Computer simulation Molecular dynamics -- Computer simulation Molecular dynamics Computer simulation Molecules -- Computer simulation Molecules Computer simulation Proteinfaltung (DE-588)4324567-5 gnd rswk-swf Statistische Physik (DE-588)4057000-9 gnd rswk-swf Kondensierte Materie (DE-588)4132810-3 gnd rswk-swf Molekulardynamik (DE-588)4170370-4 gnd rswk-swf Monte-Carlo-Simulation (DE-588)4240945-7 gnd rswk-swf (DE-588)1071861417 Konferenzschrift 2002 Konstanz gnd-content Proteinfaltung (DE-588)4324567-5 s Molekulardynamik (DE-588)4170370-4 s Monte-Carlo-Simulation (DE-588)4240945-7 s DE-604 Statistische Physik (DE-588)4057000-9 s Kondensierte Materie (DE-588)4132810-3 s Nielaba, Peter Sonstige oth Lecture notes in physics 605 (DE-604)BV000003166 605 SWB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010022256&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis
spellingShingle	Bridging time scales molecular simulations for the next decade Lecture notes in physics Física larpcal Chemistry, Physical and theoretical -- Computer simulation Chemistry, Physical and theoretical Computer simulation Molecular dynamics -- Computer simulation Molecular dynamics Computer simulation Molecules -- Computer simulation Molecules Computer simulation Proteinfaltung (DE-588)4324567-5 gnd Statistische Physik (DE-588)4057000-9 gnd Kondensierte Materie (DE-588)4132810-3 gnd Molekulardynamik (DE-588)4170370-4 gnd Monte-Carlo-Simulation (DE-588)4240945-7 gnd
subject_GND	(DE-588)4324567-5 (DE-588)4057000-9 (DE-588)4132810-3 (DE-588)4170370-4 (DE-588)4240945-7 (DE-588)1071861417
title	Bridging time scales molecular simulations for the next decade
title_auth	Bridging time scales molecular simulations for the next decade
title_exact_search	Bridging time scales molecular simulations for the next decade
title_full	Bridging time scales molecular simulations for the next decade P. Nielaba ... (eds.)
title_fullStr	Bridging time scales molecular simulations for the next decade P. Nielaba ... (eds.)
title_full_unstemmed	Bridging time scales molecular simulations for the next decade P. Nielaba ... (eds.)
title_short	Bridging time scales
title_sort	bridging time scales molecular simulations for the next decade
title_sub	molecular simulations for the next decade
topic	Física larpcal Chemistry, Physical and theoretical -- Computer simulation Chemistry, Physical and theoretical Computer simulation Molecular dynamics -- Computer simulation Molecular dynamics Computer simulation Molecules -- Computer simulation Molecules Computer simulation Proteinfaltung (DE-588)4324567-5 gnd Statistische Physik (DE-588)4057000-9 gnd Kondensierte Materie (DE-588)4132810-3 gnd Molekulardynamik (DE-588)4170370-4 gnd Monte-Carlo-Simulation (DE-588)4240945-7 gnd
topic_facet	Física Chemistry, Physical and theoretical -- Computer simulation Chemistry, Physical and theoretical Computer simulation Molecular dynamics -- Computer simulation Molecular dynamics Computer simulation Molecules -- Computer simulation Molecules Computer simulation Proteinfaltung Statistische Physik Kondensierte Materie Molekulardynamik Monte-Carlo-Simulation Konferenzschrift 2002 Konstanz
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010022256&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
volume_link	(DE-604)BV000003166
work_keys_str_mv	AT nielabapeter bridgingtimescalesmolecularsimulationsforthenextdecade

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