Aspects of nonautonomous molecular dynamics

Size: px
Start display at page:

Download "Aspects of nonautonomous molecular dynamics"

Transcription

1 Aspects of nonautonomous molecular dynamics IMA, University of Minnesota, Minneapolis January 28, 2007 Michel Cuendet Swiss Institute of Bioinformatics, Lausanne, Switzerland

2 Introduction to the Jarzynski identity Forced unfolding of 8-alanine peptide Usual thermodynamics : Jarzynski identity Xiong et al., Theor. Chem. Acc. 116 : 338 (2006) C. Jarzynski, Phys. Rev. Lett. 78, 2690 (1997). 2

3 Some quantities of interest Free energy difference between states and : Work performed to bring the system from to in time : Dissipation function : roughly such that is the entropy production. Usually : according to second law. 3

4 Nonequilibrium relations One way Equilibrium Zwanzig (1954) Work from state A to B Jarzynski (1997) Dissipation Kawazaki identity (1995) Two ways Bennett (1976) Crooks (1999) Fluctuation theo. (1993) R. W. Zwanzig, J. Chem. Phys 22, 1420 (1954). C. H. Bennett, J. Comp. Phys 22, 245 (1976). C. Jarzynski, Phys. Rev. Lett. 78, 2690 (1997). G. E. Crooks, Phys. Rev. E 60, 2721 (1999). D. J. Evans and D. J. Searles, Phys. Rev. E 52, 5839 (1995). D. J. Evans, E. G. D. Cohen, and G. P. Morriss, Phys. Rev. Lett. 71, 2401 (1993). 4

5 Experimental Crooks 5

6 Nonautonomous thermostated MD Exploring slow reactions : drive the system system W ext integrator Heat bath : ΔF = W ext + W MD cutoffs Absorb excess heat + Q - TΔS W MD SHAKE Enforce right distribution twin-range - Q Symmetry breaking between time-reversible mechanics and irreversible thermodynamics* Thermostats as artificial heat baths : NOT the thermodynamic picture! Abstract heat bath replaced by few degrees of freedom Strongly coupled dynamics thermostat T 0 steady state : - Q = W ext + W MD Phase space compression / entropy production * W. G. Hoover, «Time Reversibility, Computer Simulation and Chaos», World Sientific,

7 The Nosé-Hoover Thermostat Extended phase space EQUILIBRIUM physical variables NON-HAMILTONIAN Reproduces the canonical distribution : Conserved quantity : This is valid only with a correct discretization scheme (integrator). Time reversible Conserves pseudo-energy Preserves phase space volume Hoover, Phys. Rev. A 31 (1985),

8 Is the Jarzynski identity valid for thermostated MD? NVT ensemble F MD N particles Try to use Jarzynski Jarzynski, Phys. Rev. Lett. 14 (1997),

9 Free energy protocol Switch such that system Thermostat T 0 System energy change : NH dynamics The work is path-dependent : No variable is coupled to Jarzynski, J. Stat. Mech. : Theor. Exp. (2004) P

10 Formalism of Tuckerman et al. Invariant phase space measure : NH dynamics Metric factor : Invariant : Partition function for an isolated system : In the nonequilibrium case, also an invariant : * Tuckerman et al., JCP 115 (2001),

11 Little proof of the Jarzynski identity Variable change Use invariant and metric factor Integrate on The Jarzynski identity!!! Cuendet, Phys. Rev. Lett. 12 : (2006) 11

12 Generalizations Nosé-Hoover chain thermostat Constant pressure ensemble, via volume coupling Generalized Nosé-Hoover with generic coupling terms define : - conserved quantity - Metric factor : Bulgac and Kusnezov, Phys. Rev. A 8 (1990),

13 Generalization 2 : Hamiltonian thermostats Generalized time-dependent Nosé thermostat : Hamiltonian equations of motion integrated with respect to Laird and Leimkuhler, Phys. Rev. E 68 : (2003) Poincaré mapping : Any nonautonomous( ) Hamiltonian can be mapped to an autonomous( ) extended Hamiltonian Zare and Szebehely, Cel. Mech. 11 : 469 (1975) Struckmeier, J. Phys. A 38 : 1257 (2005) integrated with respect to Generalized Nosé-Poincaré thermostat! Bond et al., Comp. Phys. 151 : 114 (1999) Dettmann, Morriss, Phys. Rev. E 55 : 3693 (1997) Similar Jarzynski derivation with : Cuendet, J. Chem. Phys. 125 : (2006) 13

14 The JI as a property of the dynamics No need of hypotheses such as : Infinite number of particles Equivalence of microcanonical and canonical ensembles Infinite heat bath Weak or idealized coupling A priori canonical ensemble BUT : Generality loss : specific to the dynamics considered Relies only on properties of the thermostat: Inspired by this, Procacci et al. recently proved the Crooks theorem for thermostated dynamics: Procacci et al, J. Chem. Phys 125 : (2006) 14

15 Requirements for the dynamics Non-Ham. Ham. - Conserved quantity with a term linear in - Metric factor. - Representation where other variables are independent of NH dynamics Generalized Nosé-Poincaré 15

16 Unexpected Robustness Drift in Pseudo-energy : 320 kj/mol in 140 ps (!) Model the energy drift : Redo the Jarzynski proof : 16

17 Unexpected Robustness Steering potential = probe on only one degree of freedom. Drift per degree of freedom : 0.05 kj/mol (140ps) The free energy characterizes the whole system Convergence for "far" degrees of freedom out of reach 17

18 Outlook Improving MD sampling accuracy (calorimetric) Experiments time-resolved single molecule Nonequilibrium theory Jarzynski Kawazaki identity Crooks Fluctuation theo. 18

19 Usual Leap-frog : Leap-frog and Temperature Which squared velocity at step n? Squared velocity up to order 2 : 19

20 Leap-frog and Temperature 20

21 Thanks for your attention! Acknowledgments : Olivier Michielin Wilfred van Gunsteren Giovanni Ciccotti Chris Jarzynski Ben Leimkuhler 21

Javier Junquera. Statistical mechanics

Javier Junquera. Statistical mechanics Javier Junquera Statistical mechanics From the microscopic to the macroscopic level: the realm of statistical mechanics Computer simulations Thermodynamic state Generates information at the microscopic

More information

Entropy production fluctuation theorem and the nonequilibrium work relation for free energy differences

Entropy production fluctuation theorem and the nonequilibrium work relation for free energy differences PHYSICAL REVIEW E VOLUME 60, NUMBER 3 SEPTEMBER 1999 Entropy production fluctuation theorem and the nonequilibrium work relation for free energy differences Gavin E. Crooks* Department of Chemistry, University

More information

Dissipation and the Relaxation to Equilibrium

Dissipation and the Relaxation to Equilibrium 1 Dissipation and the Relaxation to Equilibrium Denis J. Evans, 1 Debra J. Searles 2 and Stephen R. Williams 1 1 Research School of Chemistry, Australian National University, Canberra, ACT 0200, Australia

More information

Nonequilibrium thermodynamics at the microscale

Nonequilibrium thermodynamics at the microscale Nonequilibrium thermodynamics at the microscale Christopher Jarzynski Department of Chemistry and Biochemistry and Institute for Physical Science and Technology ~1 m ~20 nm Work and free energy: a macroscopic

More information

Fluctuation theorems. Proseminar in theoretical physics Vincent Beaud ETH Zürich May 11th 2009

Fluctuation theorems. Proseminar in theoretical physics Vincent Beaud ETH Zürich May 11th 2009 Fluctuation theorems Proseminar in theoretical physics Vincent Beaud ETH Zürich May 11th 2009 Outline Introduction Equilibrium systems Theoretical background Non-equilibrium systems Fluctuations and small

More information

The Jarzynski Equation and the Fluctuation Theorem

The Jarzynski Equation and the Fluctuation Theorem The Jarzynski Equation and the Fluctuation Theorem Kirill Glavatskiy Trial lecture for PhD degree 24 September, NTNU, Trondheim The Jarzynski equation and the fluctuation theorem Fundamental concepts Statiscical

More information

MD Thermodynamics. Lecture 12 3/26/18. Harvard SEAS AP 275 Atomistic Modeling of Materials Boris Kozinsky

MD Thermodynamics. Lecture 12 3/26/18. Harvard SEAS AP 275 Atomistic Modeling of Materials Boris Kozinsky MD Thermodynamics Lecture 1 3/6/18 1 Molecular dynamics The force depends on positions only (not velocities) Total energy is conserved (micro canonical evolution) Newton s equations of motion (second order

More information

On the Asymptotic Convergence. of the Transient and Steady State Fluctuation Theorems. Gary Ayton and Denis J. Evans. Research School Of Chemistry

On the Asymptotic Convergence. of the Transient and Steady State Fluctuation Theorems. Gary Ayton and Denis J. Evans. Research School Of Chemistry 1 On the Asymptotic Convergence of the Transient and Steady State Fluctuation Theorems. Gary Ayton and Denis J. Evans Research School Of Chemistry Australian National University Canberra, ACT 0200 Australia

More information

arxiv: v2 [cond-mat.stat-mech] 16 Mar 2012

arxiv: v2 [cond-mat.stat-mech] 16 Mar 2012 arxiv:119.658v2 cond-mat.stat-mech] 16 Mar 212 Fluctuation theorems in presence of information gain and feedback Sourabh Lahiri 1, Shubhashis Rana 2 and A. M. Jayannavar 3 Institute of Physics, Bhubaneswar

More information

Statistical Mechanics of Nonequilibrium Liquids

Statistical Mechanics of Nonequilibrium Liquids 1. Introduction Mechanics provides a complete microscopic description of the state of a system. When the equations of motion are combined with initial conditions and boundary conditions, the subsequent

More information

Approach to Thermal Equilibrium in Biomolecular

Approach to Thermal Equilibrium in Biomolecular Approach to Thermal Equilibrium in Biomolecular Simulation Eric Barth 1, Ben Leimkuhler 2, and Chris Sweet 2 1 Department of Mathematics Kalamazoo College Kalamazoo, Michigan, USA 49006 2 Centre for Mathematical

More information

Mathematical Structures of Statistical Mechanics: from equilibrium to nonequilibrium and beyond Hao Ge

Mathematical Structures of Statistical Mechanics: from equilibrium to nonequilibrium and beyond Hao Ge Mathematical Structures of Statistical Mechanics: from equilibrium to nonequilibrium and beyond Hao Ge Beijing International Center for Mathematical Research and Biodynamic Optical Imaging Center Peking

More information

Universities of Leeds, Sheffield and York

Universities of Leeds, Sheffield and York promoting access to White Rose research papers Universities of Leeds, Sheffield and York http://eprints.whiterose.ac.uk/ This is an author produced version of a paper published in The Journal of Chemical

More information

Optimal quantum driving of a thermal machine

Optimal quantum driving of a thermal machine Optimal quantum driving of a thermal machine Andrea Mari Vasco Cavina Vittorio Giovannetti Alberto Carlini Workshop on Quantum Science and Quantum Technologies ICTP, Trieste, 12-09-2017 Outline 1. Slow

More information

7 To solve numerically the equation of motion, we use the velocity Verlet or leap frog algorithm. _ V i n = F i n m i (F.5) For time step, we approxim

7 To solve numerically the equation of motion, we use the velocity Verlet or leap frog algorithm. _ V i n = F i n m i (F.5) For time step, we approxim 69 Appendix F Molecular Dynamics F. Introduction In this chapter, we deal with the theories and techniques used in molecular dynamics simulation. The fundamental dynamics equations of any system is the

More information

Introduction to Fluctuation Theorems

Introduction to Fluctuation Theorems Hyunggyu Park Introduction to Fluctuation Theorems 1. Nonequilibrium processes 2. Brief History of Fluctuation theorems 3. Jarzynski equality & Crooks FT 4. Experiments 5. Probability theory viewpoint

More information

4. The Green Kubo Relations

4. The Green Kubo Relations 4. The Green Kubo Relations 4.1 The Langevin Equation In 1828 the botanist Robert Brown observed the motion of pollen grains suspended in a fluid. Although the system was allowed to come to equilibrium,

More information

Nosé-Hoover chain method for nonequilibrium molecular dynamics simulation

Nosé-Hoover chain method for nonequilibrium molecular dynamics simulation PHYSICAL REVIEW E VOLUME 61, NUMBER 5 MAY 000 Nosé-Hoover chain method for nonequilibrium molecular dynamics simulation A. C. Brańka Institute of Molecular Physics, Polish Academy of Sciences, Smoluchowskiego

More information

A PROJECTIVE THERMOSTATTING DYNAMICS TECHNIQUE

A PROJECTIVE THERMOSTATTING DYNAMICS TECHNIQUE A PROJECTIVE THERMOSTATTING DYNAMICS TECHNIQUE ZHIDONG JIA AND BENEDICT J. LEIMKUHLER Abstract. A dynamical framework is developed with several variations for modeling multiple timescale molecular dynamics

More information

Understanding Molecular Simulation 2009 Monte Carlo and Molecular Dynamics in different ensembles. Srikanth Sastry

Understanding Molecular Simulation 2009 Monte Carlo and Molecular Dynamics in different ensembles. Srikanth Sastry JNCASR August 20, 21 2009 Understanding Molecular Simulation 2009 Monte Carlo and Molecular Dynamics in different ensembles Srikanth Sastry Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore

More information

What is Classical Molecular Dynamics?

What is Classical Molecular Dynamics? What is Classical Molecular Dynamics? Simulation of explicit particles (atoms, ions,... ) Particles interact via relatively simple analytical potential functions Newton s equations of motion are integrated

More information

(# = %(& )(* +,(- Closed system, well-defined energy (or e.g. E± E/2): Microcanonical ensemble

(# = %(& )(* +,(- Closed system, well-defined energy (or e.g. E± E/2): Microcanonical ensemble Recall from before: Internal energy (or Entropy): &, *, - (# = %(& )(* +,(- Closed system, well-defined energy (or e.g. E± E/2): Microcanonical ensemble & = /01Ω maximized Ω: fundamental statistical quantity

More information

Introduction to Stochastic Thermodynamics: Application to Thermo- and Photo-electricity in small devices

Introduction to Stochastic Thermodynamics: Application to Thermo- and Photo-electricity in small devices Université Libre de Bruxelles Center for Nonlinear Phenomena and Complex Systems Introduction to Stochastic Thermodynamics: Application to Thermo- and Photo-electricity in small devices Massimiliano Esposito

More information

Non-equilibrium phenomena and fluctuation relations

Non-equilibrium phenomena and fluctuation relations Non-equilibrium phenomena and fluctuation relations Lamberto Rondoni Politecnico di Torino Beijing 16 March 2012 http://www.rarenoise.lnl.infn.it/ Outline 1 Background: Local Thermodyamic Equilibrium 2

More information

Optimal Thermodynamic Control and the Riemannian Geometry of Ising magnets

Optimal Thermodynamic Control and the Riemannian Geometry of Ising magnets Optimal Thermodynamic Control and the Riemannian Geometry of Ising magnets Gavin Crooks Lawrence Berkeley National Lab Funding: Citizens Like You! MURI threeplusone.com PRE 92, 060102(R) (2015) NSF, DOE

More information

Temperature and Pressure Controls

Temperature and Pressure Controls Ensembles Temperature and Pressure Controls 1. (E, V, N) microcanonical (constant energy) 2. (T, V, N) canonical, constant volume 3. (T, P N) constant pressure 4. (T, V, µ) grand canonical #2, 3 or 4 are

More information

Free energy calculations and the potential of mean force

Free energy calculations and the potential of mean force Free energy calculations and the potential of mean force IMA Workshop on Classical and Quantum Approaches in Molecular Modeling Mark Tuckerman Dept. of Chemistry and Courant Institute of Mathematical Science

More information

Fluctuations in Small Systems the case of single molecule experiments

Fluctuations in Small Systems the case of single molecule experiments Fluctuations in Small Systems the case of single molecule experiments Fabio Marchesoni, Università di Camerino, Italy Perugia, Aug. 2 nd, 2011 force distance k B T >> quantum scale I do not believe a word

More information

Supporting Information for Solid-liquid Thermal Transport and its Relationship with Wettability and the Interfacial Liquid Structure

Supporting Information for Solid-liquid Thermal Transport and its Relationship with Wettability and the Interfacial Liquid Structure Supporting Information for Solid-liquid Thermal Transport and its Relationship with Wettability and the Interfacial Liquid Structure Bladimir Ramos-Alvarado, Satish Kumar, and G. P. Peterson The George

More information

Numerical study of the steady state fluctuation relations far from equilibrium

Numerical study of the steady state fluctuation relations far from equilibrium Numerical study of the steady state fluctuation relations far from equilibrium Stephen R. Williams, Debra J. Searles, and Denis J. Evans Citation: The Journal of Chemical Physics 124, 194102 (2006); doi:

More information

Molecular Dynamics Simulations. Dr. Noelia Faginas Lago Dipartimento di Chimica,Biologia e Biotecnologie Università di Perugia

Molecular Dynamics Simulations. Dr. Noelia Faginas Lago Dipartimento di Chimica,Biologia e Biotecnologie Università di Perugia Molecular Dynamics Simulations Dr. Noelia Faginas Lago Dipartimento di Chimica,Biologia e Biotecnologie Università di Perugia 1 An Introduction to Molecular Dynamics Simulations Macroscopic properties

More information

Towards a computational chemical potential for nonequilibrium steady-state systems

Towards a computational chemical potential for nonequilibrium steady-state systems PHYSICAL REVIEW E VOLUME 60, NUMBER 5 NOVEMBER 1999 Towards a computational chemical potential for nonequilibrium steady-state systems András Baranyai Department of Theoretical Chemistry, Eötvös University,

More information

Gear methods I + 1/18

Gear methods I + 1/18 Gear methods I + 1/18 Predictor-corrector type: knowledge of history is used to predict an approximate solution, which is made more accurate in the following step we do not want (otherwise good) methods

More information

Temperature and Pressure Controls

Temperature and Pressure Controls Ensembles Temperature and Pressure Controls 1. (E, V, N) microcanonical (constant energy) 2. (T, V, N) canonical, constant volume 3. (T, P N) constant pressure 4. (T, V, µ) grand canonical #2, 3 or 4 are

More information

Classical Molecular Dynamics

Classical Molecular Dynamics Classical Molecular Dynamics Matt Probert Condensed Matter Dynamics Group Department of Physics, University of York, U.K. http://www-users.york.ac.uk/~mijp1 Overview of lecture n Motivation n Types of

More information

Fluctuation Theorems of Work and Entropy in Hamiltonian Systems

Fluctuation Theorems of Work and Entropy in Hamiltonian Systems Fluctuation Theorems of Work and Entropy in Hamiltonian Systems Sourabh Lahiri and Arun M Jayannavar Fluctuation theorems are a group of exact relations that remain valid irrespective of how far the system

More information

Fluctuation theorems: where do we go from here?

Fluctuation theorems: where do we go from here? Fluctuation theorems: where do we go from here? D. Lacoste Laboratoire Physico-Chimie Théorique, UMR Gulliver, ESPCI, Paris Outline of the talk 1. Fluctuation theorems for systems out of equilibrium 2.

More information

1. Thermodynamics 1.1. A macroscopic view of matter

1. Thermodynamics 1.1. A macroscopic view of matter 1. Thermodynamics 1.1. A macroscopic view of matter Intensive: independent of the amount of substance, e.g. temperature,pressure. Extensive: depends on the amount of substance, e.g. internal energy, enthalpy.

More information

Fluctuation relations and nonequilibrium thermodynamics II

Fluctuation relations and nonequilibrium thermodynamics II Fluctuations II p. 1/31 Fluctuation relations and nonequilibrium thermodynamics II Alberto Imparato and Luca Peliti Dipartimento di Fisica, Unità CNISM and Sezione INFN Politecnico di Torino, Torino (Italy)

More information

Molecular Dynamics at Constant Pressure: Allowing the System to Control Volume Fluctuations via a Shell Particle

Molecular Dynamics at Constant Pressure: Allowing the System to Control Volume Fluctuations via a Shell Particle Entropy 2013, 15, 3941-3969; doi:10.3390/e15093941 Review OPEN ACCESS entropy ISSN 1099-4300 www.mdpi.com/journal/entropy Molecular Dynamics at Constant Pressure: Allowing the System to Control Volume

More information

Free energy calculations using molecular dynamics simulations. Anna Johansson

Free energy calculations using molecular dynamics simulations. Anna Johansson Free energy calculations using molecular dynamics simulations Anna Johansson 2007-03-13 Outline Introduction to concepts Why is free energy important? Calculating free energy using MD Thermodynamical Integration

More information

Free energy calculations

Free energy calculations Free energy calculations Berk Hess May 5, 2017 Why do free energy calculations? The free energy G gives the population of states: ( ) P 1 G = exp, G = G 2 G 1 P 2 k B T Since we mostly simulate in the

More information

Free energy simulations

Free energy simulations Free energy simulations Marcus Elstner and Tomáš Kubař January 14, 2013 Motivation a physical quantity that is of most interest in chemistry? free energies Helmholtz F or Gibbs G holy grail of computational

More information

A potential of mean force estimator based on nonequilibrium work exponential averages

A potential of mean force estimator based on nonequilibrium work exponential averages PAPER www.rsc.org/pccp Physical Chemistry Chemical Physics A potential of mean force estimator based on nonequilibrium work exponential averages Riccardo Chelli* ab and Piero Procacci ab Received 26th

More information

The Kawasaki Identity and the Fluctuation Theorem

The Kawasaki Identity and the Fluctuation Theorem Chapter 6 The Kawasaki Identity and the Fluctuation Theorem This chapter describes the Kawasaki function, exp( Ω t ), and shows that the Kawasaki function follows an identity when the Fluctuation Theorem

More information

A Nobel Prize for Molecular Dynamics and QM/MM What is Classical Molecular Dynamics? Simulation of explicit particles (atoms, ions,... ) Particles interact via relatively simple analytical potential

More information

Thermodynamics and Equilibrium. Chemical thermodynamics is concerned with energy relationships in chemical reactions.

Thermodynamics and Equilibrium. Chemical thermodynamics is concerned with energy relationships in chemical reactions. 1 of 7 Thermodynamics and Equilibrium Chemical thermodynamics is concerned with energy relationships in chemical reactions. In addition to enthalpy (H), we must consider the change in randomness or disorder

More information

Lecture 6 non-equilibrium statistical mechanics (part 2) 1 Derivations of hydrodynamic behaviour

Lecture 6 non-equilibrium statistical mechanics (part 2) 1 Derivations of hydrodynamic behaviour Lecture 6 non-equilibrium statistical mechanics (part 2) I will outline two areas in which there has been a lot of work in the past 2-3 decades 1 Derivations of hydrodynamic behaviour 1.1 Independent random

More information

Computational Chemistry - MD Simulations

Computational Chemistry - MD Simulations Computational Chemistry - MD Simulations P. Ojeda-May pedro.ojeda-may@umu.se Department of Chemistry/HPC2N, Umeå University, 901 87, Sweden. May 2, 2017 Table of contents 1 Basics on MD simulations Accelerated

More information

Collective Effects. Equilibrium and Nonequilibrium Physics

Collective Effects. Equilibrium and Nonequilibrium Physics 1 Collective Effects in Equilibrium and Nonequilibrium Physics: Lecture 2, 24 March 2006 1 Collective Effects in Equilibrium and Nonequilibrium Physics Website: http://cncs.bnu.edu.cn/mccross/course/ Caltech

More information

2 Lyapunov Exponent exponent number. Lyapunov spectrum for colour conductivity of 8 WCA disks.

2 Lyapunov Exponent exponent number. Lyapunov spectrum for colour conductivity of 8 WCA disks. 3 2 Lyapunov Exponent 1-1 -2-3 5 1 15 exponent number Lyapunov spectrum for colour conductivity of 8 WCA disks. 2 3 Lyapunov exponent 2 1-1 -2-3 5 1 15 exponent number Lyapunov spectrum for shear flow

More information

Free energy recovery in single molecule experiments

Free energy recovery in single molecule experiments Supplementary Material Free energy recovery in single molecule experiments Single molecule force measurements (experimental setup shown in Fig. S1) can be used to determine free-energy differences between

More information

Energy Fluctuations in Thermally Isolated Driven System

Energy Fluctuations in Thermally Isolated Driven System nergy Fluctuations in Thermally Isolated Driven System Yariv Kafri (Technion) with Guy Bunin (Technion), Luca D Alessio (Boston University) and Anatoli Polkovnikov (Boston University) arxiv:1102.1735 Nature

More information

arxiv:physics/ v2 [physics.class-ph] 18 Dec 2006

arxiv:physics/ v2 [physics.class-ph] 18 Dec 2006 Fluctuation theorem for entropy production during effusion of an ideal gas with momentum transfer arxiv:physics/061167v [physicsclass-ph] 18 Dec 006 Kevin Wood 1 C Van den roeck 3 R Kawai 4 and Katja Lindenberg

More information

Comparative study on methodology in molecular dynamics simulation of nucleation

Comparative study on methodology in molecular dynamics simulation of nucleation THE JOURNAL OF CHEMICAL PHYSICS 126, 224517 2007 Comparative study on methodology in molecular dynamics simulation of nucleation Jan Julin, Ismo Napari, and Hanna Vehkamäki Department of Physical Sciences,

More information

Free Energy Estimation in Simulations

Free Energy Estimation in Simulations Physics 363/MatSE 38/ CSE 36 Free Energy Estimation in Simulations This is a brief overview of free energy estimation, much of which can be found in the article by D. Frenkel Free-Energy Computation and

More information

APMA 2811T. By Zhen Li. Today s topic: Lecture 2: Theoretical foundation and parameterization. Sep. 15, 2016

APMA 2811T. By Zhen Li. Today s topic: Lecture 2: Theoretical foundation and parameterization. Sep. 15, 2016 Today s topic: APMA 2811T Dissipative Particle Dynamics Instructor: Professor George Karniadakis Location: 170 Hope Street, Room 118 Time: Thursday 12:00pm 2:00pm Dissipative Particle Dynamics: Foundation,

More information

Energy and Forces in DFT

Energy and Forces in DFT Energy and Forces in DFT Total Energy as a function of nuclear positions {R} E tot ({R}) = E DF T ({R}) + E II ({R}) (1) where E DF T ({R}) = DFT energy calculated for the ground-state density charge-density

More information

The physics of information: from Maxwell s demon to Landauer. Eric Lutz University of Erlangen-Nürnberg

The physics of information: from Maxwell s demon to Landauer. Eric Lutz University of Erlangen-Nürnberg The physics of information: from Maxwell s demon to Landauer Eric Lutz University of Erlangen-Nürnberg Outline 1 Information and physics Information gain: Maxwell and Szilard Information erasure: Landauer

More information

Entropy Production and Fluctuation Relations in NonMarkovian Systems

Entropy Production and Fluctuation Relations in NonMarkovian Systems Entropy Production and Fluctuation Relations in NonMarkovian Systems Tapio Ala-Nissilä Department of Applied Physics and COMP CoE, Aalto University School of Science (formerly Helsinki University of Technology),

More information

On the Relation Between Dissipation and the Rate of Spontaneous Entropy. Production from Linear Irreversible Thermodynamics

On the Relation Between Dissipation and the Rate of Spontaneous Entropy. Production from Linear Irreversible Thermodynamics On the Relation Between Dissipation and the Rate of Spontaneous Entropy Production from Linear Irreversible Thermodynamics Stephen R. Williams, a Debra J. Searles b and Denis J. Evans a a Research School

More information

Entropy and Free Energy in Biology

Entropy and Free Energy in Biology Entropy and Free Energy in Biology Energy vs. length from Phillips, Quake. Physics Today. 59:38-43, 2006. kt = 0.6 kcal/mol = 2.5 kj/mol = 25 mev typical protein typical cell Thermal effects = deterministic

More information

arxiv: v1 [cond-mat.stat-mech] 28 Mar 2008

arxiv: v1 [cond-mat.stat-mech] 28 Mar 2008 Canonical sampling through velocity-rescaling Giovanni Bussi, Davide Donadio, and Michele Parrinello Computational Science, Department of Chemistry and Applied Biosciences, ETH Zürich, USI Campus, Via

More information

INTRODUCTION TO MODERN THERMODYNAMICS

INTRODUCTION TO MODERN THERMODYNAMICS INTRODUCTION TO MODERN THERMODYNAMICS Dilip Kondepudi Thurman D Kitchin Professor of Chemistry Wake Forest University John Wiley & Sons, Ltd CONTENTS Preface xiii PART I THE FORMALIS1VI OF MODERN THER1VIODYNAMICS

More information

arxiv:cond-mat/ v2 [cond-mat.soft] 29 Nov 2004

arxiv:cond-mat/ v2 [cond-mat.soft] 29 Nov 2004 arxiv:cond-mat/411654v2 [cond-mat.soft] 29 Nov 24 ork probability distribution in single molecule experiments Alberto Imparato ( ) and Luca Peliti ( ) Dipartimento di Scienze Fisiche and Unità INFM, Università

More information

Collective Effects. Equilibrium and Nonequilibrium Physics

Collective Effects. Equilibrium and Nonequilibrium Physics Collective Effects in Equilibrium and Nonequilibrium Physics: Lecture 3, 3 March 2006 Collective Effects in Equilibrium and Nonequilibrium Physics Website: http://cncs.bnu.edu.cn/mccross/course/ Caltech

More information

Contents. 1 Introduction and guide for this text 1. 2 Equilibrium and entropy 6. 3 Energy and how the microscopic world works 21

Contents. 1 Introduction and guide for this text 1. 2 Equilibrium and entropy 6. 3 Energy and how the microscopic world works 21 Preface Reference tables Table A Counting and combinatorics formulae Table B Useful integrals, expansions, and approximations Table C Extensive thermodynamic potentials Table D Intensive per-particle thermodynamic

More information

Physics 562: Statistical Mechanics Spring 2002, James P. Sethna Prelim, due Wednesday, March 13 Latest revision: March 22, 2002, 10:9

Physics 562: Statistical Mechanics Spring 2002, James P. Sethna Prelim, due Wednesday, March 13 Latest revision: March 22, 2002, 10:9 Physics 562: Statistical Mechanics Spring 2002, James P. Sethna Prelim, due Wednesday, March 13 Latest revision: March 22, 2002, 10:9 Open Book Exam Work on your own for this exam. You may consult your

More information

arxiv: v1 [cond-mat.stat-mech] 7 Mar 2019

arxiv: v1 [cond-mat.stat-mech] 7 Mar 2019 Langevin thermostat for robust configurational and kinetic sampling Oded Farago, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB EW, United Kingdom Department of Biomedical

More information

Statistical properties of entropy production derived from fluctuation theorems

Statistical properties of entropy production derived from fluctuation theorems Statistical properties of entropy production derived from fluctuation theorems Neri Merhav (1) and Yariv Kafri (2) (1) Department of Electrical Engineering, Technion, Haifa 32, Israel. (2) Department of

More information

Note on the KaplanYorke Dimension and Linear Transport Coefficients

Note on the KaplanYorke Dimension and Linear Transport Coefficients Journal of Statistical Physics, Vol. 101, Nos. 12, 2000 Note on the KaplanYorke Dimension and Linear Transport Coefficients Denis J. Evans, 1 E. G. D. Cohen, 2 Debra J. Searles, 3 and F. Bonetto 4 Received

More information

Thermodynamics of nuclei in thermal contact

Thermodynamics of nuclei in thermal contact Thermodynamics of nuclei in thermal contact Karl-Heinz Schmidt, Beatriz Jurado CENBG, CNRS/IN2P3, Chemin du Solarium B.P. 120, 33175 Gradignan, France Abstract: The behaviour of a di-nuclear system in

More information

Ab initio molecular dynamics and nuclear quantum effects

Ab initio molecular dynamics and nuclear quantum effects Ab initio molecular dynamics and nuclear quantum effects Luca M. Ghiringhelli Fritz Haber Institute Hands on workshop density functional theory and beyond: First principles simulations of molecules and

More information

This Answer/Solution Example is taken from a student s actual homework report. I thank him for permission to use it here. JG

This Answer/Solution Example is taken from a student s actual homework report. I thank him for permission to use it here. JG This Answer/Solution Example is taken from a student s actual homework report. I thank him for permission to use it here. JG Chem 8021 Spring 2005 Project II Calculation of Self-Diffusion Coeffecient of

More information

Anatoli Polkovnikov Boston University

Anatoli Polkovnikov Boston University Anatoli Polkovnikov Boston University L. D Alessio BU M. Bukov BU C. De Grandi Yale V. Gritsev Amsterdam M. Kolodrubetz Berkeley C.-W. Liu BU P. Mehta BU M. Tomka BU D. Sels BU A. Sandvik BU T. Souza BU

More information

Introduction to molecular dynamics

Introduction to molecular dynamics 1 Introduction to molecular dynamics Yves Lansac Université François Rabelais, Tours, France Visiting MSE, GIST for the summer Molecular Simulation 2 Molecular simulation is a computational experiment.

More information

ON BROWNIAN COMPUTATION

ON BROWNIAN COMPUTATION ON BROWNIAN COMPUTATION JOHN D. NORTON Department of History and Philosophy of Science Center for Philosophy of Science University of Pittsburgh Pittsburgh PA USA 15260 jdnorton@pitt.edu Draft: October10,

More information

Information Thermodynamics on Causal Networks

Information Thermodynamics on Causal Networks 1/39 Information Thermodynamics on Causal Networks FSPIP 2013, July 12 2013. Sosuke Ito Dept. of Phys., the Univ. of Tokyo (In collaboration with T. Sagawa) ariv:1306.2756 The second law of thermodynamics

More information

Emergent Fluctuation Theorem for Pure Quantum States

Emergent Fluctuation Theorem for Pure Quantum States Emergent Fluctuation Theorem for Pure Quantum States Takahiro Sagawa Department of Applied Physics, The University of Tokyo 16 June 2016, YITP, Kyoto YKIS2016: Quantum Matter, Spacetime and Information

More information

Lecture 2+3: Simulations of Soft Matter. 1. Why Lecture 1 was irrelevant 2. Coarse graining 3. Phase equilibria 4. Applications

Lecture 2+3: Simulations of Soft Matter. 1. Why Lecture 1 was irrelevant 2. Coarse graining 3. Phase equilibria 4. Applications Lecture 2+3: Simulations of Soft Matter 1. Why Lecture 1 was irrelevant 2. Coarse graining 3. Phase equilibria 4. Applications D. Frenkel, Boulder, July 6, 2006 What distinguishes Colloids from atoms or

More information

From fully quantum thermodynamical identities to a second law equality

From fully quantum thermodynamical identities to a second law equality From fully quantum thermodynamical identities to a second law equality Alvaro Alhambra, Lluis Masanes, Jonathan Oppenheim, Chris Perry Fluctuating States Phys. Rev. X 6, 041016 (2016) Fluctuating Work

More information

Thermostatic Controls for Noisy Gradient Systems and Applications to Machine Learning

Thermostatic Controls for Noisy Gradient Systems and Applications to Machine Learning Thermostatic Controls for Noisy Gradient Systems and Applications to Machine Learning Ben Leimkuhler University of Edinburgh Joint work with C. Matthews (Chicago), G. Stoltz (ENPC-Paris), M. Tretyakov

More information

Fluctuations of intensive variables and non-equivalence of thermodynamic ensembles

Fluctuations of intensive variables and non-equivalence of thermodynamic ensembles Fluctuations of intensive variables and non-equivalence of thermodynamic ensembles A. Ya. Shul'man V.A. Kotel'nikov Institute of Radio Engineering and Electronics of the RAS, Moscow, Russia 7th International

More information

Quantum. Thermodynamic. Processes. Energy and Information Flow at the Nanoscale. Gunter Mahler. Pan Stanford J [f I Publishing

Quantum. Thermodynamic. Processes. Energy and Information Flow at the Nanoscale. Gunter Mahler. Pan Stanford J [f I Publishing Quantum Thermodynamic Processes Energy and Information Flow at the Nanoscale Gunter Mahler Pan Stanford J [f I Publishing Preface Acknowledgments xiii xv 1 Introduction 1 1.1 Effective Theories 2 1.2 Partitions

More information

Ab Ini'o Molecular Dynamics (MD) Simula?ons

Ab Ini'o Molecular Dynamics (MD) Simula?ons Ab Ini'o Molecular Dynamics (MD) Simula?ons Rick Remsing ICMS, CCDM, Temple University, Philadelphia, PA What are Molecular Dynamics (MD) Simulations? Technique to compute statistical and transport properties

More information

Ergodicity of One-dimensional Systems Coupled to the Logistic Thermostat

Ergodicity of One-dimensional Systems Coupled to the Logistic Thermostat CMST 23(1) 11-18 (2017) DOI:10.12921/cmst.2016.0000061 Ergodicity of One-dimensional Systems Coupled to the Logistic Thermostat Diego Tapias 1, Alessandro Bravetti 2, David P. Sanders 3,4 1 Departamento

More information

Decoherence and Thermalization of Quantum Spin Systems

Decoherence and Thermalization of Quantum Spin Systems Copyright 2011 American Scientific Publishers All rights reserved Printed in the United States of America Journal of Computational and Theoretical Nanoscience Vol. 8, 1 23, 2011 Decoherence and Thermalization

More information

Entropy and Free Energy in Biology

Entropy and Free Energy in Biology Entropy and Free Energy in Biology Energy vs. length from Phillips, Quake. Physics Today. 59:38-43, 2006. kt = 0.6 kcal/mol = 2.5 kj/mol = 25 mev typical protein typical cell Thermal effects = deterministic

More information

Dynamical and Statistical Mechanical Characterization of Temperature Coupling Algorithms

Dynamical and Statistical Mechanical Characterization of Temperature Coupling Algorithms 5050 J. Phys. Chem. B 2002, 106, 5050-5057 Dynamical and Statistical Mechanical Characterization of Temperature Coupling Algorithms M. D Alessandro, A. Tenenbaum, and A. Amadei*, Department of Chemical

More information

Molecular Dynamics Lecture 3

Molecular Dynamics Lecture 3 Molecular Dynamics Lecture 3 Ben Leimkuhler the problem of the timestep in MD constraints - SHAKE/RATTLE multiple timestepping stochastic methods for holonomic constraints stochastic multiple timestepping

More information

arxiv: v1 [physics.chem-ph] 24 Apr 2018

arxiv: v1 [physics.chem-ph] 24 Apr 2018 arxiv:1804.08913v1 [physics.chem-ph] 24 Apr 2018 Fast-Forward Langevin Dynamics with Momentum Flips Mahdi Hijazi, 1 David M. Wilkins, 1, a) and Michele Ceriotti 1 Laboratory of Computational Science and

More information

For info and ordering all the 4 versions / languages of this book please visit: http://trl.lab.uic.edu/pon Contents Preface vii Chapter 1 Advances in Atomic and Molecular Nanotechnology Introduction 1

More information

Maxwell's Demon in Biochemical Signal Transduction

Maxwell's Demon in Biochemical Signal Transduction Maxwell's Demon in Biochemical Signal Transduction Takahiro Sagawa Department of Applied Physics, University of Tokyo New Frontiers in Non-equilibrium Physics 2015 28 July 2015, YITP, Kyoto Collaborators

More information

Lecture 4: Entropy. Chapter I. Basic Principles of Stat Mechanics. A.G. Petukhov, PHYS 743. September 7, 2017

Lecture 4: Entropy. Chapter I. Basic Principles of Stat Mechanics. A.G. Petukhov, PHYS 743. September 7, 2017 Lecture 4: Entropy Chapter I. Basic Principles of Stat Mechanics A.G. Petukhov, PHYS 743 September 7, 2017 Chapter I. Basic Principles of Stat Mechanics A.G. Petukhov, Lecture PHYS4: 743 Entropy September

More information

Time-reversible deterministic thermostats

Time-reversible deterministic thermostats Physica D 187 (2004) 253 267 Time-reversible deterministic thermostats Wm.G. Hoover a,b,, Kenichiro Aoki c, Carol G. Hoover b, Stephanie V. De Groot a a Department of Applied Science, University of California

More information

Modeling Materials. Continuum, Atomistic and Multiscale Techniques. gg CAMBRIDGE ^0 TADMOR ELLAD B. HHHHM. University of Minnesota, USA

Modeling Materials. Continuum, Atomistic and Multiscale Techniques. gg CAMBRIDGE ^0 TADMOR ELLAD B. HHHHM. University of Minnesota, USA HHHHM Modeling Materials Continuum, Atomistic and Multiscale Techniques ELLAD B. TADMOR University of Minnesota, USA RONALD E. MILLER Carleton University, Canada gg CAMBRIDGE ^0 UNIVERSITY PRESS Preface

More information

Ionic Liquids simulations : obtention of structural and transport properties from molecular dynamics. C. J. F. Solano, D. Beljonne, R.

Ionic Liquids simulations : obtention of structural and transport properties from molecular dynamics. C. J. F. Solano, D. Beljonne, R. Ionic Liquids simulations : obtention of structural and transport properties from molecular dynamics C. J. F. Solano, D. Beljonne, R. Lazzaroni Ionic Liquids simulations : obtention of structural and transport

More information

Molecular Dynamics Simulation Study of Transport Properties of Diatomic Gases

Molecular Dynamics Simulation Study of Transport Properties of Diatomic Gases MD Simulation of Diatomic Gases Bull. Korean Chem. Soc. 14, Vol. 35, No. 1 357 http://dx.doi.org/1.51/bkcs.14.35.1.357 Molecular Dynamics Simulation Study of Transport Properties of Diatomic Gases Song

More information

J. Stat. Mech. (2011) P07008

J. Stat. Mech. (2011) P07008 Journal of Statistical Mechanics: Theory and Experiment On thermodynamic and microscopic reversibility Gavin E Crooks Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA

More information

Introduction to Computer Simulations of Soft Matter Methodologies and Applications Boulder July, 19-20, 2012

Introduction to Computer Simulations of Soft Matter Methodologies and Applications Boulder July, 19-20, 2012 Introduction to Computer Simulations of Soft Matter Methodologies and Applications Boulder July, 19-20, 2012 K. Kremer Max Planck Institute for Polymer Research, Mainz Overview Simulations, general considerations

More information