Holonomic Constraints: A Case for Statistical Mechanics of Non-Hamiltonian Systems
Abstract
:1. Introduction
2. Dynamics with Holonomic Constraints
- (i)
- the f constraint relationships , and
- (ii)
- the remaining generalized coordinates .
3. SHAKE, Integrating the Equations of Motion
3.1. Verlet Algorithm
3.2. Velocity-Verlet Algorithm
4. Equilibrium Statistical Mechanics in the Hamiltonian Formulation
5. Rare Events and Blue Moon Ensemble
6. Liouville Equation in the Presence of Constraints
- (i)
- to get a correct generalized Liouville equation;
- (ii)
- to find the results already obtained for the equilibrium ensemble;
- (iii)
6.1. Generalized Distribution Function
- Construct the distribution function by Equation (106) using all the independent conservation laws implicit in the equations of motion;
- Eliminate from the statistical space all variables that result uncoupled to the bulk of the system or driven by it. By driven, we mean variables
- (i)
- whose evolution follows that of the other variables without influencing those ones and
- (ii)
- that do not appear in the phase space expression of any of the conserved quantities .
A (not so) typical example could be that of particles of zero mass interacting with the system only via the holonomic constraints defining their own values (see Appendix C).
- 3.
- Once the essential, reduced, set of variables, let us call them , has been selected, calculate the phase space compressibility of the reduced dynamical system
6.2. Response Theory
7. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
Appendix A
Appendix B
Appendix C
References
- Carter, E.; Ciccotti, G.; Hynes, J.T.; Kapral, R. Constrained reaction coordinate dynamics for the simulation of rare events. Chem. Phys. Lett. 1989, 156, 472–477. [Google Scholar] [CrossRef]
- Ciccotti, G.; Kapral, R.; Vanden-Eijnden, E. Blue Moon sampling, vectorial reaction coordinates, and unbiased constrained dynamics. ChemPhysChem 2005, 6, 1809–1814. [Google Scholar] [CrossRef] [PubMed]
- Ryckaert, J.P.; Ciccotti, G.; Berendsen, H.J. Numerical integration of the Cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes. J. Comput. Phys. 1977, 23, 327–341. [Google Scholar] [CrossRef]
- Car, R.; Parrinello, M. Unified approach for molecular dynamics and density-functional theory. Phys. Rev. Lett. 1985, 55, 2471–2474. [Google Scholar] [CrossRef] [PubMed]
- Ciccotti, G.; Ferrario, M. Constrained and nonequilibrium molecular dynamics. In Classical and Quantum Dynamics in Condensed Phase Simulations; World Scientific: Singapore, 1998; pp. 157–177. [Google Scholar]
- Ryckaert, J.P.; Ciccotti, G. Introduction of Andersen’s demon in the molecular dynamics of systems with constraints. J. Chem. Phys. 1983, 78, 7368–7374. [Google Scholar] [CrossRef]
- Tuckerman, M.E.; Liu, Y.; Ciccotti, G.; Martyna, G.J. Non-Hamiltonian molecular dynamics: Generalizing Hamiltonian phase space principles to non-Hamiltonian systems. J. Chem. Phys. 2001, 115, 1678–1702. [Google Scholar] [CrossRef]
- Ciccotti, G.; Kapral, R.; Sergi, A. Non-equilibrium molecular dynamics. In Handbook of Materials Modeling; Yip, S., Ed.; Springer: Berlin, Germany, 2005; pp. 745–761. [Google Scholar]
- Hartmann, C.; Schütte, C.; Ciccotti, G. Communications: On the linear response of mechanical systems with constraints. J. Chem. Phys. 2010, 132, 111103. [Google Scholar] [CrossRef] [PubMed]
- Goldstein, H.; Poole, C.P.; Safko, J.L. Classical Mechanics, 3rd Edition ed; Addison-Wesley: Boston, MA, USA, 2000. [Google Scholar]
- Ciccotti, G.; Ryckaert, J. Molecular dynamics simulation of rigid molecules. Comput. Phys. Rep. 1986, 4, 346–392. [Google Scholar]
- Andersen, H.C. Rattle: A “velocity” version of the shake algorithm for molecular dynamics calculations. J. Comput. Phys. 1983, 52, 24–34. [Google Scholar] [CrossRef]
- Weinbach, Y.; Elber, R. Revisiting and parallelizing SHAKE. J. Comput. Phys. 2005, 209, 193–206. [Google Scholar] [CrossRef]
- Ciccotti, G.; Ferrario, M.; Hynes, J.T.; Kapral, R. Molecular dynamics simulation of ion association reactions in a polar solvent. J. Chim. Phys. 1988, 85, 925–929. [Google Scholar] [CrossRef]
- Sprik, M.; Ciccotti, G. Free energy from constrained molecular dynamics. J. Chem. Phys. 1998, 109, 7737–7744. [Google Scholar] [CrossRef]
- Orlandini, S.; Meloni, S.; Ciccotti, G. Hydrodynamics from Statistical Mechanics: Combined dynamical-NEMD and conditional sampling to relax an interface between two immiscible liquids. Phys. Chem. Chem. Phys. 2011, 13, 13177–13181. [Google Scholar] [CrossRef] [PubMed]
- Cottone, G.; Lattanzi, G.; Ciccotti, G.; Elber, R. Multiphoton absorption of myoglobin–nitric oxide complex: Relaxation by D-NEMD of a stationary state. J. Phys. Chem. B 2012, 116, 3397–3410. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pourali, M.; Meloni, S.; Magaletti, F.; Maghari, A.; Casciola, C.M.; Ciccotti, G. Relaxation of a steep density gradient in a simple fluid: Comparison between atomistic and continuum modeling. J. Chem. Phys. 2014, 141, 154107. [Google Scholar] [CrossRef] [PubMed]
- Ciccotti, G.; Ferrario, M. Dynamical non-equilibrium molecular dynamics. Entropy 2014, 16, 233–257. [Google Scholar] [CrossRef] [Green Version]
- Ciccotti, G.; Bonella, S.; Ferrario, M.; Pierleoni, C. Probabilistic derivation of spatiotemporal correlation functions in the hydrodynamic limit. J. Phys. Chem. B 2016, 120, 1996–2000. [Google Scholar] [CrossRef] [PubMed]
- Fixman, M. Classical Statistical Mechanics of constraints: A theorem and application to polymers. Proc. Nat. Acad. Sci. USA 1974, 71, 3050–3053. [Google Scholar] [CrossRef] [PubMed]
- Hairer, E.; Lubich, C.; Wanner, G. Geometric numerical integration illustrated by the Störmer–Verlet method. Acta Numer. 2003, 12, 399–450. [Google Scholar] [CrossRef]
- Hairer, E.; Wanner, G.; Lubich, C. Geometric Numerical Integration. Structure-Preserving Algorithms for Ordinary Differential Equations; Springer: Berlin, Germany, 2006. [Google Scholar]
- Hess, B.; Bekker, H.; Berendsen, H.J.C.; Fraaije, J.G.E.M. LINCS: A linear constraint solver for molecular simulations. J. Comput. Chem. 1997, 18, 1463–1472. [Google Scholar] [CrossRef]
- Kräutler, V.; van Gunsteren, W.F.; Hünenberger, P.H. A fast SHAKE algorithm to solve distance constraint equations for small molecules in molecular dynamics simulations. J. Comput. Chem. 2001, 22, 501–508. [Google Scholar] [CrossRef]
- Gonnet, P. P-SHAKE: A quadratically convergent SHAKE in O(n2). J. Comput. Phys. 2007, 220, 740–750. [Google Scholar] [CrossRef]
- Gonnet, P.; Walther, J.H.; Koumoutsakos, P. θ-SHAKE: An extension to SHAKE for the explicit treatment of angular constraints. Comput. Phys. Commun. 2009, 180, 360–364. [Google Scholar] [CrossRef]
- Leimkuhler, B.; Reich, S. Symplectic integration of constrained Hamiltonian systems. Math. Comput. 1994, 63, 589–605. [Google Scholar] [CrossRef]
- Sergi, A.; Ciccotti, G.; Falconi, M.; Desideri, A.; Ferrario, M. Effective binding force calculation in a dimeric protein by molecular dynamics simulation. J. Chem. Phys. 2002, 116, 6329–6338. [Google Scholar] [CrossRef]
- Kubo, R. Statistical-Mechanical theory of irreversible processes. I. General theory and simple applications to magnetic and conduction problems. J. Phys. Soc. Japan 1957, 12, 570–586. [Google Scholar] [CrossRef]
- Ciccotti, G.; Jacucci, G. Direct computation of dynamical response by molecular dynamics: The mobility of a charged Lennard-Jones particle. Phys. Rev. Lett. 1975, 35, 789–792. [Google Scholar] [CrossRef]
- Ciccotti, G.; Jacucci, G.; McDonald, I.R. “Thought-experiments” by molecular dynamics. J. Stat. Phys. 1979, 21, 1–22. [Google Scholar] [CrossRef]
- Ciccotti, G.; Ferrario, M. Non-equilibrium by molecular dynamics: A dynamical approach. Mol. Simul. 2016, 42, 1385–1400. [Google Scholar] [CrossRef]
- Ferrario, M.; Bonella, S.; Ciccotti, G. On the establishment of thermal diffusion in binary Lennard-Jones liquids. Eur. Phys. J. Spec. Top. 2016, 225, 1629–1642. [Google Scholar] [CrossRef]
- Bonella, S.; Ferrario, M.; Ciccotti, G. Thermal diffusion in binary mixtures: Transient behavior and transport coefficients from equilibrium and nonequilibrium molecular dynamics. Langmuir 2017, 33, 11281–11290. [Google Scholar] [CrossRef] [PubMed]
- Evans, D.J.; Morriss, G. Statistical Mechanics of Nonequilibrium Liquids; Cambridge University Press: Cambridge, UK, 2008. [Google Scholar]
- Green, M.S. Markoff random processes and the Statistical Mechanics of time-dependent phenomena. J. Chem. Phys. 1952, 20, 1281–1295. [Google Scholar] [CrossRef]
- Ryckaert, J.P.; Bellemans, A.; Ciccotti, G. The rotation-translation coupling in diatomic molecules. Mol. Phys. 1981, 44, 979–996. [Google Scholar] [CrossRef]
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Ciccotti, G.; Ferrario, M. Holonomic Constraints: A Case for Statistical Mechanics of Non-Hamiltonian Systems. Computation 2018, 6, 11. https://doi.org/10.3390/computation6010011
Ciccotti G, Ferrario M. Holonomic Constraints: A Case for Statistical Mechanics of Non-Hamiltonian Systems. Computation. 2018; 6(1):11. https://doi.org/10.3390/computation6010011
Chicago/Turabian StyleCiccotti, Giovanni, and Mauro Ferrario. 2018. "Holonomic Constraints: A Case for Statistical Mechanics of Non-Hamiltonian Systems" Computation 6, no. 1: 11. https://doi.org/10.3390/computation6010011