GEMS: THE G RID E MPOWERED M OLECULAR S IMULATOR

1. GEMS: THE GRID EMPOWERED MOLECULAR SIMULATOR Antonio Laganà Department of Chemistry, University of Perugia, Italy

2. THE PROJECT • Step 1 - SIMBEX (Simulator of Crossed Beam Experiments) for atom diatom trajectory studies • Step 2 - GEMS (Grid Empowered Molecular Simulator) • Step 3 - Grid version of GEMS • Step 4 - Some case studies • Step 5 - The COMPCHEM Molecular Science Virtual Organization (VO) • Step 6 - Next

3. 1 - SIMBEX

4. SIMBEX: CROSSED BEAM EXPERIMENTof Perugia • MEASURABLES • Angular and time of flight product distributions • INFORMATION OBTAINABLE • - Primary reaction products • Reaction mechanisms • Structure and life time of transient • Internal energy distribution of products • Key features of the potential

5. THE SIMULATOR System input Interaction Dynamics Observables Virtual Monitors

6. The implemented INTERACTION module START CAVEATS PES not needed in on the fly methods. Seldomly a PES already exists PESs can be semiempirical Best if from a fit of ab initio values Often PESs are of low accuracy Is there a suitable PES? NO INTERACTION YES Import the PES parameters DYNAMICS

7. The implemented DYNAMICS module Are trajectory calculations accepta- ble? CAVEATS Implementation with trajectories ABCtraj for atom diatom NO DYNAMICS YES TRAJ: application using classical mechanics calculations OBSERVABLES

8. The implemented OBSERVABLES module Is the observable a state-to-state one? NO OBSERVABLES YES DISTRIBUTIONS: Virtual Monitors for scalar and vector product distributions EXTEND THE CALCULATIONTO OTHER PROPERTIES Do calculated and measured properties agree? YES NO TRY USING ANOTHER SURFACE

9. The prototype ChemGrid.it of grid.it MI CILEA RM PD UPV PG UB CESCA NA BO BA CINECA

10. Earth observation Astrophysics Bioinformatics Applications Computational Chemistry Geophysics HP Components Problem Solving Program- Ming tools Libraries Cost models Portals Communications Security Middleware Monitoring Resource Management High perfor- mance nets GARR Fiber optics

11. THE EGEE PRODUCTION GRID • EGEE is a European project aimed at developing a European service grid infrastructure available to scientists. • A prototype implementation of the Grid Molecular Simulator has been selected for the NA4 Activity of EGEE (Application Identification and Support)

12. THE EGEE PRODUCTION GRID

13. The GRIDified atom diatom TRAJ kernel Define quantities of general use TRAJ Iterate over initial conditions the integration of individual trajectories (ABCTRAJ, etc.) Collect individual trajectory results return

14. TRAJECTORY NATURAL CONCURRENCY Master: Worker: DO traj_index =1, traj_number RECEIVE status message IF worker “ready” THEN generate seed SEND seed to worker ELSE GOTO RECEIVE endIF endDO SEND “ready” status message RECEIVE seed integrate trajectory update indicators SEND “ready” status message GOTO RECEIVE

15. THE VIRTUAL MONI-TORS SHOWED THE PRODUCT ANGULAR DISTRIBUTIONS FOR THE VARIOUS CHANNELS H+ICl→Cl + HI H+ICl→H + ICl H+ICl→HCl+I

16. Using history files to rationalize mechanisms NEAR RECROSSING IN REACTIVE PROCESSES

17. 2 – A GENERALIZATION OF SIMBEX TO GEMS: THE GRID EMPOWERED MOLECULAR SIMULATOR

18. Nuclear Schrödinger equation: Electronic Schrödinger equation: The molecular dynamics problem Separation of electronic and nuclear motions

19. ELECTRONIC SCHRÖDINGER EQUATION • Programs: often standard packages • Methods - wavefunction quantum approaches (MRCI) - density functional theory (DFT)

20. NUCLEAR SCHRÖDINGER EQUATION • Quantum - Integrate the equation in time for a given (or a set of given or an average distribution) state(s) - Integrate the (stationary) equation in space for a given energy and all energetically open states • Classical transform the Schrödinger equation into a set classical mechanics equations and integrate them in time • Semiclassical overimpose quantum effects of the associated wave to quantum mechanics outcomes

21. THE QUANTUM TREATMENT Time dependent {W} – set of position vectors of the nuclei or choices of center of mass coordinates like the already seen Jacobi Rτ and rτ vectors HN - nuclear Hamiltonian METHOD – integrate the first order time dependent equation using time as continuity variable and either collocating the system wavepacket on a grid (for R and r) or by expanding it on a basis set (for Θ)

22. THE QUANTUM TREATMENT Time independent {W} – set of position vectors of the nuclei or choices of orthogonal coordinates of which one can act as continuity variable in going from one arrangement to another HN - nuclear Hamiltonian METHOD – segment the continuity variable in sectors and expand locally (in each sector) the wavefunction on the remaining (orthogonal) coordinates

23. FLUX CORRELATION FUNCTION FORMULATION OF THE RATE COEFFICIENT translationalpartition function Flux-flux correlation function rotational partition function By exact MCTDH or approximate SC-IVR calculations

24. THE MCTDH METHOD • Diagonalisation of the thermal flux operator defined onto a dividing surface to build a reduced Krylov subspace (iterative diagonalisation by consecutive application of the thermal flux operator on a trial wave function). The outcome is a set of eigenvalues and eigenstates of the thermal flux operator. • Time propagation of the thermal flux eigenstates employing MCTDH. • Calculation of observables: k(T), N(E).

25. THE FLUSS PROGRAM

26. QDYN: the Quantum dynamics group in COMPCHEM (from COST Action D37) • A COST Action to foster the constitution of a Molecular science community in the European Grid initiatives • A working group (QDYN) to implement exact and approximate quantum methods • Develop workflow and expert system tools for quantum chemical investigations • Enhance collaborative research work in terms of service offer/request within quantum chemistry developers • Foster the transfer of exact molecular treatments to industrial and commercial applications

27. MEMBERS OF QDYN • A. LAGANA’, O. GERVASI (Perugia, Italy) • G.G. BALINT KURTI (Bristol, UK) • E. GARCIA (Vittoria, Spain) • F. HUARTE (Barcelona, Spain) • G. LENDVAY (Budapest, Hungary) • G. NYMAN (Goteborg, Sweden) • S. FARANTOS (Heraklion, Greece) • M. LAUNAY (Rennes, France)

28. OTHER APPROACHES • Reduced dimensionality quantum methods • Classical, quasiclassical and molecular dynamics methods • Semiclassical methods

29. 3 – GRID IMPLEMENTATION

30. The extended INTERACTION module START Take force field data and procedures from related databases Are ab initio calculations available? Are ab initio calculations feasible? NO NO Is there a suitable Pes? NO INTERACTION YES YES YES FITTING SUPSIM Import the PES routine DYNAMICS

31. SUPSIM: the Gridified Ab initio approach Iterate over the system Geometries the call of ab initio suites of codes (GAMESS, GAUSSIAN, MOLPRO, etc) Define the characteristics of the ab initio calculation, the coordinates used and the Variable’s intervals SUPSIM return Collect single molecular geometry energy

32. The FITTING portal YES YES YES Are remai- ning values inaccurate? Do ab initio values have the proper sym- metry? Are asym- ptotic values accurate? FITTING NO NO NO Modify asym- ptotic values Modify short and long range values Enforce the proper symmetry Application using fitting programs to generate a PES routine Return

33. The extended DYNAMICS module Ap- proximate quantum calcula tions? Se- miclassical calcula tions? Exact quantum calculations? NO NO NO DYNAMICS YES YES YES CLASSICAL Integration of the Classical equations QDYN Integration of the exact quantum dynamics equations APPRQDYN Integration of the approximate quantum dynamics equations SEMICLASSICAL Integration of clas- sical equations and of the associated wave OBSERVABLES

34. The QDYN PROCEDURES State specific (summed over final states) Single Initial quantum state? Multiple initial quantum states? NO Fully averaged NO QUANTUM DYNAMICS YES YES YES TD: atom diatom S matrix elements for several energies TI: atom diatom S matrix elements for a single energy MCTDH: reactive flux over the barrier CRP: cumulative reaction probabilities and Transition State theory OBSERVABLES

35. Gridified time dependent approaches • Iterate over initial conditions • the time propagation • (RWAVEPR, CYLHYP, etc.) Define quantities of general use TD • Collect single initial state • S matrix element return

36. Gridified time independent approach Define quantities of general use including the integration bed TI Iterate over the reaction coor- dinate to build the interaction matrix Collect coupling matrix elements Broadcast coupling matrix Iterate over total energy value the integration of scattering equations return Collect state to state S matrix elements

37. Gridified MCTDH method

38. The extended MEASURABLES module INTERACTION VM for thermal and thermodynamic pro- perties including Molecular Virtual Reality tools Is the observable a state-to-state one? Is the observable a state specific onee? NO NO OBSERVABLES Beam VM for Intensity in the Lab frame YES YES CROSS: VM for state specific cross sections, rate constants and maps of product intensity DISTRIBUTIONS: VM for scalar and vector product distributions, and state-to-state crosssections Do calculated and measured properties agree? NO YES END

39. PROGRAMS BEING IMPLEMENTED ON THE GRID FOR PERSONAL USE Perugia, ABC (also using PGRADE), RWAVEPR, CYLHYP, DL_POLY Bristol, DIFFREALWAVE Vittoria, RWAVEPR, VENUS Vienna, COLUMBUS Budapest, ABC, VENUS, RWAVEPR Barcelona, MCTDH Goteborg (On the fly Q-RBA?) Heraklion, MODTINKER

40. 4 – SOME CASE STUDIES

41. The N+N2 case study

42. : the LEPS potential energy surface • Isoenergetic contour • maps 1 eV spacing • The collinear LEPS surface

44. Reactive state to state probabilities E(v) 0.146 eV V=0 V=1 0.433 eV V=2 0.717 eV V=3 0.997 eV 1.270 eV V=4 V=5 1.543eV

45. Threshold energies Etr 1.359 eV V=0 V=1 0.950 eV V=2 0.772 eV V=4 0.199 eV

46. : the L3 potential energy surface • Isoenergetic contour • maps 1 eV spacing • The bent L3 surface (125o transition • state geometry)

47. : the L4 potential energy surface • The bent L4 surface (125o transition • state geometry) • Two higher barriers sandwiching a well L4 L3

48. Rate coefficients ● LEPS ● L3 L4

49. IONIC BIOLOGICAL CHANNELS • Biological ionic channels play an important role in the control of ionic cellular concentrations and in synapses They are usually schematized as a sequence of: • Entrance gate • Bilayer pore • Selectivity filter

50. A life science application to the understanding of cellular micropores A nanotube model can be used to understand the ionic conductivity of cations (like Na+ or K+) through cellular membranes. ION FLOW THROUGH NANOTUBES