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INELASTIC AND REACTIVE INELASTIC AND REACTIVE ELE-MENTARY PROCESSES IN ELE-MENTARY PROCESSES IN
ATOM- DIATOM, DIATOM-ATOM- DIATOM, DIATOM-DIATOM COLLISIONS AND DIATOM COLLISIONS AND
BEYONDBEYONDAntonio Laganà*
Dipartimento di Chimica
University of Perugia
lag@unipg.it
*Antonio Riganelli, Dimitris Skouteris, Leonardo Pacifici, Noelia Faginas Lago, Stefano Crocchianti
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MULTISCALE SIMULATIONS
Electronic structure
Kinetics of non elementary processes
Macroscopic properties of realistic systems
Fluid dynamics, electrodynamics, etc.
Nuclear dynamics
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SUMMARY
• A priori molecular simulations: theoretical means
• The N + N2 collisions: beyond quasiclassical
• The need for accurate potential energy surfaces• Some diatom-diatom, atom-polyatom processes• Towards complex molecular systems• Concurrent computing • Metalaboratories for molecular calculations• Grid enabled molecular simulators
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AC (f) + B (reactive)
A + B + C (dissociative)
The atom-diatom case
TRAJECTORY CALCULATIONS
The Hamilton equations
Integrate the above differential equations from a given configuration of the reactants until a final reactive, non reactive or dissociation configuration is reached
dRx/dt=PRx/µA,BC
drx/dt=Prx/µBC
dPRx/dt=-∂V/∂Rx
dPrx/dt=-∂V/∂rx dry/dt=Pry/µBC drz/dt=Prz/µBC
dRy/dt=PRy/µA,BC dRz/dt=PRz/µA,BC
dPry/dt=-∂V/∂ry dPrz/dt=-∂V/∂rz
dPRy/dt=-∂V/∂Ry
dPRz/dt=-∂V/∂Rz
A + BC (i) AB (f) + C (reactive)
A + BC (f) (non reactive)
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QUANTUM METHODS
Time dependent
Time independent
{W} – set of position vectors of the nuclei or any other choice of coordinatesHn - nuclear Hamiltonian
Factor out time and choose a different continuity va-riable (or transformation from reactants to products)
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THE DYNAMICAL QUANTITIES
• PROBABILITY: Pif=Nif/N or =|Sif|2
• CROSS SECTION: σif=πb2maxPif
• RATE COEFFICIENTS: averaging σif(E) over discrete distributions and integrating over continuous distributions
Reaction and Molecular Dynamics, Springer, 2000
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• N + N2 , H+H2, O+O2
• H2+OH, H2+H2, OH+HCl, OH+CO
• Cl + CH4
RECENT DYNAMICAL STUDIES
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Nitrogen atom Nitrogen molecule reaction
)',()(),()( 12
412
4 vNSNvNSN gg
Previous calculations: extended quasiclassical trajectory calculations of state to state rate coefficients (available for distribution)
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: exact quantum calculations
Zero total angular momentum
Time dependent approach in Jacobi coordinates
Initial quantum states v=0-5 j=0,1,2
Collision energy interval
Iterations: ~2000
LEPS surface
2NN
E=1.359-1.759 eV
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THE TIME DEPENDENT METHOD
Collocate the wavepacket
Time propagate the wavepacket
Carry out its analysis at the
product asymptote
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: state to state probabilities2NN
0.146 eV
0.433 eV
0.717 eV
0.997 eV
E(v)
V=0
V=1
V=2
V=3
1.270 eV
1.543eV
V=4
V=5
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: threshold energies2NN
1.359 eV
0.950 eV
0.772 eV
0.199 eV
Etr
V=0
V=1
V=2
V=4
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Product vibrational distributions (1.65 eV)
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Time dependent 3D
Time independent RIOS
2NN
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RIOS: state to state probabilities (v=0)
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RIOS vs 3D product vibrational distributions
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State specific probabilities. Effect of rotation
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FITTING A NEW POTENTIAL ENERGY SURFACE (PES)
• Fit the parameters of the PES to ab initio data • Adopt process coordinates instead of arrangement
coordinates (like Jacobi coordinates) • Use bond order (BO) variables defined as
nij=exp[-βij(rij-reij)]
and their polar version
ρ=[n122 + n23
2]½ α=atan(n23/n12)
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OH + HCl
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POLYATOMIC REACTION FUNCTIONAL FORMS
• ROtating BO (ROBO) and Largest Angle Generalization ROBO (LAGROBO).
• Many Process Expansion (MPE)
W=ξWξVξ
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MOVING TO LARGER SYSTEMS
• Simplify the interaction
• Decompose the domain
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THE FORCE FIELD
• The most popular formulations of force fields separate intra- from inter-molecular forces
• Intramolecular terms are associated to functional forms fitted to ab initio data
• Intermolecular are expressed as sums of two body semiempirical (usually of the Lennard Johnes type) functionals
Interaction representation
Many body expansion truncated to the second term Two body interactions are of the atom(ion) – atom(ion) type
Portability among different systems
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EnergyEnergy minimizationminimizationArArnnCC66HH66
Isomer (1|1)
Isomer (2|0)
-665C3v(2|0)2
-711D6h(1|1)2
-356C6v(1 0׀ )1
E(1/cm)GPIsomern
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OTHER NEW GLOBAL POTENTIALSOTHER NEW GLOBAL POTENTIALS1. Atom-bond pseudo two-body (Pirani et al.)
2. Full Bond Order potential (ALLBO) (Laganà et al.)
nkl is the Bond Order variable of the kl atomic pair
)exp( kle
klkl rrn
V ({r}) = ∑k∑mLkm(rkm,,αkm)
L = Lennard Johnes potential, k = atom index, m = bond index
P = Bond order potential, k = atom index, l = bond index
V ({r}) = ∑k∑lL kl (nkl)
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CONCURRENCY IN MOLECULAR CALCULATIONS
1. NATURAL CONCURRENCY
FROM EXTENSIVE TRAJECTORY CALCULATIONS
2. MULTILEVEL CONCURRENCY IN QUANTUM CALCULATIONS
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SISD (Single Instruction stream Single Data
stream)
CU PU MM
CU Control Unit
PU Processing Unit
MM Memory Module
IS DS
IS Instruction stream
DS Data stream
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SIMD (Master - workers)
CU
PU1
PU2
PUn
MM1
MM2
MMn
IS
DS1
DS2
DSn
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MIMD (Cooperative workers)
CU PU1
PU2
PUn
MM1
MM2
MMn
DS1
DS2
DSn
CU
CU
IS1
IS2
ISn
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MPI QUASICLASSICAL PSEUDOCODE
SEND “ready” status messageRECEIVE seedintegrate trajectoryupdate indicatorsSEND “ready” status messageGOTO RECEIVE
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
Master:
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COLLABORATIVE INITIATIVES TO DEVELOP REALISTIC A PRIORI
SIMULATORS
• Innovative approaches to chemical (as well as to physical, aerospace, medicinal, biological, etc.) problems need the cooperation of knowledge and computer resources.
• The concentration of human and hardware resources is no longer practical for logistic, economic and psycological reasons.
METACHEM
Metalaboratories for complex computational applications in
Chemistry
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THE METALABORATORY
• The METALABORATORY is a cluster of geographically distributed laboratories having complementary expertise and software programs and having some hardware resources grafted on a computing grid.
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THE STRUCTURE OF A METALABORATORY
• Several computational science laboratories acting as reservoirs of specific expertise relevant to the realization of a given project.
• One particularly skilled computer science laboratory (or Large Scale Computing Facility) acting as the regulator of the grid.
• Other laboratories having complementary expertises (for example an experimental laboratory).
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ONGOING MOLECULAR SCIENCE
METALABORATORIES• CI Calculations (Carsky).• DIRAC (Faegri).• SIMBEX (Gervasi)• Atmospheric processes (Aguilar)• Elchem (Laganà)• Chemical knowledge (Rossi)
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The CHEMISTRY community
Simbex
Murqm
Dirac
Elchem
Dysts
Comovit
Icab
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LABS per NATIONALITY (51)
1 Isr,Pl,Sk,Nl
2 Cz,Ch, Fr, Dk, A, Sw, No
3 Hu
4 Gr
5 E
6 D, Uk,
9 I
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SIMBEX: SIMUL. MOLECULAR BEAM
EXPERIMENTS • Managing an a priori
simulation to be inter- faced with the experi- ment in crossed mole- cular beam measure- ments
Exper. Simul.
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REQUEST: a potential fitted to beam experiments
Interaction
Observables
SUPPLY: the potential and related monitors
Dynamics
YES
NO Theoretical and experimental results agree?
The GEMS.0 demo application
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The INTERACTION module
INTERACTION
DYNAMICS
Is therea suitable Pes?
Are ab initiocalculationsavailable?
Are ab initiocalculations
feasible?
Ab initio applicationusing programs forelectronic structure
Application using fitting programs to
generate a PESroutine
Import thePES routine
NO
NO NO
YES YES YES
Force field-application taking
empirical data from
database to generate a PES
START
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The DYNAMICS module
DYNAMICS
OBSERVABLES
Are quantumdynamics
calculationsinappropriate?
Is the calculation
single initial state?
NO NO
YES YES
TI: application carrying out
time-independentquantum
calculations
TD: application carrying out time-
dependent quantumcalculations
ABCtraj: quasiclassical
trajectorycalculations
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The OBSERVABLES module
OBSERVABLESNO NO
YES YES
Is the observable
a state-to-stateobservable?
Is theobservable
a state specificobservable?
RATE: virtual monitor (VM)
for thermal ratecoefficients
CROSS: VM for statespecific cross sections,
rate constants and maps of
product intensity
DISTRIBUTIONS: VMfor scalar and vectorproduct distributions,
and state-to-state crosssections
Do calculated
and measuredproperties
agree?END
YES
INTERACTION
NO
Beam VM for Intensity in the
Lab frame
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The Virtual monitors
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THE PROTOTYPE COMPUTING GRID
• The computers that the participating laboratories will put outside the firewall to be clustered on the network and act as a single virtual parallel machine.
• The running version (not the ones under develop-ment) of the relevant codes that the participating laboratories will implement to run concurrently on the grid for the project.
• The distribution software to allocate the different tasks on the most suitable machines
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Demo deployment layout
• Sites
– GILDA testbed sites, in which INFN Grid 2.2.0 (fully compatible with LCG 2.2.0) middleware is installed.
• Key services
– Resource Broker: grid004.ct.infn.it– Computing Element: ce.grid.unipg.it– User Interface: ui.grid.unipg.it– GENIUS Portal: https://genius.ct.infn.it– CompChem VOMS
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The testbed sites• The Chemistry Department of the University of Perugia has been
included in the sponsor and the testbed site list • The Chemistry Department node is made by a cluster of 14 nodes (2
proc. Intel Pentium III, 2G RAM, 40G HD) + Computing Element + LCNGFG server
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Demo scale of usage• Number of jobs: 10 per day
• Storage: 100KB – 50GB depending on the type of computational engine used and the chemical system studied:
– Trajectory calculations: <100KB
– Time Dependent Quantum: 10GB
– Time Independent Quantum: 50GB
• RAM: 100KB – 2GB
– Trajectory calculations: <100K
– Time Dependent Quantum: 1GB
– Time Independent Quantum: 2GB
• Success rate: 98%
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EGEE
Grid
Usage of LCG-2 middleware services
GEMS
Application
Deployment
Server
Resource Broker
Computing Element
MPI
GEMS
programGEMS
programGEMS
programGEMS
programs
Working nodes
License Server
•Outbound connectivity
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The grid added value• SOFTWARE INTEGRATION INTO DISTRIBUTED
WORKFLOWS: assemble applications out of various (different or complementary) distributed competences coordinated via the grid.
• COMPUTATIONAL CAMPAIGNS: evaluate properties depending on the fate of few out of millions or more events by distributing the computations on the grid
• COLLABORATIVE ENGINEERING OF KNOWLEDGE:
handle (when is the case also in a privacy protecting fashion) chemical information and knowledge including training and production of new knowledge.
SIMBEX: a research/educational tool for the simulation of elementary chemical reaction
•High interactivity
•Advanced visualization
•In deep insight into the chemical mechansm
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GRID PROJECTS
• GRID.IT: the Italian project on grid platforms
• EGEE: the European production grid
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GRID.IT
INFN
ASI
CNIT
The Italian GRID
CNR
Università
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Programming Environment
High-level servicesHigh-level servicesKnowledge services, Data bases, Scientific libraries, Image processing, …Knowledge services, Data bases, Scientific libraries, Image processing, …
Domain-specific Problem Solving Environments (PSEs)
High-performance, Grid-aware component-based High-performance, Grid-aware component-based programming model and toolsprogramming model and tools
Resource management, Performance tools, Security, VO, …Resource management, Performance tools, Security, VO, …
Next Generation MiddlewareNext Generation Middleware
Basic infrastructure - standards (OGSA-compliant)
Software technology of Grid.it
Applications (Chemistry, Biology, Earth science, etc.)
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PG
MI
PD
BO
BA
NA
RM
ChemGrid.it: a Grid model for ChemistryComp. Center
UPV
UBCESCA
Comp. Center
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ChemGrid: the PG configuration
Access to GRID.IT
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• The VO CompChem has been created to register to the VO:http://grid-cnaf.infn.it/index.php?
voregister&type=1• The implementation of the Grid Molecular Simulator prototype has
prompted a modification of the EGEE infrastructure in order to guarantee the strong need for real-time interaction with the Grid
• The prototype will be rewritten in XML (instead of PHP) to be included in the Genius application testbed to demonstrate the power of the Grid.
• We attended the following EGEE events:– EGEE Generic Applications Advisory Panel (EGAAP), First Meeting,
Geneva, June 14th, 2004– EGEE NA4 Open Meeting, Catania, July 14-16, 2004
The outcomes of CompChem
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COLLABORATIONS INFORMATICS M. Vanneschi, R. Baraglia, Pisa (Italy) O. Gervasi, S. Tasso, Perugia (Italy) CHEMISTRY G.G. Balint-Kurti, Bristol (UK) E. Garcia, Vitoria (Spain) M. Alberti, Barcelona (Spain) G. Parker, Norman (USA) SIMBEX EU COST CHEMISTRY GROUP
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CONCLUSIONS
• Rigorous dynamical calculations are becoming routinely feasible for polyatomic systems
• Molecular dynamics treatments are tackling extremely complex systems
• Dynamical treatments are becoming essential part of multiscale approaches on the computing Grid
• Research must adopt a service oriented orgnization to become sustainable
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