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GEMS: THE GRID EMPOWERED
MOLECULAR SIMULATOR
Antonio Laganà
Department of Chemistry, University of Perugia, Italy
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
1 - SIMBEX
SIMBEX: CROSSED BEAM EXPERIMENT
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
of Perugia
THE SIMULATOR
System input
Interaction
Dynamics
Observables
Virtual Monitors
The implemented INTERACTION module
START
INTERACTION
Is there
a suitable
PES?
NO
CAVEATS
PES not needed in on the fly methods.
Seldomly a PES already exists
YES
PESs can be semiempirical
Best if from a fit of ab initio values
Import the
PES parameters
DYNAMICS
Often PESs are of low accuracy
The implemented DYNAMICS
module
DYNAMICS
Are
trajectory
calculations
acceptable?
NO
CAVEATS
Implementation with trajectories
ABCtraj for atom diatom
YES
TRAJ: application
using classical
mechanics
calculations
OBSERVABLES
The implemented OBSERVABLES module
OBSERVABLES
Is the
observable
a state-to-state
one?
NO
YES
DISTRIBUTIONS:
Virtual Monitors for
scalar and vector
product distributions
EXTEND THE
CALCULATION
TO OTHER
PROPERTIES
YES
Do
calculated
and measured
properties
agree?
NO
TRY USING
ANOTHER
SURFACE
The prototype ChemGrid.it of grid.it
MI
CILEA
RM
PD
UPV
PG
UB
CESCA
NA
BO
BA
CINECA
Astrophysics
Bioinformatics
Computational Chemistry
Geophysics
HP Components
Libraries
Portals
Problem Solving
Cost models
Security
Resource Management
GARR
Earth observation
Applications
ProgramMing tools
Communications
Monitoring
Fiber optics
Middleware
High performance nets
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)
THE EGEE PRODUCTION GRID
The GRIDified atom diatom TRAJ kernel
TRAJ
Define quantities of general
use
return
Iterate over initial conditions
the integration of individual
trajectories (ABCTRAJ, etc.)
Collect individual
trajectory results
TRAJECTORY NATURAL CONCURRENCY
Master:
DO traj_index =1, traj_number
RECEIVE status message
IF worker “ready” THEN
generate seed
SEND seed to worker
ELSE GOTO RECEIVE
endIF
endDO
Worker:
SEND “ready” status message
RECEIVE seed
integrate trajectory
update indicators
SEND “ready” status message
GOTO RECEIVE
THE VIRTUAL MONITORS SHOWED THE
PRODUCT ANGULAR
DISTRIBUTIONS FOR
THE VARIOUS
CHANNELS
H+ICl→H + ICl
H+ICl→Cl + HI
H+ICl→HCl+I
Using history files to rationalize mechanisms
NEAR RECROSSING
IN REACTIVE
PROCESSES
2 – A GENERALIZATION OF SIMBEX
TO GEMS: THE GRID EMPOWERED
MOLECULAR SIMULATOR
The molecular dynamics problem

i  W , w, t   Hˆ  W , w, t 
t
Separation of electronic and nuclear motions
Electronic Schrödinger equation:
Nuclear Schrödinger equation:

ˆ
ˆ
H elec n w;W   En W n w;W  H n  n W , t   i  n W , t 
t
ELECTRONIC SCHRÖDINGER
EQUATION
• Programs: often standard packages
• Methods
- wavefunction quantum approaches (MRCI)
- density functional theory (DFT)
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
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)
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
FLUX CORRELATION FUNCTION
FORMULATION OF THE RATE COEFFICIENT

1
k (T ) 
dtC f (t )

Qtrans (T )QN 2 (T ) 0
translational partition function
3
 R 
Qtrans(T)   2 
2  
Flux-flux correlation function
rotational
partition
function
2
QN (T )  6
2

 3

By exact MCTDH or
C f (t ) approximate
SC-IVR calculations
 2 j  1exp    
j even
j
 2 j  1exp    
j odd
j
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).
THE FLUSS PROGRAM
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
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)
OTHER APPROACHES
• Reduced dimensionality quantum methods
• Classical, quasiclassical and molecular
dynamics methods
• Semiclassical methods
3 – GRID IMPLEMENTATION
The extended INTERACTION module
START
INTERACTION
NO
Is there
a suitable Pes?
YES
Import the
PES routine
DYNAMICS
Are ab initio
calculations
available?
YES
FITTING
NO
Are ab initio
calculations
feasible?
YES
SUPSIM
NO
Take force field
data and
procedures
from related
databases
SUPSIM: the Gridified Ab initio approach
SUPSIM
Define the characteristics of
the ab initio calculation, the
coordinates used and the
Variable’s intervals
return
Iterate over the system
Geometries the call of ab
initio suites of codes
(GAMESS, GAUSSIAN,
MOLPRO, etc)
Collect single molecular
geometry energy
The FITTING
portal
YES
YES
FITTING
Are asymptotic values
accurate?
NO
Modify asymptotic values
Return
YES
Are remaining values
inaccurate?
Do ab initio
values have the
proper symmetry?
NO
NO
Modify short and
long range values
Enforce the proper
symmetry
Application using
fitting programs to
generate a PES
routine
The extended DYNAMICS module
DYNAMICS
Exact
quantum
calculations?
YES
QDYN
Integration of the
exact quantum
dynamics
equations
OBSERVABLES
NO
Approximate
quantum
calcula
tions?
YES
APPRQDYN
Integration of the
approximate
quantum
dynamics
equations
NO
Semiclassical
calcula
tions?
NO
YES
SEMICLASSICAL
Integration of classical equations and
of the associated
wave
CLASSICAL
Integration of the
Classical
equations
The QDYN PROCEDURES
QUANTUM
DYNAMICS
Single
Initial
quantum
state?
YES
TD: atom diatom
S matrix
elements
for several
energies
OBSERVABLES
NO
Multiple
initial
quantum
states?
YES
TI: atom diatom
S matrix
elements for a
single energy
NO
State
specific
(summed over
final states)
Fully averaged
YES
MCTDH: reactive
flux over the
barrier
CRP:
cumulative
reaction
probabilities
and Transition
State theory
Gridified time dependent approaches
TD
Define quantities of general
use
return
•Iterate over initial conditions
•the time propagation
•(RWAVEPR, CYLHYP, etc.)
•Collect single initial state
•S matrix element
Gridified time independent approach
TI
Define quantities of general
use including the integration
bed
Iterate over the reaction coordinate 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
Gridified MCTDH method
The extended MEASURABLES module
INTERACTION
OBSERVABLES
Is the
observable
a state-to-state
one?
Beam VM for
Intensity in the
Lab frame
NO
YES
DISTRIBUTIONS: VM
for scalar and vector
product distributions,
and state-to-state
crosssections
NO
YES
END
Do
calculated
and measured
properties
agree?
Is the
observable
a state specific
onee?
YES
CROSS: VM for state
specific cross sections,
rate constants
and maps of
product intensity
NO
VM for thermal and
thermodynamic properties including
Molecular Virtual
Reality tools
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
4 – SOME CASE STUDIES
The N+N2 case study
N ( 4S )  N 2 (1  g , v)  N ( 4S )  N 2 (1  g , v' )
N  N 2 : the LEPS potential energy surface
The collinear LEPS surface
Isoenergetic contour
maps 1 eV spacing
Reactive state to state probabilities
E(v)
0.146 eV
V=0
0.433 eV
V=1
0.717 eV
V=2
0.997 eV
V=3
1.270 eV
V=4
1.543eV
V=5
Threshold energies
Etr
1.359 eV
V=0
0.950 eV
V=1
0.772 eV
V=2
0.199 eV
V=4
N  N 2 : the L3 potential energy surface
The bent L3 surface (125o transition
state geometry)
Isoenergetic contour
maps 1 eV spacing
N  N 2 : the L4 potential energy surface
The bent L4 surface (125o transition
state geometry)
Two higher barriers sandwiching a well
L4
L3
Rate coefficients
●
LEPS
●
L3
L4
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
ION FLOW THROUGH NANOTUBES
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
THE CARBON NANOTUBE AS A MODEL
We considered the CNT as a model for biological ionic
channels (though it has also several interesting
applications in itself)
MOLECULAR DYNAMICS
A quantum approach to ion flow in nanotubes
• H+/D+ ions flowing through a carbon nanotube
• A quantum scattering problem solved using a
3D time-dependent technique (the problem has
been already solved using classical approaches)
• Implementation of a quantum scattering
formalism based on polar cylindrical
coordinates to single out resonances,
interferences and tunneling
SCATTERING IN CYLINDRICAL
SYMMETRY PROBLEMS
In the nanotube problem the
symmetry is about cylindrical
The most suitable coordinates are
the polar cylindrical ones (r,,z)
The projection of the total angular
momentum on z is a good quantum
number
BASIS SET
The z component of the wavefunction is given by
plane waves:
ψ(z)  eikz
with k being the momentum along z.
The radial component is a Bessel function and the
angular component is an imaginary exponential
r
ψ(r,θ)  JK (ρn )  eiKθ
R
R is the nanotube radius
K is the angular momentum component on z
ρn is the nth zero of the Bessel function JK
THE WAVEPACKET
- The initial (t=0) wavepacket is placed at one
end of the nanotube
- Its shape is that of an eigenfunction of the
polar component of the Hamiltonian with a
given component of the total angular
momentum and a given radial excitation (that of
the corresponding Bessel function)
- Its z component is a Gaussian times a phase
factor (corresponding to the linear momentum)
 (z)  e

(z  z 0 ) 2
2σ 2
 eikz
OUTGOING FLUX PLOTS: angular momentum
H+ -
Elong=0.04 h
Etransv=0.01 h
0.001
0.000
-0.001
An increase of the
value of the angular
momentum quantum
number slightly
delays the flux (the
increase of the
centrifugal potential
pushes the
wavepacket closer to
the nanotube walls).
L=0
-0.002
Outgoing Flux
-0.003
0.000
-0.001
L=5
-0.002
-0.003
0.000
-0.001
L=10
-0.002
-0.003
0.000
-0.001
L=30
-0.002
-0.003
0
500
1000
1500
Time (atomic units)
2000
Docking Proteina - Molecola piccola
Ligando: acido
Esadecan sulfonico
Recettore: Adipocita
Proteina che lega i lipidi
PDB code: 1LIC
Docking Proteina - Proteina
Barstar
Barnase
1BRS : Barnase + Barstar
AIR POLLUTION SIMULATION
CPM10 Concentration from CHIMERE-aerosols
5 – THE COMPCHEM VIRTUAL
ORGANIZATION
WHAT IS COMPCHEM
• COMPCHEM is a Virtual Organization (VO)
• VOs specialize a segment of the European Grid
for specific purposes
• COMPCHEM is the VO of molecular and
material sciences
• It is based, at present, on a subgrid of more than
8000 cpus (out of the 80000 of EGEE)
THE COMPCHEM APPROACH
1. USER
PASSIVE : Runs other’s programs
ACTIVE: Implements at least one program for personal usage
2. SW PROVIDER (from this level on one can earn credits)
PASSIVE : Implements at least one program for other’s usage
ACTIVE: Management at least one implemented program for
cooperative usage
3. GRID DEPLOYER
PASSIVE : Confers to the infrastructure at least a small cluster
of processors
ACTIVE: Contributes to deploy and manage the structure
4. STAKEHOLDER: Takes part to the development and the
management of the virtual organization
• Further information at http://compchem.unipg.it
6 – FUTURE GUIDELINES
QUANTUM CHEMISTRY DATA
STANDARDIZATION
• The Q5 data model and format was created
for quantum chemistry (electronic structure)
data by the WG 4 of D37
• Create D5 a data model for dynamics (in
particular quantum dynamics)
• Extend the Q5 standard to D5
CREATE AND TEST
WORKFLOWS
• Inter-job workflow
- Wrap the jobs
- Treat the jobs as objects
- Define composition rules and data links
• Intra-job workflows
- Define tools as for inter-job workflows via
directives to be inserted inside the jobs
GETTING READY FOR EGI
• Broaden the molecular and material
science user basis
• Introduce and gridify other suites of
programs
• Carry out massive calculations using
the gridified programs
• Extend the usage of graphical
interfaces and virtual reality either to
define initial conditions or to
represent final observable properties
• Develop a credit system
• Cluster COMPCHEM with other Grid
ACKNOWLEDGEMENTS
• CDK group, Dept. Chemistry, Perugia
(Crocchianti, Faginas, Pacifici, Skouteris,
Costantini, Rampino, Manuali)
• HPC group, Dept. Math&Inf, Perugia
(Gervasi, Tasso)
• Qdyn group, COST D37 (Garcia, Huarte,
Lendvay, Nyman, Balint-Kurti, Farantos)
• Other groups of COST D37