Software Project Brent Fultz California Institute of Technology Software Functions Full Experiment Simulations Inversions of Dynamics Models.

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Presentation transcript:

Software Project Brent Fultz California Institute of Technology Software Functions Full Experiment Simulations Inversions of Dynamics Models

Discussions and Planning Meetings Sept. 24, 2001 meeting at Argonne with video to Oak Ridge, McMaster U., Caltech Nov. 29, 2001 small meeting at Caltech with postdoc interview. March 15, 2002 Software Workshop

Software Roadmap v. 1.0

Software Lifetime Exceeds Hardware Lifetime main () { FILE *fp; /*MEM pair 7/19/89 B. Fultz This program generates kinetic paths in a binary alloy with B2 structure. The level of approximation in the kinetic equations is equivalent to the pair (Bethe) approximation in thermodynamics. Note date above. Code runs just fine, migrated through workstations: austrl, ulysses, hyperfine1, hyperfine2, ARCS

Software Engineering Reality: Cannot rewrite all codes in one language such as C++, Java or FORTRAN90 Need New Approach: Modular software objects connected by object-oriented scripting language Different high-level scripts for different experimenters Span from detectors to dispersions on common software framework Python

Writing Python Bindings For example, given a solver routine such as and a wrapper double adlib::StableTimeStep(); char pyadlib_stableTimestep__name__[] = “stableTimestep”; PyObject * pyaldib_stableTimestep(PyObject *, PyObject * args) { double dt = adlib::StableTimeStep(“deformation”); return Py_BuildValue(“d”, dt); } dt = pyadlib.stableTimestep() one can place the result of the routine in a python variable

Software for Data Acquisition

Within 2 Hours Discovery! A feature in the data! Is it magnon, phonon, spurion?

Software for Data Analysis Before Publication Relate Data to Dynamics Model

Summary: ARCS Software Tools Are Required During Data Acquisition Users want software like a smart manservant (to take initiative, but with discretion, and no pay) ARCS needs an engineer to consult on the “user experience” Software for Data Analysis Enables New Science: Full Experiment Simulations (connect to theory) Analytical Inversions of Data Single Crystal Data

S(Q,E) from TOF Data Bare minimum for users to take home General – model independent 3D single crystals, with real-time decisions on sample orientation Absolute units [barns, meV, sr, atom, and Å-1] Calibration Handle resolution and background Data visualization

Working with S(Q,E) Visualization Comparisons of data sets, arithmetic operations Analytical results from the theory of thermal neutron scattering by condensed matter Inversions of measured data to obtain force constants or exchange energies. Data mining — e.g., recognition of dispersions

Full Experiment Simulations

Neutron Wave (or wavepacket)

EAM Simulations of Phonon DOS from Ni 3 Al Large molecular dynamics model. Computationally challenging. Calculated: PRB 57 (2): JAN

Scattering Simulations of Local Magnetic Dynamics in a Disordered System

Model Inversions — Incoherent Inelastic Scattering from 57 Fe Counts Energy (meV) 3 GPa 12 GPa 17 GPa Nuclear resonant scattering of x-rays by 57 Fe at APS 3ID Pd 3 57 Fe in diamond-anvil cell Same analysis as incoherent neutron scattering Invert data from 57 Fe to obtain full lattice dynamics

Result of Inversion — Phonon Partial DOS Curves

Phonon Partial DOS Curves Under Pressure Energy (meV) 0 GPa3 GPa17 GPa Fe Pd

Result of Inversion — Radial 1nn Force Constants vs. Pressure Radial 1nn Force Constant (N/m) Pressure (GPa) Pd-Fe Pd-Pd L1 2 Pd 3 Fe Note: Pd-Pd force constants from 57 Fe scattering !

Fifty initial conditions for Pd 3 Fe Try different numbers of nearest neighbors Quality of fit to experimental data

1nn Pd-Pd and Pd-Fe Pd 3 Fe force constants from inversions

A case of bad 1nn Pd 3 Fe force constants

Future -- S(Q,E) inversions using coherent scattering Inversions of incoherent inelastic scattering from 57 Fe overcame the neutron-weighting problem in Fe alloys. More information is available through the Q- or Q-dependence of coherent scattering.

S(Q,E) inversions using coherent scattering Polycrystalline Ni 3 Al measured at HFIR with 4 values of Q (We were looking at order-disorder phenomena...) Calculated incoherent scattering with Born-von Karman code. Calculated coherent scattering from all orientations of crystallites w.r.t. Q Coherent scattering was considered a nuisance to be overcome so we could produce a phonon DOS.

S(Q,E) inversions using coherent scattering Polycrystalline Ni 3 Al measured at HFIR with 4 values of Q

S(Q,E) inversions using coherent scattering Isotropic average of S(Q,E) of polycrystalline Ce, a coherent scatterer.

Summary A roadmap exists for the ARCS software project, but it is still subject to change. Individual roads are modules connected by Python: S(Q,E) visualization fits to models full experiment simulation Work is underway on phonon dynamics inversions incoherent scattering is useful coherent scattering should be even better The year 2002 will be an assessment of existing packages. Please let us know your views!