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Condensed Matter Physics and Materials Science: David M. Ceperley, Duane J. Johnson, Jeongnim Kim

Condensed Matter Physics and Materials Science: David M. Ceperley, Duane J. Johnson, Jeongnim Kim. Solving electronic structure problem is a key step Understand fundamental properties of condensed matter and molecular systems Predict and design new materials and devices

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Condensed Matter Physics and Materials Science: David M. Ceperley, Duane J. Johnson, Jeongnim Kim

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  1. Condensed Matter Physics and Materials Science: David M. Ceperley, Duane J. Johnson, Jeongnim Kim • Solving electronic structure problem is a key step • Understand fundamental properties of condensed matter and molecular systems • Predict and design new materials and devices • Perform multi-scale and multi-physics simulations of complex systems • Very strong economic and intellectual interest • Materials by design: how do we make better batteries, solar cells, strong alloys,  materials for alternative energies? • Can we make predictions when experiment is difficult, costly or impossible? • What is the microscopic origin of superconductivity, magnetism,…? The kernel for these questions: the solution of the many-body Schrödinger equation to high accuracy (0.01 eV for example) and the computation of thermodynamic properties. NCSA Strategic Planning Presentation (April 20,2010)

  2. Bottlenecks/Issues to Achieving Objectives • Need large-scale HPC resources, e.g., • DMC simulations of liquid H2O • Free-energy calculations of hydrogen-helium mixtures • Need efficient software on the current and future architectures • Parallel computing on large-scale SMP clusters • Heterogeneous computing, e.g. GPU clusters • Need collaborative environments • The ES problem requires multi-scale approaches: not a single theoretical framework nor code can handle the complexity and the length- and time-scale of the problems. • Data exchanges between codes and applications are essential. • New discoveries demand modern tools to analyze, archive and mine exploding simulation data. NCSA Strategic Planning Presentation (April 20,2010)

  3. Cyberinfrastructure Challenges in Reaching the Objectives: H2 storage H2 binding energy to benzene Motivations: search for carbon-based hydrogen storage media Challenges: accurate prediction of small binding energies of H2 Ingredients and stages • Structural model from experiments and simple theories • Mean-field electronic structure method to build an optimal many-body wavefunction for quantum Monte Carlo • Diffusion Monte Carlo calculations • Stochastic optimization to determine the bond length and binding energy Beaudet et. al. JCP 129, 164711 (2008) R • High-performance ES software • Data standards for multiple applications • Data analysis and mining tools • Knowledge and education tools 1.53(1) mHa 6.33(15) Bohr NCSA Strategic Planning Presentation (April 20,2010)

  4. Cyberinfrastructure Challenges in Reaching the Objectives: Free energy of H/He mixtures Motivations: model the interior of Jupiter and Saturn Challenges: accurate prediction of EOS and phase diagram of H/He mixtures Ingredients and stages • Born-Oppenheimer MD at various He concentrations, temperatures and pressures • Coupled ion-electron Monte Calro (CIEMC) calculations • Free-energy integration with CIEMC Three views of the interior of Saturn Taken from: Fortney J. J., Science305, 1414 (2004). • High-performance ES software • Data standards for multiple applications • Data analysis and mining tools • Knowledge and education tools • M. Morales et. al., PNAS 106:1324-1329 (2009) NCSA Strategic Planning Presentation (April 20,2010)

  5. Challenges in Reaching the Objectives for the ES community in the US • The US has developed many of the ES methods and numerical algorithms in the last decades and has led the development of HPC software. • Recent Gordon Bell winners include Qbox, DCA++, WL-LSMS. • But, development of production codes has moved to Europe and Asia and very few open-source community codes are originated from the US research institutions. • Why can we capitalize what we have achieved ? • Individual University groups are typically too small. • Code development is not usually considered a first rate research, so non-tenured faculty are not advised to go this route. • Corporate research has vanished. • No supports to maintain software.   NCSA Strategic Planning Presentation (April 20,2010)

  6. Strategic Planning Process We need a coordinated national program to • Develop algorithms and quality software on all computing platforms • Develop data standards and collaboration tools • Maintain software for the current and future architectures • Train developers and users Payoffs in terms of both basic and applied science are potentially very large. NCSA Strategic Planning Presentation (April 20,2010)

  7. Strategic Planning Process NCSA Strategic Planning Presentation (April 20,2010)

  8. Reference slide (Discipline or Topic Reports, Papers, Committee & Workshop Reports, People Consulted……. ) NCSA Strategic Planning Presentation (April 20,2010)

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