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## Overview

The fundamental equation governing a non-relativistic quantum system of N particles is the time-dependent Schroedinger Equation [Schroedinger, 1926]. In 1965, Kohn and Sham proposed to replace this original many-body problem by an auxiliary independent-particles problem that can be solved more easily, and formulated the equations of Density Functional Theory (DFT). Solving this simplified problem requires to find the subspace of dimension N spanned by the N eigenfunctions Ψi corresponding to the N lowest eigenvalues εi of a non-linear Hamiltonian operator H determined from first-principles.

From the solution of the Kohn-Sham equations, forces acting on atoms can be derived to optimize geometries and simulate finite temperature phenomenon by (First-Principles) molecular dynamics.

## Application examples

First-Principles molecular dynamics is used in various areas at LLNL such as

- Studying chemical reactions in molecular biology
- Predicting and characterizing structural, electronic and dynamical properties of materials under extreme conditions
- Model interfaces such as
- water-semiconductor interfaces in order to understand the microscopic mechanisms involved in photocatalytic water splitting
- electrode-electrolyte in batteries and capacitors to improve design of electrolyte/anode systems and identify the specific factors that control their performance

### O(N^{3}) complexity problem in Density Functional Theory

- Standard computational algorithms represent the electrons by N quantum wave functions extended over the whole computational domain (see Fig. 1)
- This leads to O(N
^{2}) storage requirements and O(N^{3}) arithmetic operations - Using LLNL powerful super-computers, relatively large problems can be solved (~1000 atoms). But this O(N
^{3}) complexity becomes a critical bottleneck which limits our computational capabilities to study larger and more realistic physical systems, for instance materials with realistic defects and/or realistic concentrations of alloying species

Figure 1. Isosurface of a computed electronic wave function in silicon crystal (64 atoms cell). It shows the boundary of the volume in which one has the highest probability of finding an electron.

### Maximally localized Wannier functions representation

- The electronic structure can be represented by a set of “localized” orbitals with a limited spread independent of the system size (“Maximally Localized Wannier Functions”)
- These functions can be obtained from the eigenfunctions of the Hamiltonian operator by an orthogonal transformation (see Fig. 2)
- This transformation is still an O(N
^{3}) complexity operation, but it shows that a more compact/sparse representation of the electronic structure is possible

Figure 2: Left: Electronic orbital in silicon bulk (contour plot in slicing plane with projections of nearest atoms). A linear combination of eigenfunctions can lead to very localized functions (right).

## O(N) complexity algorithm

The O(N) complexity algorithm for First-Principles Molecular Dynamics we are developing is based on the following ideas:

- Formulate the equations of DFT in terms of general non-orthogonal orbitals (instead of eigenfunctions)
- Represent the occupied electronic orbitals on real-space uniform mesh, using a finite difference discretization
- Compute directly localized orbitals (truncated beyond a cutoff radius) by minimizing an energy functional with localization constraints that only marginally affect accuracy (Figure 3 and 4)
- Compute approximately the selected elements of the inverse of the sparse Gram (overlap) matrix that enter the equations of DFT for non-orthogonal orbitals, by inverting principal submatrices of the global Gram matrix (see references [6] and [7])

Figure 3: strictly localized orbital in silicon crystal directly optimized on real-space mesh with localization constraints (contour plot in slicing plane)

Figure 4: 2 localized orbitals in silicon nanowire (slice perpendicular to wire axis)

### Overcoming the cubic scaling wall

For molecular systems with a band gap, we have demonstrated that this “localized orbitals” technique becomes more efficient than the traditional Plane Waves approach for physical systems larger than ~500 atoms. We have also demonstrated its scalability beyond 100,000 MPI tasks, for molecular systems made of over 100,000 atoms.

Figure 5: comparing computer time for the standard Plane Waves approach (QBox code) and our linear scaling algorithm for a quantum simulation of liquid water (from Ref. [5])

Figure 6: Weak scaling study: time-to-solution for one molecular dynamics time-step for liquid water on IBM/BGQ

## Software: MGmol

- Authors: J.-L. Fattebert and D. Osei-Kuffuor
- O(N) First-Principles Molecular Dynamics
- ~95K lines C++
- Parallel: using MPI, scales beyond 100,000 CPUs
- Based on domain decomposition with nonoverlaping localized orbitals treated in parallel

## Team

- Jean-Luc Fattebert (PI)
- Daniel Osei-Kuffuor

## Publications

- J.-L. Fattebert, J. Bernholc, Towards grid-based O(N) density-functional theory methods: optimized non-orthogonal orbitals and multigrid acceleration, Phys. Rev. B 62, no 3, 1713-1722 (2000).
- M. Buongiorno Nardelli, J.-L. Fattebert and J. Bernholc, O(N) real-space method for ab initio quantum transport calculations: Applications to carbon nanotube-metal contacts, Phys. Rev. B 64, 245423 (2001).
- F. Gygi, J.-L. Fattebert and E. Schwegler, Computation of Maximally Localized Wannier Functions using a Simultaneous Diagonalization Algorithm, Comput. Phys. Comm., 155, no 1 (2003), pp. 1-6.
- J.-L. Fattebert and F. Gygi, Linear scaling first-principles molecular dynamics with controlled accuracy, Comput. Phys. Comm., 162, no 1 (2004), pp. 24-36.
- J.-L. Fattebert and F. Gygi, Linear scaling first-principles molecular dynamics with plane-waves accuracy, Phys. Rev. B, 73, (2006), 115124.
- D. Osei-Kuffuor and J.-L. Fattebert, Accurate and Scalable O(N) Algorithm for First-Principles Molecular-Dynamics Computations on Large Parallel Computers, Phys. Rev. Lett. 112 (2014), 046401
- Daniel Osei-Kuffuor, Jean-Luc Fattebert, A Scalable O(N) Algorithm for Large-Scale Parallel First-Principles Molecular Dynamics Simulations, SIAM J. Scientific Computing 36(4) (2014)

## Contact Information

For further information, please contact Jean-Luc Fattebert at fattebert1@llnl.gov or at ++1 925 424 5296

Work performed under the auspices of the U. S. Department of Energy by Lawrence Livermore National Security, LLC under Contract DE-AC52-07NA27344. This is LLNL report UCRL-TR-228407.