54,407 research outputs found
A Shift Selection Strategy for Parallel Shift-invert Spectrum Slicing in Symmetric Self-consistent Eigenvalue Computation
© 2020 ACM. The central importance of large-scale eigenvalue problems in scientific computation necessitates the development of massively parallel algorithms for their solution. Recent advances in dense numerical linear algebra have enabled the routine treatment of eigenvalue problems with dimensions on the order of hundreds of thousands on the world's largest supercomputers. In cases where dense treatments are not feasible, Krylov subspace methods offer an attractive alternative due to the fact that they do not require storage of the problem matrices. However, demonstration of scalability of either of these classes of eigenvalue algorithms on computing architectures capable of expressing massive parallelism is non-trivial due to communication requirements and serial bottlenecks, respectively. In this work, we introduce the SISLICE method: a parallel shift-invert algorithm for the solution of the symmetric self-consistent field (SCF) eigenvalue problem. The SISLICE method drastically reduces the communication requirement of current parallel shift-invert eigenvalue algorithms through various shift selection and migration techniques based on density of states estimation and k-means clustering, respectively. This work demonstrates the robustness and parallel performance of the SISLICE method on a representative set of SCF eigenvalue problems and outlines research directions that will be explored in future work
Solving eigenvalue problems on curved surfaces using the Closest Point Method
Eigenvalue problems are fundamental to mathematics and science. We present a
simple algorithm for determining eigenvalues and eigenfunctions of the
Laplace--Beltrami operator on rather general curved surfaces. Our algorithm,
which is based on the Closest Point Method, relies on an embedding of the
surface in a higher-dimensional space, where standard Cartesian finite
difference and interpolation schemes can be easily applied. We show that there
is a one-to-one correspondence between a problem defined in the embedding space
and the original surface problem. For open surfaces, we present a simple way to
impose Dirichlet and Neumann boundary conditions while maintaining second-order
accuracy. Convergence studies and a series of examples demonstrate the
effectiveness and generality of our approach
Spectral-based Propagation Schemes for Time-Dependent Quantum Systems with Application to Carbon Nanotubes
Effective modeling and numerical spectral-based propagation schemes are
proposed for addressing the challenges in time-dependent quantum simulations of
systems ranging from atoms, molecules, and nanostructures to emerging
nanoelectronic devices. While time-dependent Hamiltonian problems can be
formally solved by propagating the solutions along tiny simulation time steps,
a direct numerical treatment is often considered too computationally demanding.
In this paper, however, we propose to go beyond these limitations by
introducing high-performance numerical propagation schemes to compute the
solution of the time-ordered evolution operator. In addition to the direct
Hamiltonian diagonalizations that can be efficiently performed using the new
eigenvalue solver FEAST, we have designed a Gaussian propagation scheme and a
basis transformed propagation scheme (BTPS) which allow to reduce considerably
the simulation times needed by time intervals. It is outlined that BTPS offers
the best computational efficiency allowing new perspectives in time-dependent
simulations. Finally, these numerical schemes are applied to study the AC
response of a (5,5) carbon nanotube within a 3D real-space mesh framework
Solving polynomial eigenvalue problems by means of the Ehrlich-Aberth method
Given the matrix polynomial , we
consider the associated polynomial eigenvalue problem. This problem, viewed in
terms of computing the roots of the scalar polynomial , is treated
in polynomial form rather than in matrix form by means of the Ehrlich-Aberth
iteration. The main computational issues are discussed, namely, the choice of
the starting approximations needed to start the Ehrlich-Aberth iteration, the
computation of the Newton correction, the halting criterion, and the treatment
of eigenvalues at infinity. We arrive at an effective implementation which
provides more accurate approximations to the eigenvalues with respect to the
methods based on the QZ algorithm. The case of polynomials having special
structures, like palindromic, Hamiltonian, symplectic, etc., where the
eigenvalues have special symmetries in the complex plane, is considered. A
general way to adapt the Ehrlich-Aberth iteration to structured matrix
polynomial is introduced. Numerical experiments which confirm the effectiveness
of this approach are reported.Comment: Submitted to Linear Algebra App
Diagonalization- and Numerical Renormalization-Group-Based Methods for Interacting Quantum Systems
In these lecture notes, we present a pedagogical review of a number of
related {\it numerically exact} approaches to quantum many-body problems. In
particular, we focus on methods based on the exact diagonalization of the
Hamiltonian matrix and on methods extending exact diagonalization using
renormalization group ideas, i.e., Wilson's Numerical Renormalization Group
(NRG) and White's Density Matrix Renormalization Group (DMRG). These methods
are standard tools for the investigation of a variety of interacting quantum
systems, especially low-dimensional quantum lattice models. We also survey
extensions to the methods to calculate properties such as dynamical quantities
and behavior at finite temperature, and discuss generalizations of the DMRG
method to a wider variety of systems, such as classical models and quantum
chemical problems. Finally, we briefly review some recent developments for
obtaining a more general formulation of the DMRG in the context of matrix
product states as well as recent progress in calculating the time evolution of
quantum systems using the DMRG and the relationship of the foundations of the
method with quantum information theory.Comment: 51 pages; lecture notes on numerically exact methods. Pedagogical
review appearing in the proceedings of the "IX. Training Course in the
Physics of Correlated Electron Systems and High-Tc Superconductors", Vietri
sul Mare (Salerno, Italy, October 2004
Unconditional Stability for Multistep ImEx Schemes: Theory
This paper presents a new class of high order linear ImEx multistep schemes
with large regions of unconditional stability. Unconditional stability is a
desirable property of a time stepping scheme, as it allows the choice of time
step solely based on accuracy considerations. Of particular interest are
problems for which both the implicit and explicit parts of the ImEx splitting
are stiff. Such splittings can arise, for example, in variable-coefficient
problems, or the incompressible Navier-Stokes equations. To characterize the
new ImEx schemes, an unconditional stability region is introduced, which plays
a role analogous to that of the stability region in conventional multistep
methods. Moreover, computable quantities (such as a numerical range) are
provided that guarantee an unconditionally stable scheme for a proposed
implicit-explicit matrix splitting. The new approach is illustrated with
several examples. Coefficients of the new schemes up to fifth order are
provided.Comment: 33 pages, 7 figure
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