5,729 research outputs found
Can Density Matrix Embedding Theory with the Complete Activate Space Self-Consistent Field Solver Describe Single and Double Bond Breaking in Molecular Systems?
Density matrix embedding theory (DMET) [Phys. Rev. Lett.2012, 109, 186404]
has been demonstrated as an efficient wave-function-based embedding method to
treat extended systems. Despite its success in many quantum lattice models, the
extension of DMET to real chemical systems has been tested only on selected
cases. Herein, we introduce the use of the complete active space
self-consistent field (CASSCF) method as a correlated impurity solver for DMET,
leading to a method called CAS-DMET. We test its performance in describing the
dissociation of a H-H single bond in a H10 ring model system and an N=N double
bond in azomethane (CH3-N=N-CH3) and pentyldiazene (CH3(CH2)4-N=NH). We find
that the performance of CAS-DMET is comparable to CASSCF with different active
space choices when single-embedding DMET corresponding to only one embedding
problem for the system is used. When multiple embedding problems are used for
the system, the CAS-DMET is in a good agreement with CASSCF for the geometries
around the equilibrium, but not in equal agreement at bond dissociation.Comment: 28 pages, 9 figures, TOC graphi
A Contraction Theory Approach to Stochastic Incremental Stability
We investigate the incremental stability properties of It\^o stochastic
dynamical systems. Specifically, we derive a stochastic version of nonlinear
contraction theory that provides a bound on the mean square distance between
any two trajectories of a stochastically contracting system. This bound can be
expressed as a function of the noise intensity and the contraction rate of the
noise-free system. We illustrate these results in the contexts of stochastic
nonlinear observers design and stochastic synchronization.Comment: 23 pages, 2 figure
Non-sterile electroweak-scale right-handed neutrinos and the dual nature of the 125-GeV scalar
Can, and under which conditions, the 125-\gev SM-like scalar with the signal
strengths for its decays into , , ,
and being consistent with experiments be accommodated in
models that go beyond the Standard Model? Is it truly what it appears to be,
namely the SM Higgs boson, or could it be quite different? A minimal extension
of the original electroweak-scale right-handed neutrino model, in which
right-handed neutrinos naturally obtain electroweak-scale masses, shows a
scalar spectrum which includes either the 125-\gev SM-like scalar or a scalar
which is quite {\em unlike} that of the Standard Model, both of which
possessing signal strengths compatible with experiment. In other words, the
125-\gev scalar could be an {\em impostor}.Comment: 36 double-column pages, 13 Figures, 9 Tables. Typos corrected.
Version to appear in Nuclear Physics
The Self-Organization of Interaction Networks for Nature-Inspired Optimization
Over the last decade, significant progress has been made in understanding
complex biological systems, however there have been few attempts at
incorporating this knowledge into nature inspired optimization algorithms. In
this paper, we present a first attempt at incorporating some of the basic
structural properties of complex biological systems which are believed to be
necessary preconditions for system qualities such as robustness. In particular,
we focus on two important conditions missing in Evolutionary Algorithm
populations; a self-organized definition of locality and interaction epistasis.
We demonstrate that these two features, when combined, provide algorithm
behaviors not observed in the canonical Evolutionary Algorithm or in
Evolutionary Algorithms with structured populations such as the Cellular
Genetic Algorithm. The most noticeable change in algorithm behavior is an
unprecedented capacity for sustainable coexistence of genetically distinct
individuals within a single population. This capacity for sustained genetic
diversity is not imposed on the population but instead emerges as a natural
consequence of the dynamics of the system
Use of statistical outlier detection method in adaptive evolutionary algorithms
In this paper, the issue of adapting probabilities for Evolutionary Algorithm
(EA) search operators is revisited. A framework is devised for distinguishing
between measurements of performance and the interpretation of those
measurements for purposes of adaptation. Several examples of measurements and
statistical interpretations are provided. Probability value adaptation is
tested using an EA with 10 search operators against 10 test problems with
results indicating that both the type of measurement and its statistical
interpretation play significant roles in EA performance. We also find that
selecting operators based on the prevalence of outliers rather than on average
performance is able to provide considerable improvements to adaptive methods
and soundly outperforms the non-adaptive case
Threading a path to exascale with chemical scissors and integral compressors in a singular manner
Research presented in this dissertation aims at enabling (correlated) fragmentation methods to explore biochemistry and catalysis effects of macrosystems at high levels of accuracy using exascale computing resources. The target is the second-order MollerPlesset perturbation theory (MP2), and MP2 in the FMO framework (FMO/MP2). First, the 2-electron integral bottleneck is addressed by using the resolution-of-the-identity (RI) approximation to reduce the memory storage and the computational cost of the integral transformation from the atomic orbital (AO) to the molecular orbital (MO) basis. The RI approximation is also combined with the singular value decomposition (SVD) to introduce a flexible compression factor that fully controls the accuracy of the integral compression. The RIMP2 energy and analytic energy gradient are implemented in the GAMESS electronic structure program and are parallelized with an efficient hybrid distributed/shared memory model with the support of the MPI and OpenMP APIs. Both the RI-MP2 energy and gradient are interfaced to the FMO framework for large system calculations
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