760 research outputs found
Detecting Multiple Communities Using Quantum Annealing on the D-Wave System
A very important problem in combinatorial optimization is partitioning a
network into communities of densely connected nodes; where the connectivity
between nodes inside a particular community is large compared to the
connectivity between nodes belonging to different ones. This problem is known
as community detection, and has become very important in various fields of
science including chemistry, biology and social sciences. The problem of
community detection is a twofold problem that consists of determining the
number of communities and, at the same time, finding those communities. This
drastically increases the solution space for heuristics to work on, compared to
traditional graph partitioning problems. In many of the scientific domains in
which graphs are used, there is the need to have the ability to partition a
graph into communities with the ``highest quality'' possible since the presence
of even small isolated communities can become crucial to explain a particular
phenomenon. We have explored community detection using the power of quantum
annealers, and in particular the D-Wave 2X and 2000Q machines. It turns out
that the problem of detecting at most two communities naturally fits into the
architecture of a quantum annealer with almost no need of reformulation. This
paper addresses a systematic study of detecting two or more communities in a
network using a quantum annealer
Comparative study about the use of two and three-dimensional methods in surface finishing characterization
The increasing number of works related to the surface texture characterization based on 3D information, makes convenient rethinking traditional methods based on two-dimensional measurements from profiles. This work compares results between measurements obtained using two and three-dimensional methods. It uses three kinds of data sources: reference surfaces, randomly generated surfaces and measured. Preliminary results are presented. These results must be completed trying to cover a wider number of possibilities according to the manufacturing process and the measurement instrumentation since results can vary quite significantly between them
Shadow Energy Functionals and Potentials in Born-Oppenheimer Molecular Dynamics
In Born-Oppenheimer molecular dynamics (BOMD) simulations based on density
functional theory (DFT), the potential energy and the interatomic forces are
calculated from an electronic ground state density that is determined by an
iterative self-consistent field optimization procedure, which in practice never
is fully converged. The calculated energies and the forces are therefore only
approximate, which may lead to an unphysical energy drift and instabilities.
Here we discuss an alternative shadow BOMD approach that is based on a backward
error analysis. Instead of calculating approximate solutions for an underlying
exact regular BO potential, we do the opposite. Instead, we calculate the exact
electron density, energies, and forces, but for an underlying approximate
shadow BO potential. In this way the calculated forces are conservative with
respect to the shadow potential and generate accurate molecular trajectories
with long-term energy stability. We show how such shadow BO potentials can be
constructed at different levels of accuracy as a function of the integration
time step, dt, from the minimization of a sequence of systematically
improvable, but approximate, shadow energy density functionals. For each
functional there is a corresponding ground state BO potential. These pairs of
shadow energy functionals and potentials are higher-level generalizations of
the original "0th-level" shadow energy functionals and potentials used in
extended Lagrangian BOMD [Eur. Phys. J. B vol. 94, 164 (2021)]. The proposed
shadow energy functionals and potentials are useful only within this dynamical
framework, where also the electronic degrees of freedom are propagated together
with the atomic positions and velocities. The theory is general and can be
applied to MD simulations using approximate DFT, Hartree-Fock or semi-empirical
methods, as well as to coarse-grained flexible charge models.Comment: 16 pages, 3 figure
The use of the SeDeM diagram expert system for the formulation of Captopril SR matrix tablets by direct compression
The SeDeM Diagram Expert System has been used to study excipients, Captopril and designed formulations for their galenic characterization and to ascertain the critical points of the formula affecting product quality to obtain suitable formulations of Captopril Direct Compression SR Matrix Tablets. The application of the Sedem Diagram Expert System enables selecting excipients with in order to optimize the formula in the preformulation and formulation studies. The methodology is based on the implementation of ICH Q8, establishing the design space of the formula with the use of experiment design, using the parameters of the SeDeM Diagram Expert System as system responses
A fast, dense Chebyshev solver for electronic structure on GPUs
Matrix diagonalization is almost always involved in computing the density
matrix needed in quantum chemistry calculations. In the case of modest matrix
sizes ( 5000), performance of traditional dense diagonalization
algorithms on modern GPUs is underwhelming compared to the peak performance of
these devices. This motivates the exploration of alternative algorithms better
suited to these types of architectures. We newly derive, and present in detail,
an existing Chebyshev expansion algorithm [W. Liang et al, J. Chem. Phys. 2003]
whose number of required matrix multiplications scales with the square root of
the number of terms in the expansion. Focusing on dense matrices of modest
size, our implementation on GPUs results in large speed ups when compared to
diagonalization. Additionally, we improve upon this existing method by
capitalizing on the inherent task parallelism and concurrency in the algorithm.
This improvement is implemented on GPUs by using CUDA and HIP streams via the
MAGMA library and leads to a significant speed up over the serial-only approach
for smaller ( 1000) matrix sizes. Lastly, we apply our technique to a
model system with a high density of states around the Fermi level which
typically presents significant challenges.Comment: Submitted to Journal of Chemical Physics Communication
Are traditional neem extract preparations as efficient as a commercial formulationof azadirachtin A?
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