4,139 research outputs found
Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learning
Computational study of molecules and materials from first principles is a cornerstone of physics, chemistry and materials science, but limited by the cost of accurate and precise simulations. In settings involving many simulations, machine learning can reduce these costs, sometimes by orders of magnitude, by interpolating between reference simulations. This requires representations that describe any molecule or material and support interpolation. We review, discuss and benchmark state-of-the-art representations and relations between them, including smooth overlap of atomic positions, many-body tensor representation, and symmetry functions. For this, we use a unified mathematical framework based on many-body functions, group averaging and tensor products, and compare energy predictions for organic molecules, binary alloys and Al-Ga-In sesquioxides in numerical experiments controlled for data distribution, regression method and hyper-parameter optimization
Constituent and current quark masses at low chiral energies
Light constituent quark masses and the corresponding dynamical quark masses
are determined by data, the Quark-Level Linear Model, and infrared
QCD. This allows to define effective nonstrange and strange current quark
masses which reproduce the experimental pion and kaon masses very accurately,
by simple additivity. Moreover, the masses of the light scalar mesons
and can be obtained straightforwardly from the
constituent quark masses. In contrast, the usual nonstrange and strange current
quark masses employed by Chiral Perturbation Theory do not allow a simple
quantitative explanation of the pion and kaon masses.Comment: 5 pages, EPL style, accepted for publication in Europhys. Let
A performance comparison of fullband and different subband adaptive equalisers
We present two different fractionally spaced (FS) equalisers based on subband methods, with the aim of reducing the computational complexity and increasing the convergence rate of a standard fullband FS equaliser. This is achieved by operating in decimated subbands; at a considerably lower update rate and by exploiting the prewhitening effect that a filter bank has on the considerable spectral dynamics of a signal received through a severely distorting channel. The two presented subband structures differ in their level of realising the feedforward and feedback part of the equaliser in the subband domain, with distinct impacts on the updating. Simulation results pinpoint the faster convergence at lower cost for the proposed subband equalisers
Hospital Cost and Efficiency Under Per Service and Per Case Payment in Maryland: A Tale of the Carrot and the Stick
The simultaneous operation of per case and per servicepayment systems in Maryland, and the varying levels of stringency used in setting per case rates allows comparison of effects of differing incentive structures on hospital costs. This paper presents such a comparison with 1977-1981 data. Cost per case and total cost regressions show evidence of lower costs only when per case payment limits are very stringent. Positive net revenue incentives appear insufficient to induce reductions in length of stay and in ancillary services use. Our results suggest these changes in medical practice patterns are more likely under the threat of financial losses.
Likelihood Consensus and Its Application to Distributed Particle Filtering
We consider distributed state estimation in a wireless sensor network without
a fusion center. Each sensor performs a global estimation task---based on the
past and current measurements of all sensors---using only local processing and
local communications with its neighbors. In this estimation task, the joint
(all-sensors) likelihood function (JLF) plays a central role as it epitomizes
the measurements of all sensors. We propose a distributed method for computing,
at each sensor, an approximation of the JLF by means of consensus algorithms.
This "likelihood consensus" method is applicable if the local likelihood
functions of the various sensors (viewed as conditional probability density
functions of the local measurements) belong to the exponential family of
distributions. We then use the likelihood consensus method to implement a
distributed particle filter and a distributed Gaussian particle filter. Each
sensor runs a local particle filter, or a local Gaussian particle filter, that
computes a global state estimate. The weight update in each local (Gaussian)
particle filter employs the JLF, which is obtained through the likelihood
consensus scheme. For the distributed Gaussian particle filter, the number of
particles can be significantly reduced by means of an additional consensus
scheme. Simulation results are presented to assess the performance of the
proposed distributed particle filters for a multiple target tracking problem
Adaptive Positive Position Feedback Control of Flexible Aircraft Structures Using Piezoelectric Actuators
Buffet Adaptively Managed Fin (BAMF) focused on vibrations due to the interaction of aerodynamic forces with aircraft structure. Past failures of F-16 ventral fins due to vibrations provided grounds for control research. The fin used had piezoelectric patches as collocated sensors/actuators. A custom amplifier and transformer were restructured into a system that could safely and reliably run, and adaptive software was created to address issues of system plant changes. Generating a PSD from the fin sensors, the highest peaks were assumed to represent the low damped vibration modes. A PPF controller for each mode was designed and control signals were sent to the fin actuators. Limited data were collected in a wind tunnel behind a custom system that caused buffet by varying vortex strength/shedding frequencies from pods upstream of the fin. While minimal testing was accomplished to optimize gains, the system showed significant PSD peak reductions for the first three modes of the fin up to -14.9, -15.3, and -16.4 dB, respectively. The system maintained stability and effective control even when both sensor input and controller output were saturated
Light Higgs bosons from a strongly interacting Higgs sector
The mass and the decay width of a Higgs boson in the minimal standard model
are evaluated by a variational method in the limit of strong self-coupling
interaction. The non-perturbative technique provides an interpolation scheme
between strong-coupling regime and weak-coupling limit where the standard
perturbative results are recovered. In the strong-coupling limit the physical
mass and the decay width of the Higgs boson are found to be very small as a
consequence of mass renormalization. Thus it is argued that the eventual
detection of a light Higgs boson would not rule out the existence of a strongly
interacting Higgs sector.Comment: 2 figure
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