12,158 research outputs found
Clustering and Correlations at the Neutron Dripline
Some recent experimental studies of clustering and correlations within very
neutron-rich light nuclei are reviewed. In particular, the development of the
novel probes of neutron-neutron interferometry and Dalitz-plot analyses is
presented through the example of the dissociation of the two-neutron halo
system Be. The utility of high-energy proton radiative capture is
illustrated using a study of the He(p,) reaction. A new approach
to the production and detection of bound neutron clusters is also described,
and the observation of events with the characteristics expected for
tetraneutrons (n) liberated in the breakup of Be is discussed. The
prospects for future work, including systems beyond the neutron dripline, are
briefly outlined.Comment: Invited contribution to a topical issue on Exotic Nuclei of Les
Comptes Rendus de l'Academie des Sciences Paris, Serie IV. 29 pages,11
figures (format RevTex preprint
Benchmark calculations for reduced density-matrix functional theory
Reduced density-matrix functional theory (RDMFT) is a promising alternative
approach to the problem of electron correlation. Like standard density
functional theory, it contains an unknown exchange-correlation functional, for
which several approximations have been proposed in the last years. In this
article, we benchmark some of these functionals in an extended set of molecules
with respect to total and atomization energies. Our results show that the most
recent RDMFT functionals give very satisfactory results compared to more
involved quantum chemistry and density functional approaches.Comment: 17 pages, 1 figur
mfEGRA: Multifidelity Efficient Global Reliability Analysis through Active Learning for Failure Boundary Location
This paper develops mfEGRA, a multifidelity active learning method using
data-driven adaptively refined surrogates for failure boundary location in
reliability analysis. This work addresses the issue of prohibitive cost of
reliability analysis using Monte Carlo sampling for expensive-to-evaluate
high-fidelity models by using cheaper-to-evaluate approximations of the
high-fidelity model. The method builds on the Efficient Global Reliability
Analysis (EGRA) method, which is a surrogate-based method that uses adaptive
sampling for refining Gaussian process surrogates for failure boundary location
using a single-fidelity model. Our method introduces a two-stage adaptive
sampling criterion that uses a multifidelity Gaussian process surrogate to
leverage multiple information sources with different fidelities. The method
combines expected feasibility criterion from EGRA with one-step lookahead
information gain to refine the surrogate around the failure boundary. The
computational savings from mfEGRA depends on the discrepancy between the
different models, and the relative cost of evaluating the different models as
compared to the high-fidelity model. We show that accurate estimation of
reliability using mfEGRA leads to computational savings of 46% for an
analytic multimodal test problem and 24% for a three-dimensional acoustic horn
problem, when compared to single-fidelity EGRA. We also show the effect of
using a priori drawn Monte Carlo samples in the implementation for the acoustic
horn problem, where mfEGRA leads to computational savings of 45% for the
three-dimensional case and 48% for a rarer event four-dimensional case as
compared to single-fidelity EGRA
Schwinger-Dyson equations and the quark-antiquark static potential
In lattice QCD, a confining potential for a static quark-antiquark pair can
be computed with the Wilson loop technique. This potential, dominated by a
linear potential at moderate distances, is consistent with the confinement with
a flux tube, an extended and scalar system also directly observable in lattice
QCD. Quantized flux tubes have also been observed in another class of
confinement, the magnetic confinement in type II superconductors. On the other
hand the solution of Schwinger Dyson Equations, say with the Landau gauge
fixing and the truncation of the series of Feynman diagrams, already at the
rainbow level for the self energy and at the ladder level for the Bethe
Salpeter equation, provides a signal of a possible inverse quartic potential in
momentum space derived from one gluon and one ghost exchange, consistent with
confinement. Here we address the successes, difficulties and open problems of
the matching of these two different perspectives of confinement, the
Schwinger-Dyson perspective versus the flux tube perspective.Comment: 12 pages, 18 figures; talk presented at QCD-TNT, Trento, 7-11 sep
200
Generalized Pauli constraints in reduced density matrix functional theory
Functionals of the one-body reduced density matrix (1-RDM) are routinely
minimized under Coleman's ensemble -representability conditions. Recently,
the topic of pure-state -representability conditions, also known as
generalized Pauli constraints, received increased attention following the
discovery of a systematic way to derive them for any number of electrons and
any finite dimensionality of the Hilbert space. The target of this work is to
assess the potential impact of the enforcement of the pure-state conditions on
the results of reduced density-matrix functional theory calculations. In
particular, we examine whether the standard minimization of typical 1-RDM
functionals under the ensemble -representability conditions violates the
pure-state conditions for prototype 3-electron systems. We also enforce the
pure-state conditions, in addition to the ensemble ones, for the same systems
and functionals and compare the correlation energies and optimal occupation
numbers with those obtained by the enforcement of the ensemble conditions
alone
Bioprocess microfluidics: applying microfluidic devices for bioprocessing
Scale-down approaches have long been applied in bioprocessing to resolve scale-up problems. Miniaturized bioreactors have thrived as a tool to obtain process relevant data during early-stage process development. Microfluidic devices are an attractive alternative in bioprocessing development due to the high degree of control over process variables afforded by the laminar flow, and the possibility to reduce time and cost factors. Data quality obtained with these devices is high when integrated with sensing technology and is invaluable for scale-translation and to assess the economical viability of bioprocesses. Microfluidic devices as upstream process development tools have been developed in the area of small molecules, therapeutic proteins, and cellular therapies. More recently, they have also been applied to mimic downstream unit operations
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