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 $^{14}$Be. The utility of high-energy proton radiative capture is illustrated using a study of the $^{6}$He(p,$\gamma$) 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 ($^{4}$n) liberated in the breakup of $^{14}$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 $\sim$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 $N$-representability conditions. Recently, the topic of pure-state $N$-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 $N$-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