Electric control of collective atomic coherence in an Erbium doped solid

We demonstrate fast and accurate control of the evolution of collective atomic coherences in an Erbium doped solid using external electric fields. This is achieved by controlling the inhomogeneous broadening of Erbium ions emitting at 1536 nm using an electric field gradient and the linear Stark effect. The manipulation of atomic coherence is characterized with the collective spontaneous emission (optical free induction decay) emitted by the sample after an optical excitation, which does not require any previous preparation of the atoms. We show that controlled dephasing and rephasing of the atoms by the electric field result in collapses and revivals of the optical free induction decay. Our results show that the use of external electric fields does not introduce any substantial additional decoherence and enables the manipulation of collective atomic coherence with a very high degree of precision on the time scale of tens of ns. This provides an interesting resource for photonic quantum state storage and quantum state manipulation.Comment: 10 pages, 5 figure

Network Inference via the Time-Varying Graphical Lasso

Many important problems can be modeled as a system of interconnected entities, where each entity is recording time-dependent observations or measurements. In order to spot trends, detect anomalies, and interpret the temporal dynamics of such data, it is essential to understand the relationships between the different entities and how these relationships evolve over time. In this paper, we introduce the time-varying graphical lasso (TVGL), a method of inferring time-varying networks from raw time series data. We cast the problem in terms of estimating a sparse time-varying inverse covariance matrix, which reveals a dynamic network of interdependencies between the entities. Since dynamic network inference is a computationally expensive task, we derive a scalable message-passing algorithm based on the Alternating Direction Method of Multipliers (ADMM) to solve this problem in an efficient way. We also discuss several extensions, including a streaming algorithm to update the model and incorporate new observations in real time. Finally, we evaluate our TVGL algorithm on both real and synthetic datasets, obtaining interpretable results and outperforming state-of-the-art baselines in terms of both accuracy and scalability

Practical Bayesian Modeling and Inference for Massive Spatial Datasets On Modest Computing Environments

With continued advances in Geographic Information Systems and related computational technologies, statisticians are often required to analyze very large spatial datasets. This has generated substantial interest over the last decade, already too vast to be summarized here, in scalable methodologies for analyzing large spatial datasets. Scalable spatial process models have been found especially attractive due to their richness and flexibility and, particularly so in the Bayesian paradigm, due to their presence in hierarchical model settings. However, the vast majority of research articles present in this domain have been geared toward innovative theory or more complex model development. Very limited attention has been accorded to approaches for easily implementable scalable hierarchical models for the practicing scientist or spatial analyst. This article is submitted to the Practice section of the journal with the aim of developing massively scalable Bayesian approaches that can rapidly deliver Bayesian inference on spatial process that are practically indistinguishable from inference obtained using more expensive alternatives. A key emphasis is on implementation within very standard (modest) computing environments (e.g., a standard desktop or laptop) using easily available statistical software packages without requiring message-parsing interfaces or parallel programming paradigms. Key insights are offered regarding assumptions and approximations concerning practical efficiency.Comment: 20 pages, 4 figures, 2 table

Afghanistan: Final Assessment Report

In December 2005 the European Commission (EC) performed an Assessment Mission with the overall objective of assisting the EC in designing its strategy to support the government of Afghanistan in implementing its Mine Action and Ammunition Stockpile Destruction programmes. The objective of the mission was to sketch out a strategy for landmine and ammunition stockpile destruction and contribute to its implementation

New term in effective field theory at fixed topology

A random matrix model for lattice QCD which takes into account the positive definite nature of the Wilson term is introduced. The corresponding effective theory for fixed index of the Wilson Dirac operator is derived to next to leading order. It reveals a new term proportional to the topological index of the Wilson Dirac operator and the lattice spacing. The new term appears naturally in a fixed index spurion analysis. The spurion approach reveals that the term is the first in a new family of such terms and that equivalent terms are relevant for the effective theory of continuum QCD.Comment: 22 pages, 2 figures, version to appear in PR

The Pharmacopsychometric Triangle to Illustrate the Effectiveness of T-PEMF Concomitant with Antidepressants in Treatment Resistant Patients: A Double-Blind, Randomised, Sham-Controlled Trial Revisited with Focus on the Patient-Reported Outcomes

Background. Our T-PEMF trial has been revisited with focus on the pharmacopsychometric triangle in which effect size is used when comparing wanted versus unwanted clinical effects and quality of life as outcomes. In this analysis, we have especially focused on the self-reported HAM-D6. Methods. The antidepressive medication which the patients were resistant to was kept unchanged during the five weeks of active versus sham T-PEMF. Results. In total 21, patients received active T-PEMF, and 19 patients received sham T-PEMF. The effect size was 1.02 and 0.90, respectively, on HAM-D6 and HAM-D6-S. Concerning side effects, the active T-PEMF reduced the baseline score on concentration problems with an effect size of 0.44 while inducing more autonomic symptoms than sham T-PEMF with an effect size of −0.41. The advantage of active over sham T-PEMF obtained an effect size of 0.48. Conclusion. Active T-PEMF was found superior to sham T-PEMF within the pharmacopsychometric triangle with a clinically significant effect size level above 0.40

Equilibration through local information exchange in networks

We study the equilibrium states of energy functions involving a large set of real variables, defined on the links of sparsely connected networks, and interacting at the network nodes, using the cavity and replica methods. When applied to the representative problem of network resource allocation, an efficient distributed algorithm is devised, with simulations showing full agreement with theory. Scaling properties with the network connectivity and the resource availability are found.Comment: v1: 7 pages, 1 figure, v2: 4 pages, 2 figures, simplified analysis and more organized results, v3: minor change

The physical determinants of the thickness of lamellar polymer crystals

Based upon kinetic Monte Carlo simulations of crystallization in a simple polymer model we present a new picture of the mechanism by which the thickness of lamellar polymer crystals is constrained to a value close to the minimum thermodynamically stable thickness. This description contrasts with those given by the two dominant theoretical approaches.Comment: 4 pages, 4 figures, revte