Evidence for a singularity in ideal magnetohydrodynamics: implications for fast reconnection

Numerical evidence for a finite-time singularity in ideal 3D magnetohydrodynamics (MHD) is presented. The simulations start from two interlocking magnetic flux rings with no initial velocity. The magnetic curvature force causes the flux rings to shrink until they come into contact. This produces a current sheet between them. In the ideal compressible calculations, the evidence for a singularity in a finite time $t_c$ is that the peak current density behaves like $|J|_\infty \sim 1/(t_c-t)$ for a range of sound speeds (or plasma betas). For the incompressible calculations consistency with the compressible calculations is noted and evidence is presented that there is convergence to a self-similar state. In the resistive reconnection calculations the magnetic helicity is nearly conserved and energy is dissipated.Comment: 4 pages, 4 figure

Robust Online Hamiltonian Learning

In this work we combine two distinct machine learning methodologies, sequential Monte Carlo and Bayesian experimental design, and apply them to the problem of inferring the dynamical parameters of a quantum system. We design the algorithm with practicality in mind by including parameters that control trade-offs between the requirements on computational and experimental resources. The algorithm can be implemented online (during experimental data collection), avoiding the need for storage and post-processing. Most importantly, our algorithm is capable of learning Hamiltonian parameters even when the parameters change from experiment-to-experiment, and also when additional noise processes are present and unknown. The algorithm also numerically estimates the Cramer-Rao lower bound, certifying its own performance.Comment: 24 pages, 12 figures; to appear in New Journal of Physic

On Breakdown Criteria for Nonvacuum Einstein Equations

The recent "breakdown criterion" result of S. Klainerman and I. Rodnianski stated roughly that an Einstein-vacuum spacetime, given as a CMC foliation, can be further extended in time if the second fundamental form and the derivative of the lapse of the foliation are uniformly bounded. This theorem and its proof were extended to Einstein-scalar and Einstein-Maxwell spacetimes in the author's Ph.D. thesis. In this paper, we state the main results of the thesis, and we summarize and discuss their proofs. In particular, we will discuss the various issues resulting from nontrivial Ricci curvature and the coupling between the Einstein and the field equations.Comment: 62 pages This version: corrected minor typos, expanded Section 6 (geometry of null cones

Controlling magnetic order and quantum disorder in molecule-based magnets.

We investigate the structural and magnetic properties of two molecule-based magnets synthesized from the same starting components. Their different structural motifs promote contrasting exchange pathways and consequently lead to markedly different magnetic ground states. Through examination of their structural and magnetic properties we show that [Cu(pyz)(H 2 O)(gly) 2 ](ClO 4 ) 2 may be considered a quasi-one-dimensional quantum Heisenberg antiferromagnet whereas the related compound [Cu(pyz)(gly)](ClO 4 ) , which is formed from dimers of antiferromagnetically interacting Cu 2+ spins, remains disordered down to at least 0.03 K in zero field but shows a field-temperature phase diagram reminiscent of that seen in materials showing a Bose-Einstein condensation of magnons

Controlling magnetic order and quantum disorder in molecule-based magnets

We investigate the structural and magnetic properties of two molecule-based magnets synthesized from the same starting components. Their different structural motifs promote contrasting exchange pathways and consequently lead to markedly different magnetic ground states. Through examination of their structural and magnetic properties we show that [Cu(pyz)(H2O)(gly)2](ClO4)2 may be considered a quasi-one-dimensional quantum Heisenberg antiferromagnet whereas the related compound [Cu(pyz)(gly)](ClO4), which is formed from dimers of antiferromagnetically interacting Cu2+ spins, remains disordered down to at least 0.03 K in zero field but shows a field-temperature phase diagram reminiscent of that seen in materials showing a Bose-Einstein condensation of magnons

A Randomized Controlled Trial of Extended Brief Intervention for Alcohol-Dependent Patients in an Acute Hospital Setting

To determine whether alcohol-dependent patients in a hospital setting benefit from extended brief interventions (EBI) delivered by an Alcohol Specialist Nurse. Methods Alcohol-dependent patients recruited via screening at the emergency department (ED) (n = 267), whether or not admitted to hospital, were randomized to EBI (up to six counselling sessions offered) or control. At 6 months, 84.2% of patients were assessed by a researcher blinded to the intervention. The primary outcome was a fall in Severity of Alcohol Dependence Questionnaire. Results There was no difference between groups in the primary outcome [odds ratio (OR) 1.02; 95% confidence interval (CI): 0.38, 2.75, P = 0.97]. Secondary outcomes including alcohol consumption and readiness to change did not show a significant difference between groups. However, all secondary outcome measures improved, on average, in both arms. Conclusions Although EBI can be delivered in an ED or inpatient setting, it was not shown to be an advantage over screening and usual management (which included advice on alternative services), with patients in both groups showing an average improvement

Modeling healthcare authorization and claim submissions using the openEHR dual-model approach

<p>Abstract</p> <p>Background</p> <p>The TISS standard is a set of mandatory forms and electronic messages for healthcare authorization and claim submissions among healthcare plans and providers in Brazil. It is not based on formal models as the new generation of health informatics standards suggests. The objective of this paper is to model the TISS in terms of the openEHR archetype-based approach and integrate it into a patient-centered EHR architecture.</p> <p>Methods</p> <p>Three approaches were adopted to model TISS. In the first approach, a set of archetypes was designed using ENTRY subclasses. In the second one, a set of archetypes was designed using exclusively ADMIN_ENTRY and CLUSTERs as their root classes. In the third approach, the openEHR ADMIN_ENTRY is extended with classes designed for authorization and claim submissions, and an ISM_TRANSITION attribute is added to the COMPOSITION class. Another set of archetypes was designed based on this model. For all three approaches, templates were designed to represent the TISS forms.</p> <p>Results</p> <p>The archetypes based on the openEHR RM (Reference Model) can represent all TISS data structures. The extended model adds subclasses and an attribute to the COMPOSITION class to represent information on authorization and claim submissions. The archetypes based on all three approaches have similar structures, although rooted in different classes. The extended openEHR RM model is more semantically aligned with the concepts involved in a claim submission, but may disrupt interoperability with other systems and the current tools must be adapted to deal with it.</p> <p>Conclusions</p> <p>Modeling the TISS standard by means of the openEHR approach makes it aligned with ISO recommendations and provides a solid foundation on which the TISS can evolve. Although there are few administrative archetypes available, the openEHR RM is expressive enough to represent the TISS standard. This paper focuses on the TISS but its results may be extended to other billing processes. A complete communication architecture to simulate the exchange of TISS data between systems according to the openEHR approach still needs to be designed and implemented.</p

A Geometric Characterization of the Power of Finite Adaptability in Multistage Stochastic and Adaptive Optimization

In this paper, we show a significant role that geometric properties of uncertainty sets, such as symmetry, play in determining the power of robust and finitely adaptable solutions in multistage stochastic and adaptive optimization problems. We consider a fairly general class of multistage mixed integer stochastic and adaptive optimization problems and propose a good approximate solution policy with performance guarantees that depend on the geometric properties of the uncertainty sets. In particular, we show that a class of finitely adaptable solutions is a good approximation for both the multistage stochastic and the adaptive optimization problem. A finitely adaptable solution generalizes the notion of a static robust solution and specifies a small set of solutions for each stage; the solution policy implements the best solution from the given set, depending on the realization of the uncertain parameters in past stages. Therefore, it is a tractable approximation to a fully adaptable solution for the multistage problems. To the best of our knowledge, these are the first approximation results for the multistage problem in such generality. Moreover, the results and the proof techniques are quite general and also extend to include important constraints such as integrality and linear conic constraints.National Science Foundation (U.S.) (Grant EFRI-0735905

The geometry of nonlinear least squares with applications to sloppy models and optimization

Parameter estimation by nonlinear least squares minimization is a common problem with an elegant geometric interpretation: the possible parameter values of a model induce a manifold in the space of data predictions. The minimization problem is then to find the point on the manifold closest to the data. We show that the model manifolds of a large class of models, known as sloppy models, have many universal features; they are characterized by a geometric series of widths, extrinsic curvatures, and parameter-effects curvatures. A number of common difficulties in optimizing least squares problems are due to this common structure. First, algorithms tend to run into the boundaries of the model manifold, causing parameters to diverge or become unphysical. We introduce the model graph as an extension of the model manifold to remedy this problem. We argue that appropriate priors can remove the boundaries and improve convergence rates. We show that typical fits will have many evaporated parameters. Second, bare model parameters are usually ill-suited to describing model behavior; cost contours in parameter space tend to form hierarchies of plateaus and canyons. Geometrically, we understand this inconvenient parametrization as an extremely skewed coordinate basis and show that it induces a large parameter-effects curvature on the manifold. Using coordinates based on geodesic motion, these narrow canyons are transformed in many cases into a single quadratic, isotropic basin. We interpret the modified Gauss-Newton and Levenberg-Marquardt fitting algorithms as an Euler approximation to geodesic motion in these natural coordinates on the model manifold and the model graph respectively. By adding a geodesic acceleration adjustment to these algorithms, we alleviate the difficulties from parameter-effects curvature, improving both efficiency and success rates at finding good fits.Comment: 40 pages, 29 Figure