A few things I learnt from Jurgen Moser

A few remarks on integrable dynamical systems inspired by discussions with Jurgen Moser and by his work.Comment: An article for the special issue of "Regular and Chaotic Dynamics" dedicated to 80-th anniversary of Jurgen Mose

Validating Predictions of Unobserved Quantities

The ultimate purpose of most computational models is to make predictions, commonly in support of some decision-making process (e.g., for design or operation of some system). The quantities that need to be predicted (the quantities of interest or QoIs) are generally not experimentally observable before the prediction, since otherwise no prediction would be needed. Assessing the validity of such extrapolative predictions, which is critical to informed decision-making, is challenging. In classical approaches to validation, model outputs for observed quantities are compared to observations to determine if they are consistent. By itself, this consistency only ensures that the model can predict the observed quantities under the conditions of the observations. This limitation dramatically reduces the utility of the validation effort for decision making because it implies nothing about predictions of unobserved QoIs or for scenarios outside of the range of observations. However, there is no agreement in the scientific community today regarding best practices for validation of extrapolative predictions made using computational models. The purpose of this paper is to propose and explore a validation and predictive assessment process that supports extrapolative predictions for models with known sources of error. The process includes stochastic modeling, calibration, validation, and predictive assessment phases where representations of known sources of uncertainty and error are built, informed, and tested. The proposed methodology is applied to an illustrative extrapolation problem involving a misspecified nonlinear oscillator

Polarization control at the microscopic and electronic structure observatory

The new Microscopic and Electronic Structure Observatory (MAESTRO) at the Advanced Light Source (ALS) in Berkeley provides X-rays of variable polarization, produced by an elliptically polarized undulator (EPU), for angle resolved photoemission (ARPES) and photoemission electron microscopy (PEEM) experiments. The interpretation of photoemission data, in particular of dichroism effects in ARPES, requires the precise knowledge of the exact polarization state. Numerical simulations show that the first harmonics of the EPU at MAESTRO provides soft X-rays of almost 100% on axis polarization. However, the higher harmonics as well as the downstream optical elements of the beamline, have a considerable impact on the polarization of the light delivered to the experimental end-station. Employing a simple reflective polarimeter, the polarization is characterized for variable EPU and beamline settings and the overall degree of polarization in the MAESTRO end-stations is estimated to be on the order of 83%

An integrated brain-behavior model for working memory.

Working memory (WM) is a central construct in cognitive neuroscience because it comprises mechanisms of active information maintenance and cognitive control that underpin most complex cognitive behavior. Individual variation in WM has been associated with multiple behavioral and health features including demographic characteristics, cognitive and physical traits and lifestyle choices. In this context, we used sparse canonical correlation analyses (sCCAs) to determine the covariation between brain imaging metrics of WM-network activation and connectivity and nonimaging measures relating to sensorimotor processing, affective and nonaffective cognition, mental health and personality, physical health and lifestyle choices derived from 823 healthy participants derived from the Human Connectome Project. We conducted sCCAs at two levels: a global level, testing the overall association between the entire imaging and behavioral-health data sets; and a modular level, testing associations between subsets of the two data sets. The behavioral-health and neuroimaging data sets showed significant interdependency. Variables with positive correlation to the neuroimaging variate represented higher physical endurance and fluid intelligence as well as better function in multiple higher-order cognitive domains. Negatively correlated variables represented indicators of suboptimal cardiovascular and metabolic control and lifestyle choices such as alcohol and nicotine use. These results underscore the importance of accounting for behavioral-health factors in neuroimaging studies of WM and provide a neuroscience-informed framework for personalized and public health interventions to promote and maintain the integrity of the WM network

Laboratory simulations of astrophysical jets and solar coronal loops: new results

An experimental program underway at Caltech has produced plasmas where the shape is neither fixed by the vacuum chamber nor fixed by an external coil set, but instead is determined by self-organization. The plasma dynamics is highly reproducible and so can be studied in considerable detail even though the morphology of the plasma is both complex and time-dependent. A surprising result has been the observation that self-collimating MHD-driven plasma jets are ubiquitous and play a fundamental role in the self-organization. The jets can be considered lab-scale simulations of astrophysical jets and in addition are intimately related to solar coronal loops. The jets are driven by the combination of the axial component of the J×B force and the axial pressure gradient resulting from the non-uniform pinch force associated with the flared axial current density. Behavior is consistent with a model showing that collimation results from axial non-uniformity of the jet velocity. In particular, flow stagnation in the jet frame compresses frozen-in azimuthal magnetic flux, squeezes together toroidal magnetic field lines, thereby amplifying the embedded toroidal magnetic field, enhancing the pinch force, and hence causing collimation of the jet

Ionization signals from electrons and alpha-particles in mixtures of liquid Argon and Nitrogen - perspectives on protons for Gamma Resonant Nuclear Absorption applications

In this paper we report on a detailed study of ionization signals produced by Compton electrons and alpha-particles in a Time Projection Chamber (TPC) flled with different mixtures of liquid Argon and Nitrogen. The measurements were carried out with Nitrogen concentrations up to 15% and a drift electric feld in the range 0-50 kV/cm. A prediction for proton ionization signals is made by means of interpolation. This study has been conducted in view of the possible use of liquid Ar-N2 TPCs for the detection of gamma-rays in the resonant band of the Nitrogen absorption spectrum, a promising technology for security and medical applications

30 kV coaxial vacuum-tight feedthrough for operation at cryogenic temperatures

In this paper we describe the technology of building a vacuum-tight high voltage feedthrough which is able to operate at voltages up to 30 kV. The feedthrough has a coaxial structure with a grounded sheath which makes it capable to lead high voltage potentials into cryogenic liquids, without risk of surface discharges in the gas phase above the liquid level. The feedthrough is designed to be used in ionization detectors, based on liquefied noble gases, such as Argon or Xenon

Spin chain from membrane and the Neumann-Rosochatius integrable system

We find membrane configurations in AdS_4 x S^7, which correspond to the continuous limit of the SU(2) integrable spin chain, considered as a limit of the SU(3) spin chain, arising in N=4 SYM in four dimensions, dual to strings in AdS_5 x S^5. We also discuss the relationship with the Neumann-Rosochatius integrable system at the level of Lagrangians, comparing the string and membrane cases.Comment: LaTeX, 16 pages, no figures; v2: 17 pages, title changed, explanations and references added; v3: more explanations added; v4: typos fixed, to appear in Phys. Rev.