Laser radiation pressure slowing of a molecular beam

There is substantial interest in producing samples of ultracold molecules for possible applications in quantum computation, quantum simulation of condensed matter systems, precision measurements, controlled chemistry, and high precision spectroscopy. A crucial step to obtaining large samples of ultracold, trapped molecules is developing a means to bridge the gap between typical molecular source velocities (~150-600 m/s) and velocities for which trap loading or confinement is possible (~5-20 m/s). Here we show deceleration of a beam of neutral strontium monofluoride (SrF) molecules using radiative force. Under certain conditions, the deceleration results in a substantial flux of molecules with velocities <50 m/s. The observed slowing, from ~140 m/s, corresponds to scattering ~10000 photons. We also observe longitudinal velocity compression under different conditions. Combined with molecular laser cooling techniques, this lays the groundwork to create slow and cold molecular beams suitable for trap loading.Comment: 7 pages, 7 figures. Supplementary material updated

The weight-inclusive vs. weight-normative approach to health: Evaluating the evidence for prioritizing well-being over weight

Using an ethical lens, this review evaluates two methods of working within patient care and public health: the weight-normative approach (emphasis on weight and weight loss when defining health and well-being) and the weight-inclusive approach (emphasis on viewing health and well-being as multifaceted while directing efforts toward improving health access and reducing weight stigma). Data reveal that the weight-normative approach is not effective for most people because of high rates of weight regain and cycling from weight loss interventions, which are linked to adverse health and well-being. Its predominant focus on weight may also foster stigma in health care and society, and data show that weight stigma is also linked to adverse health and well-being. In contrast, data support a weight-inclusive approach, which is included in models such as Health at Every Size for improving physical (e.g., blood pressure), behavioral (e.g., binge eating), and psychological (e.g., depression) indices, as well as acceptability of public health messages. Therefore, the weight-inclusive approach upholds nonmaleficience and beneficience, whereas the weight-normative approach does not. We offer a theoretical framework that organizes the research included in this review and discuss how it can guide research efforts and help health professionals intervene with their patients and community

Reactions of C+ + Cl-, Br-, and I--A comparison of theory and experiment.

Rate constants for the reactions of C+ + Cl-, Br-, and I- were measured at 300 K using the variable electron and neutral density electron attachment mass spectrometry technique in a flowing afterglow Langmuir probe apparatus. Upper bounds of &lt;10-8 cm3 s-1 were found for the reaction of C+ with Br- and I-, and a rate constant of 4.2 ± 1.1 × 10-9 cm3 s-1 was measured for the reaction with Cl-. The C+ + Cl- mutual neutralization reaction was studied theoretically from first principles, and a rate constant of 3.9 × 10-10 cm3 s-1, an order of magnitude smaller than experiment, was obtained with spin-orbit interactions included using a semiempirical model. The discrepancy between the measured and calculated rate constants could be explained by the fact that in the experiment, the total loss of C+ ions was measured, while the theoretical treatment did not include the associative ionization channel. The charge transfer was found to take place at small internuclear distances, and the spin-orbit interaction was found to have a minor effect on the rate constant

Spectral Graph Convolutions for Population-based Disease Prediction

Exploiting the wealth of imaging and non-imaging information for disease prediction tasks requires models capable of representing, at the same time, individual features as well as data associations between subjects from potentially large populations. Graphs provide a natural framework for such tasks, yet previous graph-based approaches focus on pairwise similarities without modelling the subjects' individual characteristics and features. On the other hand, relying solely on subject-specific imaging feature vectors fails to model the interaction and similarity between subjects, which can reduce performance. In this paper, we introduce the novel concept of Graph Convolutional Networks (GCN) for brain analysis in populations, combining imaging and non-imaging data. We represent populations as a sparse graph where its vertices are associated with image-based feature vectors and the edges encode phenotypic information. This structure was used to train a GCN model on partially labelled graphs, aiming to infer the classes of unlabelled nodes from the node features and pairwise associations between subjects. We demonstrate the potential of the method on the challenging ADNI and ABIDE databases, as a proof of concept of the benefit from integrating contextual information in classification tasks. This has a clear impact on the quality of the predictions, leading to 69.5% accuracy for ABIDE (outperforming the current state of the art of 66.8%) and 77% for ADNI for prediction of MCI conversion, significantly outperforming standard linear classifiers where only individual features are considered.Comment: International Conference on Medical Image Computing and Computer-Assisted Interventions (MICCAI) 201

Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks

Evaluating similarity between graphs is of major importance in several computer vision and pattern recognition problems, where graph representations are often used to model objects or interactions between elements. The choice of a distance or similarity metric is, however, not trivial and can be highly dependent on the application at hand. In this work, we propose a novel metric learning method to evaluate distance between graphs that leverages the power of convolutional neural networks, while exploiting concepts from spectral graph theory to allow these operations on irregular graphs. We demonstrate the potential of our method in the field of connectomics, where neuronal pathways or functional connections between brain regions are commonly modelled as graphs. In this problem, the definition of an appropriate graph similarity function is critical to unveil patterns of disruptions associated with certain brain disorders. Experimental results on the ABIDE dataset show that our method can learn a graph similarity metric tailored for a clinical application, improving the performance of a simple k-nn classifier by 11.9% compared to a traditional distance metric.Comment: International Conference on Medical Image Computing and Computer-Assisted Interventions (MICCAI) 201

A Bright, Slow Cryogenic Molecular Beam Source for Free Radicals

We demonstrate and characterize a cryogenic buffer gas-cooled molecular beam source capable of producing bright beams of free radicals and refractory species. Details of the beam properties (brightness, forward velocity distribution, transverse velocity spread, rotational and vibrational temperatures) are measured under varying conditions for the molecular species SrF. Under typical conditions we produce a beam of brightness 1.2 x 10^11 molecules/sr/pulse in the rovibrational ground state, with 140 m/s forward velocity and a rotational temperature of approximately 1 K. This source compares favorably to other methods for producing beams of free radicals and refractory species for many types of experiments. We provide details of construction that may be helpful for others attempting to use this method.Comment: 15 pages, 14 figure

Franck-Condon Factors and Radiative Lifetime of the A^{2}\Pi_{1/2} - X^{2}\Sigma^{+} Transition of Ytterbium Monoflouride, YbF

The fluorescence spectrum resulting from laser excitation of the A^{2}\Pi_{1/2} - X^{2}\Sigma^{+} (0,0) band of ytterbium monofluoride, YbF, has been recorded and analyzed to determine the Franck-Condon factors. The measured values are compared with those predicted from Rydberg-Klein-Rees (RKR) potential energy curves. From the fluorescence decay curve the radiative lifetime of the A^{2}\Pi_{1/2} state is measured to be 28\pm2 ns, and the corresponding transition dipole moment is 4.39\pm0.16 D. The implications for laser cooling YbF are discussed.Comment: 5 pages, 5 figure

Seasonal variations of glaciochemical, isotopic and stratigraphic properties in Siple Dome (Antarctica) surface snow

Six snow-pit records recovered from Siple Dome, West Antarctica, during 1994 are used to study seasonal variations in chemical (major ion and H202), isotopic (deuterium) and physical stratigraphic properties during the 1988-94 period. Comparison of δD measurements and satellite-derived brightness temperature for the Siple Dome area suggests that most seasonal SD maxima occur within ±4 weeks of each 1 January. Several other chemical species (H2O2, non-sea-salt (nss) SO4 2-, methanesulfonic acid and NO3-) show coeval peaks with SD, together providing an accurate method for identifying summer accumulation. Sea-salt-derived species generally peak during winter/spring, but episodic input is noted throughout some years. No reliable seasonal signal is identified in species with continental sources (nssCa2+ nss Mg2+), NH4 + or nssCl-. Visible strata such as large depth-hoar layers (\u3e5 cm) are associated with summer accumulation and its metamorphosis, but smaller hoar layers and crusts are more difficult to interpret. A multi-parameter approach is found to provide the most accurate dating of these snow-pit records, and is used to determine annual layer thicknesses at each site Significant spatial accumulation variability exists on an annual basis, but mean accumulation in the sampled 10 km2 grid for the 1988-94 period is fairly uniform

Laser cooling of a diatomic molecule

It has been roughly three decades since laser cooling techniques produced ultracold atoms, leading to rapid advances in a vast array of fields. Unfortunately laser cooling has not yet been extended to molecules because of their complex internal structure. However, this complexity makes molecules potentially useful for many applications. For example, heteronuclear molecules possess permanent electric dipole moments which lead to long-range, tunable, anisotropic dipole-dipole interactions. The combination of the dipole-dipole interaction and the precise control over molecular degrees of freedom possible at ultracold temperatures make ultracold molecules attractive candidates for use in quantum simulation of condensed matter systems and quantum computation. Also ultracold molecules may provide unique opportunities for studying chemical dynamics and for tests of fundamental symmetries. Here we experimentally demonstrate laser cooling of the molecule strontium monofluoride (SrF). Using an optical cycling scheme requiring only three lasers, we have observed both Sisyphus and Doppler cooling forces which have substantially reduced the transverse temperature of a SrF molecular beam. Currently the only technique for producing ultracold molecules is by binding together ultracold alkali atoms through Feshbach resonance or photoassociation. By contrast, different proposed applications for ultracold molecules require a variety of molecular energy-level structures. Our method provides a new route to ultracold temperatures for molecules. In particular it bridges the gap between ultracold temperatures and the ~1 K temperatures attainable with directly cooled molecules (e.g. cryogenic buffer gas cooling or decelerated supersonic beams). Ultimately our technique should enable the production of large samples of molecules at ultracold temperatures for species that are chemically distinct from bialkalis.Comment: 10 pages, 7 figure

Validation of a Climate-Data Record of the "Clear-Sky" Surface Temperature of the Greenland Ice Sheet

Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented since 1981. We extended and refined this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. We developed a daily and monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using an ice-surface temperature (1ST) algorithm developed for use with MODIS data. Validation of this CDR is ongoing. MODIS Terra swath data are projected onto a polar stereographic grid at 6.25-km resolution to develop binary, gridded daily and mean-monthly 1ST maps. Each monthly map also has a color-coded image map that is available to download. Also included with the monthly maps is an accompanying map showing number of days in the month that were used to calculate the mean-monthly 1ST. This is important because no 1ST decision is made by the algorithm for cells that are considered cloudy by the internal cloud mask, so a sufficient number of days must be available to produce a mean 1ST for each grid cell. Validation of the CDR consists of several facets: 1) comparisons between ISTs and in-situ measurements; 2) comparisons between ISTs and AWS data; and 3) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer (ASTER) and Enhanced Thematic Mapper Plus (ETM+). Previous work shows that Terra MODIS ISTs are about 3 C lower than in-situ temperatures measured at Summit Camp, during the winter of 2008-09 under clear skies. In this work we begin to compare surface temperatures derived from AWS data with ISTs from the MODIS CDR