Direct observation of growth and collapse of a Bose-Einstein condensate with attractive interactions

The dynamical behavior of Bose-Einstein condensation (BEC) in a gas with attractive interactions is striking. Quantum theory predicts that BEC of a spatially homogeneous gas with attractive interactions is precluded by a conventional phase transition into either a liquid or solid. When confined to a trap, however, such a condensate can form provided that its occupation number does not exceed a limiting value. The stability limit is determined by a balance between self-attraction and a repulsion arising from position-momentum uncertainty under conditions of spatial confinement. Near the stability limit, self-attraction can overwhelm the repulsion, causing the condensate to collapse. Growth of the condensate, therefore, is punctuated by intermittent collapses, which are triggered either by macroscopic quantum tunneling or thermal fluctuation. Previous observation of growth and collapse has been hampered by the stochastic nature of these mechanisms. Here we reduce the stochasticity by controlling the initial number of condensate atoms using a two-photon transition to a diatomic molecular state. This enables us to obtain the first direct observation of the growth of a condensate with attractive interactions and its subsequent collapse.Comment: 10 PDF pages, 5 figures (2 color), 19 references, to appear in Nature Dec. 7 200

Determination of the Fermion Pair Size in a Resonantly Interacting Superfluid

Fermionic superfluidity requires the formation of pairs. The actual size of these fermion pairs varies by orders of magnitude from the femtometer scale in neutron stars and nuclei to the micrometer range in conventional superconductors. Many properties of the superfluid depend on the pair size relative to the interparticle spacing. This is expressed in BCS-BEC crossover theories, describing the crossover from a Bardeen-Cooper-Schrieffer (BCS) type superfluid of loosely bound and large Cooper pairs to Bose-Einstein condensation (BEC) of tightly bound molecules. Such a crossover superfluid has been realized in ultracold atomic gases where high temperature superfluidity has been observed. The microscopic properties of the fermion pairs can be probed with radio-frequency (rf) spectroscopy. Previous work was difficult to interpret due to strong and not well understood final state interactions. Here we realize a new superfluid spin mixture where such interactions have negligible influence and present fermion-pair dissociation spectra that reveal the underlying pairing correlations. This allows us to determine the spectroscopic pair size in the resonantly interacting gas to be 2.6(2)/kF (kF is the Fermi wave number). The pairs are therefore smaller than the interparticle spacing and the smallest pairs observed in fermionic superfluids. This finding highlights the importance of small fermion pairs for superfluidity at high critical temperatures. We have also identified transitions from fermion pairs into bound molecular states and into many-body bound states in the case of strong final state interactions.Comment: 8 pages, 7 figures; Figures updated; New Figures added; Updated discussion of fit function

Collective decision-making on triadic graphs

Many real-world networks exhibit community structures and non-trivial clustering associated with the occurrence of a considerable number of triangular subgraphs known as triadic motifs. Triads are a set of distinct triangles that do not share an edge with any other triangle in the network. Network motifs are subgraphs that occur significantly more often compared to random topologies. Two prominent examples, the feedforward loop and the feedback loop, occur in various real-world networks such as gene-regulatory networks, food webs or neuronal networks. However, as triangular connections are also prevalent in communication topologies of complex collective systems, it is worthwhile investigating the influence of triadic motifs on the collective decision-making dynamics. To this end, we generate networks called Triadic Graphs (TGs) exclusively from distinct triadic motifs. We then apply TGs as underlying topologies of systems with collective dynamics inspired from locust marching bands. We demonstrate that the motif type constituting the networks can have a paramount influence on group decision-making that cannot be explained solely in terms of the degree distribution. We find that, in contrast to the feedback loop, when the feedforward loop is the dominant subgraph, the resulting network is hierarchical and inhibits coherent behavior

Gauge-Higgs Dark Matter

When the anti-periodic boundary condition is imposed for a bulk field in extradimensional theories, independently of the background metric, the lightest component in the anti-periodic field becomes stable and hence a good candidate for the dark matter in the effective 4D theory due to the remaining accidental discrete symmetry. Noting that in the gauge-Higgs unification scenario, introduction of anti-periodic fermions is well-motivated by a phenomenological reason, we investigate dark matter physics in the scenario. As an example, we consider a five-dimensional SO(5)\timesU(1)_X gauge-Higgs unification model compactified on the $S^1/Z_2$ with the warped metric. Due to the structure of the gauge-Higgs unification, interactions between the dark matter particle and the Standard Model particles are largely controlled by the gauge symmetry, and hence the model has a strong predictive power for the dark matter physics. Evaluating the dark matter relic abundance, we identify a parameter region consistent with the current observations. Furthermore, we calculate the elastic scattering cross section between the dark matter particle and nucleon and find that a part of the parameter region is already excluded by the current experimental results for the direct dark matter search and most of the region will be explored in future experiments.Comment: 16 pages, 2 figure

Prediction of Maximal Heart Rate in Children and Adolescents.

OBJECTIVE: To identify a method to predict the maximal heart rate (MHR) in children and adolescents, as available prediction equations developed for adults have a low accuracy in children. We hypothesized that MHR may be influenced by resting heart rate, anthropometric factors, or fitness level. DESIGN: Cross-sectional study. SETTING: Sports medicine center in primary care. PARTICIPANTS: Data from 627 treadmill maximal exercise tests performed by 433 pediatric athletes (age 13.7 ± 2.1 years, 70% males) were analyzed. INDEPENDENT VARIABLES: Age, sex, sport type, stature, body mass, BMI, body fat, fitness level, resting, and MHR were recorded. MAIN OUTCOME MEASURES: To develop a prediction equation for MHR in youth, using stepwise multivariate linear regression and linear mixed model. To determine correlations between existing prediction equations and pediatric MHR. RESULTS: Observed MHR was 197 ± 8.6 b·min. Regression analysis revealed that resting heart rate, fitness, body mass, and fat percent were predictors of MHR (R = 0.25, P < 0.001), whereas age was not. Resting heart rate explained 15.6% of MHR variance, body mass added 5.7%, fat percent added 2.4%, and fitness added 1.2%. Existing adult equations had low correlations with observed MHR in children and adolescents (r = -0.03-0.34). CONCLUSIONS: A new equation to predict MHR in children and adolescents was developed, but was found to have low predictive ability, a finding similar to adult equations applied to children. CLINICAL RELEVANCE: Considering the narrow range of MHR in youth, we propose using 197 b·min as the mean MHR in children and adolescents, with 180 b·min the minimal threshold value (-2 standard deviations)

Physics of Ultra-Peripheral Nuclear Collisions

Moving highly-charged ions carry strong electromagnetic fields that act as a field of photons. In collisions at large impact parameters, hadronic interactions are not possible, and the ions interact through photon-ion and photon-photon collisions known as {\it ultra-peripheral collisions} (UPC). Hadron colliders like the Relativistic Heavy Ion Collider (RHIC), the Tevatron and the Large Hadron Collider (LHC) produce photonuclear and two-photon interactions at luminosities and energies beyond that accessible elsewhere; the LHC will reach a $\gamma p$ energy ten times that of the Hadron-Electron Ring Accelerator (HERA). Reactions as diverse as the production of anti-hydrogen, photoproduction of the $\rho^0$, transmutation of lead into bismuth and excitation of collective nuclear resonances have already been studied. At the LHC, UPCs can study many types of `new physics.'Comment: 47 pages, to appear in Annual Review of Nuclear and Particle Scienc

Gap junction proteins and their role in spinal cord injury

© 2015 Tonkin, Mao, O'Carroll, Nicholson, Green, Gorrie and Moalem-Taylor. Gap junctions are specialized intercellular communication channels that are formed by two hexameric connexin hemichannels, one provided by each of the two adjacent cells. Gap junctions and hemichannels play an important role in regulating cellular metabolism, signaling, and functions in both normal and pathological conditions. Following spinal cord injury (SCI), there is damage and disturbance to the neuronal elements of the spinal cord including severing of axon tracts and rapid cell death. The initial mechanical disruption is followed by multiple secondary cascades that cause further tissue loss and dysfunction. Recent studies have implicated connexin proteins as playing a critical role in the secondary phase of SCI by propagating death signals through extensive glial networks. In this review, we bring together past and current studies to outline the distribution, changes and roles of various connexins found in neurons and glial cells, before and in response to SCI. We discuss the contribution of pathologically activated connexin proteins, in particular connexin 43, to functional recovery and neuropathic pain, as well as providing an update on potential connexin specific pharmacological agents to treat SCI

Retinal glycoprotein enrichment by concanavalin a enabled identification of novel membrane autoantigen synaptotagmin-1 in equine recurrent uveitis.

Complete knowledge of autoantigen spectra is crucial for understanding pathomechanisms of autoimmune diseases like equine recurrent uveitis (ERU), a spontaneous model for human autoimmune uveitis. While several ERU autoantigens were identified previously, no membrane protein was found so far. As there is a great overlap between glycoproteins and membrane proteins, the aim of this study was to test whether pre-enrichment of retinal glycoproteins by ConA affinity is an effective tool to detect autoantigen candidates among membrane proteins. In 1D Western blots, the glycoprotein preparation allowed detection of IgG reactions to low abundant proteins in sera of ERU patients. Synaptotagmin-1, a Ca2+-sensing protein in synaptic vesicles, was identified as autoantigen candidate from the pre-enriched glycoprotein fraction by mass spectrometry and was validated as a highly prevalent autoantigen by enzyme-linked immunosorbent assay. Analysis of Syt1 expression in retinas of ERU cases showed a downregulation in the majority of ERU affected retinas to 24%. Results pointed to a dysregulation of retinal neurotransmitter release in ERU. Identification of synaptotagmin-1, the first cell membrane associated autoantigen in this spontaneous autoimmune disease, demonstrated that examination of tissue fractions can lead to the discovery of previously undetected novel autoantigens. Further experiments will address its role in ERU pathology

Weak Mixing Angle and Higgs Mass in Gauge-Higgs Unification Models with Brane Kinetic Terms

We show that the idea of Gauge-Higgs unification(GHU) can be rescued from the constraint of weak mixing angle by introducing localized brane kinetic terms in higher dimensional GHU models with bulk and simple gauge groups. We find that those terms lead to a ratio between Higgs and W boson masses, which is a little bit deviated from the one derived in the standard model. From numerical analysis, we find that the current lower bound on the Higgs mass tends to prefer to exceptional groups E(6), E(7), E(8) rather than other groups like SU(3l), SO(2n+1), G(2), and F(4) in 6-dimensional(D) GHU models irrespective of the compactification scales. For the compactification scale below 1 TeV, the Higgs masses in 6D GHU models with SU(3l), SO(2n+1), G(2), and F(4) groups are predicted to be less than the current lower bound unless a model parameter responsible for re-scaling SU(2) gauge coupling is taken to be unnaturally large enough. To see how the situation is changed in more higher dimensional GHU model, we take 7D S^{3}/ Z_{2} and 8D T^{4}/ Z_{2} models. It turns out from our numerical analysis that these higher dimensional GHU models with gauge groups except for E(6) can lead to the Higgs boson whose masses are predicted to be above the current lower bound only for the compatification scale above 1 TeV without taking unnaturally large value of the model parameter, whereas the Higgs masses in the GHU models with E(6) are compatible with the current lower bound even for the compatification scale below 1 TeV.Comment: 22 pages, 4 figure

Fr-TM-align: a new protein structural alignment method based on fragment alignments and the TM-score

©2008 Pandit and Skolnick; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This article is available from: http://www.biomedcentral.com/1471-2105/9/531doi:10.1186/1471-2105-9-531Background: Protein tertiary structure comparisons are employed in various fields of contemporary structural biology. Most structure comparison methods involve generation of an initial seed alignment, which is extended and/or refined to provide the best structural superposition between a pair of protein structures as assessed by a structure comparison metric. One such metric, the TM-score, was recently introduced to provide a combined structure quality measure of the coordinate root mean square deviation between a pair of structures and coverage. Using the TM-score, the TM-align structure alignment algorithm was developed that was often found to have better accuracy and coverage than the most commonly used structural alignment programs; however, there were a number of situations when this was not true. Results: To further improve structure alignment quality, the Fr-TM-align algorithm has been developed where aligned fragment pairs are used to generate the initial seed alignments that are then refined using dynamic programming to maximize the TM-score. For the assessment of the structural alignment quality from Fr-TM-align in comparison to other programs such as CE and TMalign, we examined various alignment quality assessment scores such as PSI and TM-score. The assessment showed that the structural alignment quality from Fr-TM-align is better in comparison to both CE and TM-align. On average, the structural alignments generated using Fr-TM-align have a higher TM-score (~9%) and coverage (~7%) in comparison to those generated by TM-align. Fr- TM-align uses an exhaustive procedure to generate initial seed alignments. Hence, the algorithm is computationally more expensive than TM-align. Conclusion: Fr-TM-align, a new algorithm that employs fragment alignment and assembly provides better structural alignments in comparison to TM-align. The source code and executables of Fr- TM-align are freely downloadable at: http://cssb.biology.gatech.edu/skolnick/files/FrTMalign/