69 research outputs found

    Determination of the Fermion Pair Size in a Resonantly Interacting Superfluid

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    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

    Vortices and Superfluidity in a Strongly Interacting Fermi Gas

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    Quantum-degenerate Fermi gases provide a remarkable opportunity to study strongly interacting fermions. In contrast to other Fermi systems, such as superconductors, neutron stars or the quark-gluon plasma, these gases have low densities and their interactions can be precisely controlled over an enormous range. Here we report observations of vortices in such a gas that provide definitive evidence for superfluidity. By varying the pairing strength between two fermions near a Feshbach resonance, one can explore the crossover from a Bose-Einstein condensate (BEC) of molecules to a Bardeen-Cooper-Schrieffer (BCS) superfluid of loosely bound pairs whose size is comparable to, or even larger than, the interparticle spacing. The crossover realizes a novel form of high-T_C superfluidity and it may provide new insight for high-T_C superconductors. Previous experiments with Fermi gases have revealed condensation of fermion pairs. While these and other studies were consistent with predictions assuming superfluidity, the smoking gun for superfluid behavior has been elusive. Our observation of vortex lattices directly displays superfluid flow in a strongly interacting, rotating Fermi gas.Comment: 14 pages, including 7 figures, submitted to Natur

    Stochastic flowering phenology in Dactylis Glomerata populations described by Markov chain modelling

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    Understanding the relationship between flowering patterns and pollen dispersal is important in climate change modelling, pollen forecasting, forestry and agriculture. Enhanced understanding of this connection can be gained through detailed spatial and temporal flowering observations on a population level, combined with modelling simulating the dynamics. Species with large distribution ranges, long flowering seasons, high pollen production and naturally large populations can be used to illustrate these dynamics. Revealing and simulating species-specific demographic and stochastic elements in the flowering process will likely be important in determining when pollen release is likely to happen in flowering plants. Spatial and temporal dynamics of eight populations of Dactylis glomerata were collected over the course of two years to determine high-resolution demographic elements. Stochastic elements were accounted for using Markov Chain approaches in order to evaluate tiller-specific contribution to overall population dynamics. Tiller-specific developmental dynamics were evaluated using three different RV matrix correlation coefficients. We found that the demographic patterns in population development were the same for all populations with key phenological events differing only by a few days over the course of the seasons. Many tillers transitioned very quickly from non-flowering to full flowering, a process that can be replicated with Markov Chain modelling. Our novel approach demonstrates the identification and quantification of stochastic elements in the flowering process of D. glomerata, an element likely to be found in many flowering plants. The stochastic modelling approach can be used to develop detailed pollen release models for Dactylis, other grass species and probably other flowering plants

    Why medical students choose psychiatry - a 20 country cross-sectional survey

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    BACKGROUND: Recruitment to psychiatry is insufficient to meet projected mental health service needs world-wide. We report on the career plans of final year medical students from 20 countries, investigating factors identified from the literature which influence psychiatric career choice. METHODS: Cross sectional electronic or paper survey. Subjects were final year medical students at 46 medical schools in participating countries. We assessed students' career intentions, motivations, medical school teaching and exposure to psychiatry. We assessed students' attitudes and personality factors. The main outcome measure was likelihood of specializing in psychiatry. Multilevel logistic regression was used to examine the joint effect of factors upon the main outcome. RESULTS: 2198 of 9135 (24%) of students responded (range 4 to 91%) across the countries. Internationally 4.5% of students definitely considered psychiatry as a career (range 1 to 12%). 19% of students (range 0 to 33%) were "quite likely", and 25% were "definitely not" considering psychiatry. Female gender, experience of mental/physical illness, media portrayal of doctors, and positive attitudes to psychiatry, but not personality factors, were associated with choosing psychiatry. Quality of psychiatric placement (correlation coefficient = 0.22, p < 0.001) and number of placements (correlation coefficient =0.21, p < 0.001) were associated with higher ATP scores. During medical school, experience of psychiatric enrichment activities (special studies modules and university psychiatry clubs), experience of acutely unwell patients and perceived clinical responsibility were all associated with choice of psychiatry.Multilevel logistic regression revealed six factors associated with students choosing psychiatry: importance of own vocation, odds ratio (OR) 3.01, 95% CI 1.61 to 5.91, p < 0.001); interest in psychiatry before medical school, OR 10.8 (5.38 to 21.8, p < 0.001); undertaking a psychiatry special study module, OR 1.45 (1.05 to 2.01, p = 0.03) or elective OR 4.28 (2.87- 6.38, p < 0.001); membership of a university psychiatry club, OR 3.25 (2.87 to 6.38, p < 0.001); and exposure to didactic teaching, OR 0.54 (0.40 to 0.72, p < 0.001). CONCLUSIONS: We report factors relevant to medical student selection and psychiatry teaching which affect career choice. Addressing these factors may improve recruitment to psychiatry internationally

    Pan-cancer analysis of whole genomes

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    Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe
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