696 research outputs found
Simulating quantum statistics with entangled photons: a continuous transition from bosons to fermions
In contrast to classical physics, quantum mechanics divides particles into
two classes-bosons and fermions-whose exchange statistics dictate the dynamics
of systems at a fundamental level. In two dimensions quasi-particles known as
'anyons' exhibit fractional exchange statistics intermediate between these two
classes. The ability to simulate and observe behaviour associated to
fundamentally different quantum particles is important for simulating complex
quantum systems. Here we use the symmetry and quantum correlations of entangled
photons subjected to multiple copies of a quantum process to directly simulate
quantum interference of fermions, bosons and a continuum of fractional
behaviour exhibited by anyons. We observe an average similarity of 93.6\pm0.2%
between an ideal model and experimental observation. The approach generalises
to an arbitrary number of particles and is independent of the statistics of the
particles used, indicating application with other quantum systems and large
scale application.Comment: 10 pages, 5 figure
Overcoming the barriers to greater public engagement
Integrating science communication training into an undergraduate research project encourages greater academic involvement in public engagement, maximizes audience size, and provides high-quality research data
Python as a Federation Tool for GENESIS 3.0
The GENESIS simulation platform was one of the first broad-scale modeling systems in computational biology to encourage modelers to develop and share model features and components. Supported by a large developer community, it participated in innovative simulator technologies such as benchmarking, parallelization, and declarative model specification and was the first neural simulator to define bindings for the Python scripting language. An important feature of the latest version of GENESIS is that it decomposes into self-contained software components complying with the Computational Biology Initiative federated software architecture. This architecture allows separate scripting bindings to be defined for different necessary components of the simulator, e.g., the mathematical solvers and graphical user interface. Python is a scripting language that provides rich sets of freely available open source libraries. With clean dynamic object-oriented designs, they produce highly readable code and are widely employed in specialized areas of software component integration. We employ a simplified wrapper and interface generator to examine an application programming interface and make it available to a given scripting language. This allows independent software components to be ‘glued’ together and connected to external libraries and applications from user-defined Python or Perl scripts. We illustrate our approach with three examples of Python scripting. (1) Generate and run a simple single-compartment model neuron connected to a stand-alone mathematical solver. (2) Interface a mathematical solver with GENESIS 3.0 to explore a neuron morphology from either an interactive command-line or graphical user interface. (3) Apply scripting bindings to connect the GENESIS 3.0 simulator to external graphical libraries and an open source three dimensional content creation suite that supports visualization of models based on electron microscopy and their conversion to computational models. Employed in this way, the stand-alone software components of the GENESIS 3.0 simulator provide a framework for progressive federated software development in computational neuroscience
Neural Dynamics during Anoxia and the “Wave of Death”
Recent experiments in rats have shown the occurrence of a high amplitude slow brain wave in the EEG approximately 1 minute after decapitation, with a duration of 5–15 s (van Rijn et al, PLoS One 6, e16514, 2011) that was presumed to signify the death of brain neurons. We present a computational model of a single neuron and its intra- and extracellular ion concentrations, which shows the physiological mechanism for this observation. The wave is caused by membrane potential oscillations, that occur after the cessation of activity of the sodium-potassium pumps has lead to an excess of extracellular potassium. These oscillations can be described by the Hodgkin-Huxley equations for the sodium and potassium channels, and result in a sudden change in mean membrane voltage. In combination with a high-pass filter, this sudden depolarization leads to a wave in the EEG. We discuss that this process is not necessarily irreversible
Measuring symmetry, asymmetry and randomness in neural network connectivity
Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits non-random features, so-called motifs. In this work, we focus on bidirectional, symmetric motifs, i.e. two neurons that project to each other via connections of equal strength, and unidirectional, non-symmetric motifs, i.e. within a pair of neurons only one neuron projects to the other. We hypothesise that such motifs have been shaped via activity dependent synaptic plasticity processes. As a consequence, learning moves the distribution of the synaptic connections away from randomness. Our aim is to provide a global, macroscopic, single parameter characterisation of the statistical occurrence of bidirectional and unidirectional motifs. To this end we define a symmetry measure that does not require any a priori thresholding of the weights or knowledge of their maximal value. We calculate its mean and variance for random uniform or Gaussian distributions, which allows us to introduce a confidence measure of how significantly symmetric or asymmetric a specific configuration is, i.e. how likely it is that the configuration is the result of chance. We demonstrate the discriminatory power of our symmetry measure by inspecting the eigenvalues of different types of connectivity matrices. We show that a Gaussian weight distribution biases the connectivity motifs to more symmetric configurations than a uniform distribution and that introducing a random synaptic pruning, mimicking developmental regulation in synaptogenesis, biases the connectivity motifs to more asymmetric configurations, regardless of the distribution. We expect that our work will benefit the computational modelling community, by providing a systematic way to characterise symmetry and asymmetry in network structures. Further, our symmetry measure will be of use to electrophysiologists that investigate symmetry of network connectivity
The genomes of two key bumblebee species with primitive eusocial organization
Background: The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results: We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions: These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation
Phagocytosis and digestion of pH-sensitive fluorescent dye (Eos-FP) transfected E. coli in whole blood assays from patients with severe sepsis and septic shock
The function of phagocytic and antigen presenting cells is of crucial importance to sustain immune competence against infectious agents as well as malignancies. We here describe a reproducible procedure for the quantification of phagocytosis by leukocytes in whole blood. For this, a pH-sensitive green-fluorescent protein- (GFP) like dye (Eos-FP) is transfected into infectious microroganisms. After UV-irradiation, the transfected bacteria emit green (≈5160 nm) and red (≈581 nm) fluorescent light at 490 nm excitation. Since the red fluorescent light is sensitive to acidic pH, the phagocytosed bacteria stop emitting red fluorescent light as soon as the phagosomes fuse with lysosomes. The green fluorescence is maintained in the phagolysosome until pathogen degradation is completed. Fluorescence emission can be followed by flow cytometry with filter settings documenting fluorescence 1 (FL 1, FITC) and fluorescence 2 (FL 2, phycoerythrin, PE). Eos-FP transfected bacteria can also be traced within phagocytes using microscopical techniques. A standardized assay has been developed which is suitable for clinical studies by providing clinicians with syringes pre-filled with fixed and appropriately UV-irradiated Eos-FP E. coli (TruCulture™). After adding blood or body fluids to these containers and starting the incubation at 37°C, phagocytosis by granulocytes proceeds over time. Cultures can be terminated at a given time by lysing red blood cells followed by flow cytometry. A pilot study demonstrated that Eos-FP E. coli phagocytosis and digestion was up-regulated in the majority of patients with either severe sepsis or septic shock as compared to healthy donors (p < 0.0001 after o/n incubation). Following treatment with recombinant human granulocyte colony-stimulating factor (rhG-CSF) in selected patients with sepsis, phagolysosome fusion appeared to be accelerated
Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector
Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02 TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1 μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos2Δϕ modulation for all ΣETPb ranges and particle pT
Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector
The inclusive and dijet production cross-sections have been measured for jets
containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass
energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The
measurements use data corresponding to an integrated luminosity of 34 pb^-1.
The b-jets are identified using either a lifetime-based method, where secondary
decay vertices of b-hadrons in jets are reconstructed using information from
the tracking detectors, or a muon-based method where the presence of a muon is
used to identify semileptonic decays of b-hadrons inside jets. The inclusive
b-jet cross-section is measured as a function of transverse momentum in the
range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet
cross-section is measured as a function of the dijet invariant mass in the
range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets
and the angular variable chi in two dijet mass regions. The results are
compared with next-to-leading-order QCD predictions. Good agreement is observed
between the measured cross-sections and the predictions obtained using POWHEG +
Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet
cross-section. However, it does not reproduce the measured inclusive
cross-section well, particularly for central b-jets with large transverse
momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final
version published in European Physical Journal
Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV
The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration
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