2,134 research outputs found

    Sensing electric fields using single diamond spins

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    The ability to sensitively detect charges under ambient conditions would be a fascinating new tool benefitting a wide range of researchers across disciplines. However, most current techniques are limited to low-temperature methods like single-electron transistors (SET), single-electron electrostatic force microscopy and scanning tunnelling microscopy. Here we open up a new quantum metrology technique demonstrating precision electric field measurement using a single nitrogen-vacancy defect centre(NV) spin in diamond. An AC electric field sensitivity reaching ~ 140V/cm/\surd Hz has been achieved. This corresponds to the electric field produced by a single elementary charge located at a distance of ~ 150 nm from our spin sensor with averaging for one second. By careful analysis of the electronic structure of the defect centre, we show how an applied magnetic field influences the electric field sensing properties. By this we demonstrate that diamond defect centre spins can be switched between electric and magnetic field sensing modes and identify suitable parameter ranges for both detector schemes. By combining magnetic and electric field sensitivity, nanoscale detection and ambient operation our study opens up new frontiers in imaging and sensing applications ranging from material science to bioimaging

    Observation of anomalous decoherence effect in a quantum bath at room temperature

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    Decoherence of quantum objects is critical to modern quantum sciences and technologies. It is generally believed that stronger noises cause faster decoherence. Strikingly, recent theoretical research discovers the opposite case for spins in quantum baths. Here we report experimental observation of the anomalous decoherence effect for the electron spin-1 of a nitrogen-vacancy centre in high-purity diamond at room temperature. We demonstrate that under dynamical decoupling, the double-transition can have longer coherence time than the single-transition, even though the former couples to the nuclear spin bath as twice strongly as the latter does. The excellent agreement between the experimental and the theoretical results confirms the controllability of the weakly coupled nuclear spins in the bath, which is useful in quantum information processing and quantum metrology.Comment: 22 pages, related paper at http://arxiv.org/abs/1102.557

    On the State Complexity of Partial Derivative Automata For Regular Expressions with Intersection

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    Extended regular expressions (with complement and intersection) are used in many applications due to their succinctness. In particular, regular expressions extended with intersection only (also called semi-extended) can already be exponentially smaller than standard regular expressions or equivalent nondeterministic finite automata (NFA). For practical purposes it is important to study the average behaviour of conversions between these models. In this paper, we focus on the conversion of regular expressions with intersection to nondeterministic finite automata, using partial derivatives and the notion of support. First, we give a tight upper bound of 2O(n) for the worst-case number of states of the resulting partial derivative automaton, where n is the size of the expression. Using the framework of analytic combinatorics, we then establish an upper bound of (1.056 + o(1))n for its asymptotic average-state complexity, which is significantly smaller than the one for the worst case. (c) IFIP International Federation for Information Processing 2016

    Quantum control of proximal spins using nanoscale magnetic resonance imaging

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    Quantum control of individual spins in condensed matter systems is an emerging field with wide-ranging applications in spintronics, quantum computation, and sensitive magnetometry. Recent experiments have demonstrated the ability to address and manipulate single electron spins through either optical or electrical techniques. However, it is a challenge to extend individual spin control to nanoscale multi-electron systems, as individual spins are often irresolvable with existing methods. Here we demonstrate that coherent individual spin control can be achieved with few-nm resolution for proximal electron spins by performing single-spin magnetic resonance imaging (MRI), which is realized via a scanning magnetic field gradient that is both strong enough to achieve nanometric spatial resolution and sufficiently stable for coherent spin manipulations. We apply this scanning field-gradient MRI technique to electronic spins in nitrogen-vacancy (NV) centers in diamond and achieve nanometric resolution in imaging, characterization, and manipulation of individual spins. For NV centers, our results in individual spin control demonstrate an improvement of nearly two orders of magnitude in spatial resolution compared to conventional optical diffraction-limited techniques. This scanning-field-gradient microscope enables a wide range of applications including materials characterization, spin entanglement, and nanoscale magnetometry.Comment: 7 pages, 4 figure

    RNA secondary structure prediction from multi-aligned sequences

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    It has been well accepted that the RNA secondary structures of most functional non-coding RNAs (ncRNAs) are closely related to their functions and are conserved during evolution. Hence, prediction of conserved secondary structures from evolutionarily related sequences is one important task in RNA bioinformatics; the methods are useful not only to further functional analyses of ncRNAs but also to improve the accuracy of secondary structure predictions and to find novel functional RNAs from the genome. In this review, I focus on common secondary structure prediction from a given aligned RNA sequence, in which one secondary structure whose length is equal to that of the input alignment is predicted. I systematically review and classify existing tools and algorithms for the problem, by utilizing the information employed in the tools and by adopting a unified viewpoint based on maximum expected gain (MEG) estimators. I believe that this classification will allow a deeper understanding of each tool and provide users with useful information for selecting tools for common secondary structure predictions.Comment: A preprint of an invited review manuscript that will be published in a chapter of the book `Methods in Molecular Biology'. Note that this version of the manuscript may differ from the published versio

    Potential climatic transitions with profound impact on Europe

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    We discuss potential transitions of six climatic subsystems with large-scale impact on Europe, sometimes denoted as tipping elements. These are the ice sheets on Greenland and West Antarctica, the Atlantic thermohaline circulation, Arctic sea ice, Alpine glaciers and northern hemisphere stratospheric ozone. Each system is represented by co-authors actively publishing in the corresponding field. For each subsystem we summarize the mechanism of a potential transition in a warmer climate along with its impact on Europe and assess the likelihood for such a transition based on published scientific literature. As a summary, the ‘tipping’ potential for each system is provided as a function of global mean temperature increase which required some subjective interpretation of scientific facts by the authors and should be considered as a snapshot of our current understanding. <br/

    Strengthening seasonal marine CO2 variations due to increasing atmospheric CO2

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    The increase of atmospheric CO2 (ref. 1) has been predicted to impact the seasonal cycle of inorganic carbon in the global ocean2,3, yet the observational evidence to verify this prediction has been missing. Here, using an observation-based product of the oceanic partial pressure of CO2 (pCO2) covering the past 34 years, we find that the winter-to-summer difference of the pCO2 has increased on average by 2.2 ± 0.4 μatm per decade from 1982 to 2015 poleward of 10° latitude. This is largely in agreement with the trend expected from thermodynamic considerations. Most of the increase stems from the seasonality of the drivers acting on an increasing oceanic pCO2 caused by the uptake of anthropogenic CO2 from the atmosphere. In the high latitudes, the concurrent ocean-acidification-induced changes in the buffer capacity of the ocean enhance this effect. This strengthening of the seasonal winter-to-summer difference pushes the global ocean towards critical thresholds earlier, inducing stress to ocean ecosystems and fisheries4. Our study provides observational evidence for this strengthening seasonal difference in the oceanic carbon cycle on a global scale, illustrating the inevitable consequences of anthropogenic CO2 emissions

    A characteristics framework for Semantic Information Systems Standards

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    Semantic Information Systems (IS) Standards play a critical role in the development of the networked economy. While their importance is undoubted by all stakeholders—such as businesses, policy makers, researchers, developers—the current state of research leaves a number of questions unaddressed. Terminological confusion exists around the notions of “business semantics”, “business-to-business interoperability”, and “interoperability standards” amongst others. And, moreover, a comprehensive understanding about the characteristics of Semantic IS Standards is missing. The paper addresses this gap in literature by developing a characteristics framework for Semantic IS Standards. Two case studies are used to check the applicability of the framework in a “real-life” context. The framework lays the foundation for future research in an important field of the IS discipline and supports practitioners in their efforts to analyze, compare, and evaluate Semantic IS Standard

    Representation of Time-Varying Stimuli by a Network Exhibiting Oscillations on a Faster Time Scale

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    Sensory processing is associated with gamma frequency oscillations (30–80 Hz) in sensory cortices. This raises the question whether gamma oscillations can be directly involved in the representation of time-varying stimuli, including stimuli whose time scale is longer than a gamma cycle. We are interested in the ability of the system to reliably distinguish different stimuli while being robust to stimulus variations such as uniform time-warp. We address this issue with a dynamical model of spiking neurons and study the response to an asymmetric sawtooth input current over a range of shape parameters. These parameters describe how fast the input current rises and falls in time. Our network consists of inhibitory and excitatory populations that are sufficient for generating oscillations in the gamma range. The oscillations period is about one-third of the stimulus duration. Embedded in this network is a subpopulation of excitatory cells that respond to the sawtooth stimulus and a subpopulation of cells that respond to an onset cue. The intrinsic gamma oscillations generate a temporally sparse code for the external stimuli. In this code, an excitatory cell may fire a single spike during a gamma cycle, depending on its tuning properties and on the temporal structure of the specific input; the identity of the stimulus is coded by the list of excitatory cells that fire during each cycle. We quantify the properties of this representation in a series of simulations and show that the sparseness of the code makes it robust to uniform warping of the time scale. We find that resetting of the oscillation phase at stimulus onset is important for a reliable representation of the stimulus and that there is a tradeoff between the resolution of the neural representation of the stimulus and robustness to time-warp. Author Summary Sensory processing of time-varying stimuli, such as speech, is associated with high-frequency oscillatory cortical activity, the functional significance of which is still unknown. One possibility is that the oscillations are part of a stimulus-encoding mechanism. Here, we investigate a computational model of such a mechanism, a spiking neuronal network whose intrinsic oscillations interact with external input (waveforms simulating short speech segments in a single acoustic frequency band) to encode stimuli that extend over a time interval longer than the oscillation's period. The network implements a temporally sparse encoding, whose robustness to time warping and neuronal noise we quantify. To our knowledge, this study is the first to demonstrate that a biophysically plausible model of oscillations occurring in the processing of auditory input may generate a representation of signals that span multiple oscillation cycles.National Science Foundation (DMS-0211505); Burroughs Wellcome Fund; U.S. Air Force Office of Scientific Researc

    Specialized interfaces of Smc5/6 control hinge stability and DNA association

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    The Structural Maintenance of Chromosomes (SMC) complexes: cohesin, condensin and Smc5/6 are involved in the organization of higher-order chromosome structure—which is essential for accurate chromosome duplication and segregation. Each complex is scaffolded by a specific SMC protein dimer (heterodimer in eukaryotes) held together via their hinge domains. Here we show that the Smc5/6-hinge, like those of cohesin and condensin, also forms a toroidal structure but with distinctive subunit interfaces absent from the other SMC complexes; an unusual ‘molecular latch’ and a functional ‘hub’. Defined mutations in these interfaces cause severe phenotypic effects with sensitivity to DNA-damaging agents in fission yeast and reduced viability in human cells. We show that the Smc5/6-hinge complex binds preferentially to ssDNA and that this interaction is affected by both ‘latch’ and ‘hub’ mutations, suggesting a key role for these unique features in controlling DNA association by the Smc5/6 complex
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