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Utilizing spatial filtering for analyzing structural configuration of Michigan Basin for application to remote sensing
Chemical analysis at the nanoscale is critical to advance our understanding of materials and systems from medicine and biology to material science and computing. Macroscale-observed phenomena in these systems are in the large part driven by processes that take place at the nanoscale and are highly heterogeneous. Therefore, there is a clear need to develop a new technology that enables correlative imaging of material functionalities with nanoscale spatial and chemical resolutions that will enable us to untangle the structure–function relationship of functional materials. As such, here, we report on the analytical figures of merit of the newly developed correlative chemical imaging technique of helium ion microscopy coupled with secondary ion mass spectrometry (HIM-SIMS) that enables multimodal topographical/chemical imaging of organic and inorganic materials at the nanoscale. In HIM-SIMS, a focused ion beam acts as a sputtering and ionization source for chemical analysis along with simultaneous high-resolution surface imaging, providing an unprecedented level of spatial resolution for gathering chemical information on organic and inorganic materials. In this work, we demonstrate HIM-SIMS as a platform for a next-generation tool for an in situ material design and analysis capable of down to 8 nm spatial resolution chemical imaging, layered metal structure imaging in depth profiling, single graphene layer detection, and spectral analysis of metals, metal oxides, and polymers.
While crystals of strongly correlated metals exhibit a diverse set of electronic ground states, few approaches exist for spatially modulating their properties. In this study, we demonstrate disorder-free control, on the micrometer scale, over the superconducting state in samples of the heavy-fermion superconductor CeIrIn 5 . We pattern crystals by focused ion beam milling to tailor the boundary conditions for the elastic deformation upon thermal contraction during cooling. The resulting nonuniform strain fields induce complex patterns of superconductivity, owing to the strong dependence of the transition temperature on the strength and direction of strain. These findings showcase a generic approach to manipulating electronic order on micrometer length scales in strongly correlated matter without compromising the cleanliness, stoichiometry, or mean free path.
The toolbox for imaging molecules is well-equipped today. Some techniques visualize the geometrical structure, others the electron density or electron orbitals. Molecules are many-body systems for which the correlation between the constituents is decisive and the spatial and the momentum distribution of one electron depends on those of the other electrons and the nuclei. Such correlations have escaped direct observation by imaging techniques so far. Here, we implement an imaging scheme which visualizes correlations between electrons by coincident detection of the reaction fragments after high energy photofragmentation. With this technique, we examine the H 2 two-electron wave function in which electron-electron correlation beyond the mean-field level is prominent. We visualize the dependence of the wave function on the internuclear distance. High energy photoelectrons are shown to be a powerful tool for molecular imaging. Finally, our study paves the way for future time resolved correlation imaging at FELs and laser based X-ray sources.
Traditional theories of the nuclear magnetic resonance (NMR) autocorrelation function for intra-molecular dipole pairs assume a single-exponential decay, yet the calculated autocorrelation of realistic systems displays a rich, multi-exponential behavior, resulting in anomalous NMR relaxation dispersion (i.e., frequency dependence). We develop an approach to model and interpret the multi-exponential intra-molecular autocorrelation using simple, physical models within a rigorous statistical mechanical development that encompasses both rotational diffusion and translational diffusion in the same framework. Here, we recast the problem of evaluating the autocorrelation in terms of averaging over a diffusion propagator whose evolution is described by a Fokker–Planck equation. The time-independent part admits an eigenfunction expansion, allowing us to write the propagator as a sum over modes. Each mode has a spatial part that depends on the specified eigenfunction and a temporal part that depends on the corresponding eigenvalue (i.e., correlation time) with a simple, exponential decay. The spatial part is a probability distribution of the dipole pair, analogous to the stationary states of a quantum harmonic oscillator. Drawing inspiration from the idea of inherent structures in liquids, we interpret each of the spatial contributions as a specific molecular mode. These modes can be used to model and predict the NMR dipole–dipole relaxation dispersion of fluids by incorporating phenomena on the molecular level. We validate our statistical mechanical description of the distribution in molecular modes with molecular dynamics simulations interpreted without any relaxation models or adjustable parameters: the most important poles in the Padé–Laplace transform of the simulated autocorrelation agree with the eigenvalues predicted by the theory
The emergent property of resilience is the ability of a system to return to an original state after a disturbance. Resilience may be used as an early warning system for significant or irreversible community transition, i.e., a community with diminishing or low resilience may be close to catastrophic shift in function or an irreversible collapse. Typically, resilience is quantified using recovery time, which may be difficult or impossible to directly measure in microbial systems. A recent study in the literature showed that under certain conditions, a set of spatial-based metrics termed recovery length, can be correlated to recovery time, and thus may be a reasonable alternative measure of resilience. As a limitation, however, this spatial metric of resilience is useful only for step-change perturbations. Building upon the concept of recovery length, we propose a more general form of the spatial metric of resilience that can be applied to any shape of perturbation profiles (i.e., a sharp or smooth gradient). We termed this new spatial measure “perturbation-adjusted spatial metric of resilience” (PASMORE). We demonstrate the applicability of the proposed metric using a mathematical model of a microbial mat. PASMORE can help identify when a system, such as a microbial community, is on the verge of collapse or nearing an irreversible transition across a tipping point.
Hot-wire anemometry measurements in an incompressible turbulent boundary-layer flow over a flat plate, at zero pressure gradient were made using two X-probes simultaneously. The over seven meters long flat plate installed within the wind tunnel generated an approximately 20-cm thick boundary layer, and R(theta) of about 4,000. The mean velocity and turbulence intensity data very close to the wall were measured with a single-wire. Space-time velocity fluctuation and shear-product correlation measurements enabled the calculation of large-scale structure convection velocity, inclination-angle to the wall, and spatial extent in space. The shear-product correlation results are reported for the first time.
Fluctuations and stochastic transitions are ubiquitous in nanometre-scale systems, especially in the presence of disorder. However, their direct observation has so far been impeded by a seemingly fundamental, signal-limited compromise between spatial and temporal resolution. Here we develop coherent correlation imaging (CCI) to overcome this dilemma. Our method begins by classifying recorded camera frames in Fourier space. Contrast and spatial resolution emerge by averaging selectively over same-state frames. Temporal resolution down to the acquisition time of a single frame arises independently from an exceptionally low misclassification rate, which we achieve by combining a correlation-based similarity metric with a modified, iterative hierarchical clustering algorithm. We apply CCI to study previously inaccessible magnetic fluctuations in a highly degenerate magnetic stripe domain state with nanometre-scale resolution. We uncover an intricate network of transitions between more than 30 discrete states. Our spatiotemporal data enable us to reconstruct the pinning energy landscape and to thereby explain the dynamics observed on a microscopic level. CCI massively expands the potential of emerging high-coherence X-ray sources and paves the way for addressing large fundamental questions such as the contribution of pinning and topology in phase transitions and the role of spin and charge order fluctuations in high-temperature superconductivity.
Background/Question/Methods: The complexity of plant-pollinator interactions, the large number of species involved, and the lack of species response functions present challenges to understanding how these critical interactions may be impacted by climate and land cover change on large scales. Given the importance of this interaction for terrestrial ecosystems, it is desirable to develop new approaches. We monitor the daily weight change of honey bee (Apis mellifera) colonies to record the phenology of the Honey Bee Nectar Flow (HBNF) in a volunteer network (honeybeenet.gsfc.nasa.gov). The records document the successful interaction of a generalist pollinator with a variety of plant resources. We extract useful HBNF phenology metrics for three seasons. Sites currently exist in 35 states/provinces in North America, with a concentration in the Mid-Atlantic region. HBNF metrics are compared to standard phenology metrics derived from remotely sensed vegetation indices from NASA's MODIS sensor and published results from NOAA's A VHRR. At any given time the percentage of plants producing nectar is usually a sma11 fraction of the total satellite sensor signal. We are interested in determining how well the 'bulk' satellite vegetation parameters relate to the phenology of the HBNF, and how it varies spatially on landscape to continental scales. Results/Conclusions: We found the median and peak seasonal HBNF dates to be robust, with variation between replicate scale hives of only a few days. We developed quality assessment protocols to identify abnormal colony artifacts. Temporally, the peak and median of the HBNF in the Mid-Atlantic show a significant advance of 0.58 d/y beginning about 1970, very similar to that observed by the A VHRR since 1982 (0.57 d/y). Spatially, the HBNF metrics are highly correlated with elevation and winter minimum temperature distribution, and exhibit significant but regionally coherent inter-annual variation. The relationship between median of the spring HBNF with the "Green-up" metric from the 500 meter MODIS NDVI phenology product, for sites throughout the Eastern US 2000-2009, is well described by a single linear fit (r(exp 2) = 0.72). We conclude.that for the tree-dominated areas of the Eastern US at least the spring HBNF can be tracked very well by MODIS phenology. Analysis of other regions and seasons is presently underway but with more limited data. Spatial patterns in the eastern US and management implications will be presented and discussed.
Evapotranspiration (ET) is a key component of the water balance, which influences hydrometeorology, water resources, carbon and other biogeochemical cycles, and ecosystem diversity. This study aims to investigate the spatio-temporal variations of ET at the East River watershed in Colorado and analyze the factors that control these variations. ET was acquired using the community land model (CLM) simulations and was compared with the values estimated using Fu’s equation and a watershed-scale water balance equation. The simulation results showed that 55% of annual precipitation in the East River is lost to ET, in which 75% of the ET comes from the summer months (May to September). We also found that the contribution of transpiration to the total ET was ~50%, which is much larger than that of soil evaporation (32%) and canopy evaporation (18%). Spatial analysis indicated that the ET is greater at elevations of 2950–3200 m and lower along the river valley (<2750 m) and at the high elevations (>3900 m). A correlation analysis of factors affecting ET showed that the land elevation, air temperature, and vegetation are closely correlated and together they govern the ET spatial variability. The results also suggested that ET in areas with more finely textured soil is slightly larger than regions with coarse-texture soil. This study presents a promising approach to the assessment of ET with a high spatiotemporal resolution over watershed scales and investigates factors controlling ET spatiotemporal variations.
Abstract. A mechanistic understanding of how tropical-tree mortality responds to climate variation is urgently needed to predict how tropical-forest carbon pools will respond to anthropogenic global change, which is altering the frequency and intensity of storms, droughts, and other climate extremes in tropical forests. We used 5 years of approximately monthly drone-acquired RGB (red–green–blue) imagery for 50 ha of mature tropical forest on Barro Colorado Island, Panama, to quantify spatial structure; temporal variation; and climate correlates of canopy disturbances, i.e., sudden and major drops in canopy height due to treefalls, branchfalls, or the collapse of standing dead trees. Canopy disturbance rates varied strongly over time and were higher in the wet season, even though wind speeds were lower in the wet season. The strongest correlate of monthly variation in canopy disturbance rates was the frequency of extreme rainfall events. The size distribution of canopy disturbances was best fit by a Weibull function and was close to a power function for sizes above 25 m2. Treefalls accounted for 74 % of the total area and 52 % of the total number of canopy disturbances in treefalls and branchfalls combined. We hypothesize that extremely high rainfall is a good predictor because it is an indicator of storms having high wind speeds, as well as saturated soils that increase uprooting risk. These results demonstrate the utility of repeat drone-acquired data for quantifying forest canopy disturbance rates at fine temporal and spatial resolutions over large areas, thereby enabling robust tests of how temporal variation in disturbance relates to climate drivers. Further insights could be gained by integrating these canopy observations with high-frequency measurements of wind speed and soil moisture in mechanistic models to better evaluate proximate drivers and with focal tree observations to quantify the links to tree mortality and woody turnover.
We investigate the inhomogeneity of kinetic and magnetic dissipations in thermal convection using high-resolution calculations. In statistically steady turbulence, the injected and dissipated energies are balanced. This means that a large amount of energy is continuously converted into internal energy via dissipation. As in thermal convection, downflows are colder than upflows and the inhomogeneity of the dissipation potentially changes the convection structure. Our investigation of the inhomogeneity of the dissipation shows the following. (1) More dissipation is seen around the bottom of the calculation domain, and this tendency is promoted with the magnetic field. (2) The dissipation in the downflow is much larger than that in the upflow. The dissipation in the downflow is more than 80% of the total at maximum. This tendency is also promoted with the magnetic field. (3) Although 2D probability density functions of the kinetic and magnetic dissipations versus the vertical velocity are similar, the kinetic and magnetic dissipations are not well correlated. Our result suggests that the spatial inhomogeneity of the dissipation is significant and should be considered when modeling a small-scale strong magnetic field generated with an efficient small-scale dynamo for low-resolution calculations.
For automation and robotics in the Space Station era, NASA's Johnson Space Center is pursuing several means of synthetic vision. The optical correlator is one such means. The deformable mirror device will form the basis of the first correlator in this project. In-house and contracted effort is being used. Initial in-house activities will concentrate on an impulse deconvolution technique and on a programmable retina for spatial remappings of an image prior to correlation. The retina will permit a form of edge extraction and other primitive operations. Additionally, it will be used as a research tool for assisting persons with low vision.
Whistler mode chorus waves are particularly important in outer radiation belt dynamics due to their key role in controlling the acceleration and scattering of electrons over a very wide energy range. The key parameters for both nonlinear and quasi-linear treatment of wave-particle interactions are the temporal and spatial scales of the wave source region and coherence of the wave field perturbations. Neither the source scale nor the coherence scale is well established experimentally, mostly because of a lack of multipoint VLF waveform measurements. We present an unprecedentedly long interval of coordinated VLF waveform measurements (sampled at 16384 s(exp -1)) aboard the two Van Allen Probes spacecraft-9 h (0800-1200 UT and 1700-2200 UT) during two consecutive apogees on 15 July 2014. The spacecraft separations varied from about 100 to 5000 km (mostly radially); measurements covered an L shell range from 3 to 6; magnetic local time 0430-0900, and magnetic latitudes were approximately 15 and approximately 5 deg during the two orbits. Using time-domain correlation techniques, the single chorus source spatial extent transverse to the background magnetic field has been determined to be about 550-650 km for upper band chorus waves with amplitudes less than 100 pT and up to 800 km for larger amplitude, lower band chorus waves. The ratio between wave amplitudes measured on the two spacecraft is also examined to reveal that the wave amplitude distribution within a single chorus element generation area can be well approximated by a Gaussian exp(-0.5 x r (exp 2)/r(sub 0)(exp 2)), with the characteristic scale r(sub 0) around 300 km. Waves detected by the two spacecraft were found to be coherent in phase at distances up to 400 km.
Large, complex, active regions may produce multiple flares within a certain period of one or two days. These flares could occur in the same location with similar morphologies, commonly referred to as 'homologous flares'. In 2011 September, active region NOAA 11283 produced a pair of homologous flares on the 6th and 7th, respectively. Both of them were white-light (WL) flares, as captured by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory in visible continuum at 6173 Å which is believed to originate from the deep solar atmosphere. We investigate the WL emission of these X-class flares with HMI's seeing-free imaging spectroscopy. The durations of impulsive peaks in the continuum are about 4 minutes. We compare the WL with hard X-ray (HXR) observations for the September 6 flare and find a good correlation between the continuum and HXR both spatially and temporally. In absence of RHESSI data during the second flare on September 7, the derivative of the GOES soft X-ray is used and also found to be well correlated temporally with the continuum. We measure the contrast enhancements, characteristic sizes, and HXR fluxes of the twin flares, which are similar for both flares, indicating analogous triggering and heating processes. However, the September 7 flare was associated with conspicuous sunquake signals whereas no seismic wave was detected during the flare on September 6. Therefore, this comparison suggests that the particle bombardment may not play a dominant role in producing the sunquake events studied in this paper.
Among the multitude of methods used to investigate coronal heating, the time lag method of Viall and Klimchuk is becoming increasingly prevalent as an analysis technique that is complementary to those that are traditionally used. The time lag method cross correlates light curves at a given spatial location obtained in spectral bands that sample different temperature plasmas. It has been used most extensively with data from the Atmospheric Imaging Assembly on the Solar Dynamics Observatory . We have previously applied the time lag method to entire active regions and surrounding the quiet Sun and created maps of the results. We find that the majority of time lags are consistent with the cooling of coronal plasma that has been impulsively heated. Additionally, a significant fraction of the map area has a time lag of zero. This does not indicate a lack of variability. Rather, strong variability must be present, and it must occur in phase between the different channels. We have previously shown that these zero time lags are consistent with the transition region response to coronal nanoflares, although other explanations are possible. A common misconception is that the zero time lag indicates steady emission resulting from steady heating. Using simulated and observed light curves, we demonstrate here that highly correlated light curves at zero time lag are not compatible with equilibrium solutions. Such light curves can only be created by evolution.
Among the multitude of methods used to investigate coronal heating, the time lag method of Viall Klimchuk is becoming increasingly prevalent as an analysis technique that is complementary to those that are traditionally used.The time lag method cross correlates light curves at a given spatial location obtained in spectral bands that sample different temperature plasmas. It has been used most extensively with data from the Atmospheric Imaging Assembly on the Solar Dynamics Observatory. We have previously applied the time lag method to entire active regions and surrounding the quiet Sun and created maps of the results. We find that the majority of time lags are consistent with the cooling of coronal plasma that has been impulsively heated. Additionally, a significant fraction of the map area has a time lag of zero. This does not indicate a lack of variability. Rather, strong variability must be present, and it must occur in phase between the different channels. We have previously shown that these zero time lags are consistent with the transition region response to coronal nanoflares, although other explanations are possible. A common misconception is that the zero time lag indicates steady emission resulting from steady heating. Using simulated and observed light curves, we demonstrate here that highly correlated light curves at zero time lag are not compatible with equilibrium solutions. Such light curves can only be created by evolution