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- ISM: individual objects (RX J1713.7-3946, G347.3-0.5) (1)
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Prospects for Cherenkov Telescope Array Observations of the Young Supernova Remnant RX J1713.7-3946
(2017)
We perform simulations for future Cherenkov Telescope Array (CTA) observations of RX J1713.7-3946, a young supernova remnant (SNR) and one of the brightest sources ever discovered in very high energy (VHE) gamma rays. Special attention is paid to exploring possible spatial (anti) correlations of gamma rays with emission at other wavelengths, in particular X-rays and CO/H I emission. We present a series of simulated images of RX J1713.7-3946 for CTA based on a set of observationally motivated models for the gamma-ray emission. In these models, VHE gamma rays produced by high-energy electrons are assumed to trace the nonthermal X-ray emission observed by XMM-Newton, whereas those originating from relativistic protons delineate the local gas distributions. The local atomic and molecular gas distributions are deduced by the NANTEN team from CO and H I observations. Our primary goal is to show how one can distinguish the emission mechanism(s) of the gamma rays (i.e., hadronic versus leptonic, or a mixture of the two) through information provided by their spatial distribution, spectra, and time variation. This work is the first attempt to quantitatively evaluate the capabilities of CTA to achieve various proposed scientific goals by observing this important cosmic particle accelerator.
Moving in the Anthropocene
(2018)
Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.
Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area
) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.
We studied the photoinduced ultrafast relaxation dynamics of the nucleobase thymine using gas-phase time-resolved photoelectron spectroscopy. By employing extreme ultraviolet pulses from high harmonic generation for photoionization, we substantially extend our spectral observation window with respect to previous studies. This enables us to follow relaxation of the excited state population all the way to low-lying electronic states including the ground state. In thymine, we observe relaxation from the optically bright (1)pi pi* state of thymine to a dark (1)n pi* state within 80 +/- 30 fs. The (1)n pi* state relaxes further within 3.5 +/- 0.3 ps to a low-lying electronic state. By comparison with quantum chemical simulations, we can unambiguously assign its spectroscopic signature to the (3)pi pi* state. Hence, our study draws a comprehensive picture of the relaxation mechanism of thymine including ultrafast intersystem crossing to the triplet manifold.
The high resolution near edge X-ray absorption fine structure spectrum of nitrogen displays the vibrational structure of the core-excited states. This makes nitrogen well suited for assessing the accuracy of different electronic structure methods for core excitations. We report high resolution experimental measurements performed at the SOLEIL synchrotron facility. These are compared with theoretical spectra calculated using coupled cluster theory and algebraic diagrammatic construction theory. The coupled cluster singles and doubles with perturbative triples model known as CC3 is shown to accurately reproduce the experimental excitation energies as well as the spacing of the vibrational transitions. The computational results are also shown to be systematically improved within the coupled cluster hierarchy, with the coupled cluster singles, doubles, triples, and quadruples method faithfully reproducing the experimental vibrational structure. Published by AIP Publishing.
The motion of tectonic plates is accommodated at fault zones. One of the unanswered questions about fault zones relates to the role they play in controlling shallow and local hydrology. This study focuses on the Arava/Araba Fault (AF) zone, the southern portion of the Dead Sea Transform (DST) in the Middle East. We combine seismic and electromagnetic methods (EM) to image the geometry and map the petro-physical properties and water occurrence in the top 100 m of this active fault. For three profiles, P-velocity and resistivity images were derived independently. Using a neural network cluster analysis three classes with similar P-velocity and resistivities could then be determined from these images. These classes correspond to spatial domains of specific material and wetness. The first class occurs primarily east of the fault consisting of 'wet' sand (dunes) and brecciated sediments, whereas the second class composed of similar material located west of the fault is 'dry'. The third class lies at depth below ca. 50 m and is composed of highly deformed and weathered Precambrian rocks that constitute the multi-branch fault zone of the AF at this location. The combination of two independent measurements like seismics and EM linked by a stringent mathematical approach has thus shown the potential to delineate the interplay of lithology and water near active faults.