We present ground-based and Swift observations of iPTF16fnl, a likely tidal disruption event (TDE) discovered by the intermediate Palomar Transient Factory (iPTF) survey at 66.6 Mpc. The light curve ...of the object peaked at an absolute mag . The maximum bolometric luminosity (from optical and UV) was erg s−1, an order of magnitude fainter than any other optical TDE discovered so far. The luminosity in the first 60 days is consistent with an exponential decay, with , where t0 = 57631.0 (MJD) and days. The X-ray shows a marginal detection at erg s−1 (Swift X-ray Telescope). No radio counterpart was detected down to 3 , providing upper limits for monochromatic radio luminosities of erg s−1 and erg s−1 (Very Large Array, 6.1 and 22 GHz). The blackbody temperature, obtained from combined Swift UV and optical photometry, shows a constant value of 19,000 K. The transient spectrum at peak is characterized by broad He ii and H emission lines, with FWHMs of about 14,000 km s−1 and 10,000 km s−1, respectively. He i lines are also detected at λλ 5875 and 6678. The spectrum of the host is dominated by strong Balmer absorption lines, which are consistent with a post-starburst (E+A) galaxy with an age of ∼650 Myr and solar metallicity. The characteristics of iPTF16fnl make it an outlier on both luminosity and decay timescales, as compared to other optically selected TDEs. The discovery of such a faint optical event suggests a higher rate of tidal disruptions, as low-luminosity events may have gone unnoticed in previous searches.
Research on automatic identification of impact craters on Mars and other planetary bodies has concentrated on detecting them from imagery data. We present a novel approach to crater detection that ...utilizes digital topography data instead of images. Craters are delineated by topographic curvature. Thresholding maps of curvature transforms topographic data into a binary image, from which craters are identified using a combination of segmentation and detection algorithms. We apply our method to a large and technically demanding test site and compare the results to the existing catalog of manually identified craters. Our algorithm finds many small craters not listed in the manual catalog, but it fails to detect heavily degraded craters. A detailed quality assessment of the algorithm is presented. The topography-based crater-detection algorithm offers a relatively simple and ready-to-use tool for identification and characterization of fresh impact craters with an adequate performance for the immediate application to Martian geomorphology
Early observations of Type Ia supernovae (SNe Ia) provide a unique probe of their progenitor systems and explosion physics. Here we report the intermediate Palomar Transient Factory (iPTF) discovery ...of an extraordinarily young SN Ia, iPTF 16abc. By fitting a power law to our early light curve, we infer that first light for the SN, that is, when the SN could have first been detected by our survey, occurred only days before our first detection. In the ∼24 hr after discovery, iPTF 16abc rose by ∼2 mag, featuring a near-linear rise in flux for days. Early spectra show strong C ii absorption, which disappears after ∼7 days. Unlike the extensively observed Type Ia SN 2011fe, the colors of iPTF 16abc are blue and nearly constant in the days after explosion. We show that our early observations of iPTF 16abc cannot be explained by either SN shock breakout and the associated, subsequent cooling or the SN ejecta colliding with a stellar companion. Instead, we argue that the early characteristics of iPTF 16abc, including (i) the rapid, near-linear rise, (ii) the nonevolving blue colors, and (iii) the strong C ii absorption, are the result of either ejecta interaction with nearby, unbound material or vigorous mixing of radioactive 56Ni in the SN ejecta, or a combination of the two. In the next few years, dozens of very young normal SNe Ia will be discovered, and observations similar to those presented here will constrain the white dwarf explosion mechanism.
We propose a numerical method for classification and characterization of landforms on Mars. The method provides an alternative to manual geomorphic mapping of the Martian surface. Digital elevation ...data is used to calculate several topographic attributes for each pixel in a landscape. Unsupervised classification, based on the self-organizing map technique, divides all pixels into mutually exclusive and exhaustive landform classes on the basis of similarity between attribute vectors. The results are displayed as a thematic map of landforms and statistics of attributes are used to assign semantic meaning to the classes. This method is used to produce a geomorphic map of the Terra Cimmeria region on Mars. We assess the quality of the automated classification and discuss differences between results of automated and manual mappings. Potential applications of our method, including crater counting, landscape feature search, and large scale quantitative comparisons of Martian surface morphology, are identified and evaluated.
At local scales, emissions of methane and carbon dioxide are highly uncertain. Localized sources of both trace gases can create strong local gradients in its columnar abundance, which can be ...discerned using absorption spectroscopy at high spatial resolution. In a previous study, more than 250 methane plumes were observed in the San Juan Basin near Four Corners during April 2015 using the next-generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) and a linearized matched filter. For the first time, we apply the iterative maximum a posteriori differential optical absorption spectroscopy (IMAP-DOAS) method to AVIRIS-NG data and generate gas concentration maps for methane, carbon dioxide, and water vapor plumes. This demonstrates a comprehensive greenhouse gas monitoring capability that targets methane and carbon dioxide, the two dominant anthropogenic climate-forcing agents. Water vapor results indicate the ability of these retrievals to distinguish between methane and water vapor despite spectral interference in the shortwave infrared. We focus on selected cases from anthropogenic and natural sources, including emissions from mine ventilation shafts, a gas processing plant, tank, pipeline leak, and natural seep. In addition, carbon dioxide emissions were mapped from the flue-gas stacks of two coal-fired power plants and a water vapor plume was observed from the combined sources of cooling towers and cooling ponds. Observed plumes were consistent with known and suspected emission sources verified by the true color AVIRIS-NG scenes and higher-resolution Google Earth imagery. Real-time detection and geolocation of methane plumes by AVIRIS-NG provided unambiguous identification of individual emission source locations and communication to a ground team for rapid follow-up. This permitted verification of a number of methane emission sources using a thermal camera, including a tank and buried natural gas pipeline.
Machine cataloging of impact craters on Mars Stepinski, Tomasz F.; Mendenhall, Michael P.; Bue, Brian D.
Icarus (New York, N.Y. 1962),
09/2009, Letnik:
203, Številka:
1
Journal Article
Recenzirano
This study presents an automated system for cataloging impact craters using the MOLA 128
pixels/degree digital elevation model of Mars. Craters are detected by a two-step algorithm that first ...identifies round and symmetric topographic depressions as crater candidates and then selects craters using a machine-learning technique. The system is robust with respect to surface types; craters are identified with similar accuracy from all different types of martian surfaces without adjusting input parameters. By using a large training set in its final selection step, the system produces virtually no false detections. Finally, the system provides a seamless integration of crater detection with its characterization. Of particular interest is the ability of our algorithm to calculate crater depths. The system is described and its application is demonstrated on eight large sites representing all major types of martian surfaces. An evaluation of its performance and prospects for its utilization for global surveys are given by means of detailed comparison of obtained results to the manually-derived Catalog of Large Martian Impact Craters. We use the results from the test sites to construct local depth–diameter relationships based on a large number of craters. In general, obtained relationships are in agreement with what was inferred on the basis of manual measurements. However, we have found that, in Terra Cimmeria, the depth/diameter ratio has an abrupt decrease at ∼38°S regardless of crater size. If shallowing of craters is attributed to presence of sub-surface ice, a sudden change in its spatial distribution is suggested by our findings.
Visible–shortwave infrared imaging spectroscopy provides valuable remote
measurements of Earth's surface and atmospheric properties. These
measurements generally rely on inversions of computationally ...intensive
radiative transfer models (RTMs). RTMs' computational expense makes them
difficult to use with high-volume imaging spectrometers, and forces
approximations such as lookup table interpolation and surface–atmosphere
decoupling. These compromises limit the accuracy and flexibility of the
remote retrieval; dramatic speed improvements in radiative transfer models
could significantly improve the utility and interpretability of remote
spectroscopy for Earth science. This study demonstrates that nonparametric
function approximation with neural networks can replicate radiative transfer
calculations and generate accurate radiance spectra at multiple wavelengths
over a diverse range of surface and atmosphere state parameters. We also
demonstrate such models can act as surrogate forward models for atmospheric
correction procedures. Incorporating physical knowledge into the network
structure provides improved interpretability and model efficiency. We
evaluate the approach in atmospheric correction of data from the PRISM
airborne imaging spectrometer, and demonstrate accurate emulation of
radiative transfer calculations, which run several orders of magnitude faster
than first-principles models. These results are particularly amenable to
iterative spectrum fitting approaches, providing analytical benefits
including statistically rigorous treatment of uncertainty and the potential
to recover information on spectrally broad signals.
Abstract
In the summer of 2020, the AVIRIS-NG airborne imaging spectrometer surveyed California’s Southern San Joaquin Valley and the South Bay (Los Angeles County) to identify anthropogenic methane ...(CH
4
) point source plumes, estimate emission rates, and attribute sources to both facilities and emission sectors. These flights were designed to revisit regions previously surveyed by the 2016–2017 California Methane Survey and to assess the socioeconomic responses of COVID-19 on emissions across multiple sectors. For regions flown by both the California Methane Survey and the California COVID campaigns, total CH
4
point source emissions from the energy and oil & natural gas sectors were 34.8% lower during the summer 2020 flights, however, emission trends varied across sector. For the energy sector, there was a 28.2% decrease driven by reductions in refinery emissions consistent with a drop in production, which was offset in part with increases from powerplants. For the oil & natural gas sector, CH
4
emissions declined 34.2% and significant variability was observed at the oilfield scale. Emissions declined for all but the Buena Vista and Cymric fields with an observed positive relationship between production and emissions. In addition to characterizing the short-term impact of COVID-19 on CH
4
emissions, this study demonstrates the broader potential of remote sensing with sufficient sensitivity, spatial resolution, and spatio-temporal completeness to quantify changes in CH
4
emissions at the scale of key sectors and facilities.
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