4,517 research outputs found

    Spitzer spectroscopy of circumstellar disks in the 5 Myr old upper Scorpius OB association

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    We present mid-infrared spectra between 5.2 and 38 μm for 26 disk-bearing members of the ~5 Myr old Upper Scorpius OB association obtained with the Infrared Spectrograph (IRS) onboard the Spitzer Space Telescope. We find clear evidence for changes in the spectral characteristics of dust emission between the early-type (B+A) and late-type (K+M) infrared excess stars. The early-type members exhibit featureless continuum excesses that become apparent redward of ~8 μm. In contrast, 10 and 20 μm silicate features or polycyclic aromatic hydrocarbon emission are present in all but one of the late-type excess members of Upper Scorpius. The strength of silicate emission among late-type Upper Scorpius members is spectral-type dependent, with the most prominent features being associated with K5-M2-type stars. By fitting the spectral energy distributions (SED) of a representative sample of low-mass stars with accretion disk models, we find that the SEDs are consistent with models having inner disk radii ranging from ~0.2 to 1.2 AU. Complementary high-resolution (R ~ 33,000) optical (λλ4800-9200) spectra for the Upper Scorpius excess stars were examined for signatures of gaseous accretion. Of the 35 infrared excess stars identified in Upper Scorpius, only seven (all late-type) exhibit definitive signatures of accretion. Mass-accretion rates (M) for these stars were estimated to range from 10^–11 to 10^–8.9 M⊙ yr^–1. Compared to Class II sources in Taurus-Auriga, the disk population in Upper Scorpius exhibits reduced levels of near- and mid-infrared excess emission and an order of magnitude lower mass-accretion rates. These results suggest that the disk structure has changed significantly over the 2-4 Myr in age separating these two stellar populations. The ubiquity of depleted inner disks in the Upper Scorpius excess sample implies that such disks are a common evolutionary pathway that persists for some time

    An ALMA Continuum Survey of Circumstellar Disks in the Upper Scorpius OB Association

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    We present ALMA 880 micron continuum observations of 20 K and M-type stars in the Upper Scorpius OB association that are surrounded by protoplanetary disks. These data are used to measure the dust content in disks around low mass stars (0.1-1.6 Msun) at a stellar age of 5-11 Myr. Thirteen sources were detected in the 880 micron dust continuum at >3 sigma with inferred dust masses between 0.3 and 52 Mearth. The dust masses tend to be higher around the more massive stars, but the significance is marginal in that the probability of no correlation is p ~ 0.03. The evolution in the dust content in disks was assessed by comparing the Upper Sco observations with published continuum measurements of disks around ~ 1-2 Myr stars in the Class II stage in the Taurus molecular cloud. While the dust masses in the Upper Sco disks are on average lower than in Taurus, any difference in the dust mass distributions is significant at less than 3sigma. For stellar masses between 0.49 Msun and 1.6 Msun, the mean dust mass in disks is lower in Upper Sco relative to Taurus by Delta log Mdust = 0.44 +/-0.26.Comment: Accepted by Ap

    ARTMAP: Supervised Real-Time Learning and Classification of Nonstationary Data by a Self-Organizing Neural Network

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    This article introduces a new neural network architecture, called ARTMAP, that autonomously learns to classify arbitrarily many, arbitrarily ordered vectors into recognition categories based on predictive success. This supervised learning system is built up from a pair of Adaptive Resonance Theory modules (ARTa and ARTb) that are capable of self-organizing stable recognition categories in response to arbitrary sequences of input patterns. During training trials, the ARTa module receives a stream {a^(p)} of input patterns, and ARTb receives a stream {b^(p)} of input patterns, where b^(p) is the correct prediction given a^(p). These ART modules are linked by an associative learning network and an internal controller that ensures autonomous system operation in real time. During test trials, the remaining patterns a^(p) are presented without b^(p), and their predictions at ARTb are compared with b^(p). Tested on a benchmark machine learning database in both on-line and off-line simulations, the ARTMAP system learns orders of magnitude more quickly, efficiently, and accurately than alternative algorithms, and achieves 100% accuracy after training on less than half the input patterns in the database. It achieves these properties by using an internal controller that conjointly maximizes predictive generalization and minimizes predictive error by linking predictive success to category size on a trial-by-trial basis, using only local operations. This computation increases the vigilance parameter ρa of ARTa by the minimal amount needed to correct a predictive error at ARTb· Parameter ρa calibrates the minimum confidence that ARTa must have in a category, or hypothesis, activated by an input a^(p) in order for ARTa to accept that category, rather than search for a better one through an automatically controlled process of hypothesis testing. Parameter ρa is compared with the degree of match between a^(p) and the top-down learned expectation, or prototype, that is read-out subsequent to activation of an ARTa category. Search occurs if the degree of match is less than ρa. ARTMAP is hereby a type of self-organizing expert system that calibrates the selectivity of its hypotheses based upon predictive success. As a result, rare but important events can be quickly and sharply distinguished even if they are similar to frequent events with different consequences. Between input trials ρa relaxes to a baseline vigilance pa When ρa is large, the system runs in a conservative mode, wherein predictions are made only if the system is confident of the outcome. Very few false-alarm errors then occur at any stage of learning, yet the system reaches asymptote with no loss of speed. Because ARTMAP learning is self stabilizing, it can continue learning one or more databases, without degrading its corpus of memories, until its full memory capacity is utilized.British Petroleum (98-A-1204); Defense Advanced Research Projects Agency (90-0083, 90-0175, 90-0128); National Science Foundation (IRI-90-00539); Army Research Office (DAAL-03-88-K0088

    High-order cyclo-difference techniques: An alternative to finite differences

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    The summation-by-parts energy norm is used to establish a new class of high-order finite-difference techniques referred to here as 'cyclo-difference' techniques. These techniques are constructed cyclically from stable subelements, and require no numerical boundary conditions; when coupled with the simultaneous approximation term (SAT) boundary treatment, they are time asymptotically stable for an arbitrary hyperbolic system. These techniques are similar to spectral element techniques and are ideally suited for parallel implementation, but do not require special collocation points or orthogonal basis functions. The principal focus is on methods of sixth-order formal accuracy or less; however, these methods could be extended in principle to any arbitrary order of accuracy

    Fuzzy ARTMAP, Slow Learning and Probability Estimation

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    A nonparametric probability estimation procedure using the fuzzy ARTMAP neural network is here described. Because the procedure does not make a priori assumptions about underlying probability distributions, it yields accurate estimates on a wide variety of prediction tasks. Fuzzy ARTMAP is used to perform probability estimation in two different modes. In a 'slow-learning' mode, input-output associations change slowly, with the strength of each association computing a conditional probability estimate. In 'max-nodes' mode, a fixed number of categories are coded during an initial fast learning interval, and weights are then tuned by slow learning. Simulations illustrate system performance on tasks in which various numbers of clusters in the set of input vectors mapped to a given class.British Petroleum (89-A-1204); Defense Advanced Research Projects Agency (AFOSR-90-0083, ONR-N00014-92-J-4015); National Science Foundation (IRI-90-00530); Office of Naval Research (N00014-91-J-4100); Air Force Office of Scientific Research (90-1075

    Near-Infrared Photometric Variability of Stars Toward the Orion A Molecular Cloud

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    We present an analysis of J, H, and K time series photometry obtained with the southern 2MASS telescope over a 0.84 x 6 deg^2 region centered near the Orion Nebula Cluster. These data are used to establish the near-infrared variability properties of pre-main-sequence stars in Orion on time scales of 1-36 days, 2 months, and 2 years. A total of 1235 variable stars are identified, ~93% of which are associated with the Orion A molecular cloud. The variable stars exhibit a diversity of photometric behavior with time, including cyclic fluctuations, aperiodic day-to-day fluctuations, eclipses, slow drifts in brightness over one month, colorless variability, stars that become redder as they fade, and stars that become bluer as they fade. We examine rotational modulation of cool and hot star spots, variable obscuration from an inner circumstellar disk, and changes in the mass accretion rate and other properties in a circumstellar disk as possible origins of the variability. Cool spots can explain the variability characteristics in 56-77% of the stars, while the properties of the photometric fluctuations are more consistent with hot spots or extinction changes in at least 23% of the stars, and with variations in the disk mass accretion rate or inner disk radius in 1% of our sample. However, differences between the details of the observations and the details of variability predicted these models suggest either that another variability mechanism not considered here may be operative, or that the observed variability represents the net results of several of these phenomena. Analysis of the star count data indicates that the ONC is part of a larger area of enhanced stellar surface density which extends over a 0.4 x 2.4 deg^2 (3.4 x 20 pc^2) region containing 2700 stars brighter than K=14. (abridged version)Comment: 75 pages with 27 figures; to appear in AJ; see also http://www.astro.caltech.edu/~jmc/variables/orio
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