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Industrial Control Systems: Cyber Security Risk Candidate Methods Analysis

In recognition of their mission and in response to continuously evolving cyber threats against nuclear facilities, Department of Energy - Nuclear Energy (DOE-NE) is building the Nuclear Energy Cyber security Research, Development, and Demonstration (RD&D) Program, which includes a cyber risk management thrust. This report supports the cyber risk management thrust objective which is to deliver "Standardized methodologies for credible risk-based identification, evaluation and prioritization of digital components." In a previous task, the Sandia National Laboratories (SNL) team presented evaluation criteria and a survey to review methods to determine the most suitable techniques. In this task we will identify and evaluate a series of candidate methodologies. In this report, 10 distinct methodologies are evaluated. The overall goal of this effort was to identify the current range of risk analysis techniques that were currently available, and how they could be applied, with an focus on industrial control systems (ICS). Overall, most of the techniques identified did fall into accepted risk analysis practices, though they generally addressed only one step of the multi-step risk management process. A few addressed multiple steps, but generally their treatment was superficial. This study revealed that the current state of security risk analysis in digital control systems was not comprehensive and did not support a science-based evaluation. The papers surveyed did use mathematical formulation to describe the addressed problems, and tied the models to some kind of experimental or experiential evidence as support. Most of the papers, however, did not use a rigorous approach to experimentally support the proposed models, nor did they have enough evidence supporting the efficacy of the models to statistically analyze model impact. Both of these issues stem from the difficulty and expense associated with collecting experimental data in this domain.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Operating displays - new concept: high performance displays - 118

New control rooms in Nuclear Power Plants using digital Distributed Control System (DCS) operated with software displays, are providing thousands of signals to the operating crew. When an event happens, the Flood of information provided to operators could obscure the initiator event increasing the operator response time, work load and complicating the selection of the actions to be performed. There are some initiatives that are trying to minimize the 'avalanche effect' as the alarm engineering filtering and prioritization or diagnostic displays. Likewise, new control rooms are lost the availability to know the plant status just with a quick glance to the panel indicators. Regarding Small Modular Reactors, where in some cases four operators should monitor and control twelve reactors, these problems are even more significant. The challenge is to find a solution, based on current digital systems, that supply information to operators in order to prevent events and take early actions to minimize or avoid any unexpected incident. In order to minimize human errors, Tecnatom has developed a specific set of displays, called 'High Performance Displays' (HPD) based on objectives, work environment limitation, and non-anticipated events. These displays are being design following the HFE standards: applying the NUREG-0711 elements to identify the information that they have to content and the NUREG-0700 to design the interface. The function of these displays is monitoring the plant situation in a way that the operators are able to recognize any potential event at a simple glance but controlling thousands of signals through pattern recognition, symmetries, regular polygons and colors. The objective of the HPD is to provide an integrated function minimizing the tunnel effect and reduce the workload during the diagnosis phase. Moreover, HPD enhance operators to take the right actions to anticipate the response to any event, even avoiding it, if possible This paper analyzes how HPD's have been design as well as presents the results of a preliminary validation of their capabilities. The preliminary validation is a reduce validation in a full scope simulator running two representative scenarios of abnormal and emergency operation. The analysis is focused on the first stage of the event, i.e. the detection phase, HPD's have been installed in a generic full scope simulator of a nuclear power plant, digital controlled. Both scenarios have been performed by two different operator crews. The first operator shift has worked with the conventional human machine interface, that is, displays similar to the ones currently installed in existing nuclear power plant with digital control. The second crew, reproduce the same scenarios but with HPD available. The studio collects preliminary data in order to compare results, draw lesson learned from the experience to improve HPD design, and find solutions in terms of reducing human errors, human workload, and increase the availability of the plant. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

AN ALL-SKY CATALOG OF BRIGHT M DWARFS

We present an all-sky catalog of M dwarf stars with apparent infrared magnitude J < 10. The 8889 stars are selected from the ongoing SUPERBLINK survey of stars with proper motion {mu} > 40 mas yr{sup -1}, supplemented on the bright end with the Tycho-2 catalog. Completeness tests which account for kinematic (proper motion) bias suggest that our catalog represents {approx}75% of the estimated {approx}11, 900 M dwarfs with J < 10 expected to populate the entire sky. Our catalog is, however, significantly more complete for the northern sky ({approx}90%) than it is for the south ({approx}60%). Stars are identified as cool, red M dwarfs from a combination of optical and infrared color cuts, and are distinguished from background M giants and highly reddened stars using either existing parallax measurements or, if such measurements are lacking, using their location in an optical-to-infrared reduced proper motion diagram. These bright M dwarfs are all prime targets for exoplanet surveys using the Doppler radial velocity or transit methods; the combination of low-mass and bright apparent magnitude should make possible the detection of Earth-size planets on short-period orbits using currently available techniques. Parallax measurements, when available, and photometric distance estimates are provided for all stars, and these place most systems within 60 pc of the Sun. Spectral type estimated from V - J color shows that most of the stars range from K7 to M4, with only a few late M dwarfs, all within 20 pc. Proximity to the Sun also makes these stars good targets for high-resolution exoplanet imaging searches, especially if younger objects can be identified on the basis of X-ray or UV excess. For that purpose, we include X-ray flux from ROSAT and FUV/NUV ultraviolet magnitudes from GALEX for all stars for which a counterpart can be identified in those catalogs. Additional photometric data include optical magnitudes from Digitized Sky Survey plates and infrared magnitudes from the Two Micron All Sky Survey.

79 ASTRONOMY AND ASTROPHYSICS↗

Discovery of eight z ∼ 6 quasars in the Sloan Digital Sky Survey overlap regions

We present the discovery of eight quasars at z∼6 identified in the Sloan Digital Sky Survey (SDSS) overlap regions. Individual SDSS imaging runs have some overlap with each other, leading to repeat observations over an area spanning >4000 deg{sup 2} (more than one-fourth of the total footprint). These overlap regions provide a unique data set that allows us to select high-redshift quasars more than 0.5 mag fainter in the z band than those found with the SDSS single-epoch data. Our quasar candidates were first selected as i-band dropout objects in the SDSS imaging database. We then carried out a series of follow-up observations in the optical and near-IR to improve photometry, remove contaminants, and identify quasars. The eight quasars reported here were discovered in a pilot study utilizing the overlap regions at high galactic latitude (|b|>30{sup ∘}). These quasars span a redshift range of 5.86<z<6.06 and a flux range of 19.3<z{sub AB}<20.6 mag. Five of them are fainter than z{sub AB}=20 mag, the typical magnitude limit of z∼6 quasars used for the SDSS single-epoch images. In addition, we recover eight previously known quasars at z∼6 that are located in the overlap regions. These results validate our procedure for selecting quasar candidates from the overlap regions and confirming them with follow-up observations, and they provide guidance to a future systematic survey over all SDSS imaging regions with repeat observations.

79 ASTRONOMY AND ASTROPHYSICS↗

The miniJPAS survey quasar selection – I. Mock catalogues for classification

In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar candidates. Since no representative sample of spectroscopically confirmed sources exists at present to train these ML algorithms, we rely on mock catalogues. In this first paper, we develop a pipeline to compute synthetic photometry of quasars, galaxies, and stars using spectra of objects targeted as quasars in the Sloan Digital Sky Survey . To match the same depths and signal-to-noise ratio distributions in all bands expected for miniJPAS point sources in the range 17.5 ≤ r < 24, we augment our sample of available spectra by shifting the original r-band magnitude distributions towards the faint end, ensure that the relative incidence rates of the different objects are distributed according to their respective luminosity functions, and perform a thorough modelling of the noise distribution in each filter, by sampling the flux variance either from Gaussian realizations with given widths, or from combinations of Gaussian functions. Finally, we also add in the mocks the patterns of non-detections which are present in all real observations. Although the mock catalogues presented in this work are a first step towards simulated data sets that match the properties of the miniJPAS observations, these mocks can be adapted to serve the purposes of other photometric surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

THE GALACTIC O-STAR SPECTROSCOPIC SURVEY (GOSSS). III. 142 ADDITIONAL O-TYPE SYSTEMS

This is the third installment of the Galactic O-Star Spectroscopic Survey (GOSSS), a massive spectroscopic survey of Galactic O stars, based on new homogeneous, high signal-to-noise ratio, R ∼ 2500 digital observations selected from the Galactic O-Star Catalog. In this paper, we present 142 additional stellar systems with O stars from both hemispheres, bringing the total of O-type systems published within the project to 590. Among the new objects, there are 20 new O stars. We also identify 11 new double-lined spectroscopic binaries, 6 of which are of O+O type and 5 of O+B type, and an additional new tripled-lined spectroscopic binary of O+O+B type. We also revise some of the previous GOSSS classifications, present some egregious examples of stars erroneously classified as O-type in the past, introduce the use of luminosity class IV at spectral types O4-O5.5, and adapt the classification scheme to the work of Arias et al.

79 ASTRONOMY AND ASTROPHYSICS↗

Automatic detection of cataclysmic variables from SDSS images

Abstract Investigating rare and new objects have always been an important direction in astronomy. Cataclysmic variables (CVs) are ideal and natural celestial bodies for studying the accretion process of semi-detached binaries with accretion processes. However, the sample size of CVs must increase because a lager gap exists between the observational and the theoretical expanding CVs. Astronomy has entered the big data era and can provide massive images containing CV candidates. CVs as a type of faint celestial objects, are highly challenging to be identified directly from images using automatic manners. Deep learning has rapidly developed in intelligent image processing and has been widely applied in some astronomical fields with excellent detection results. YOLOX, as the latest YOLO framework, is advantageous in detecting small and dark targets. This work proposes an improved YOLOX-based framework according to the characteristics of CVs and Sloan Digital Sky Survey (SDSS) photometric images to train and verify the model to realise CV detection. We use the Convolutional Block Attention Module to increase the number of output features with the feature extraction network and adjust the feature fusion network to obtain fused features. Accordingly, the loss function is modified. Experimental results demonstrate that the improved model produces satisfactory results, with average accuracy (mean average Precision at 0.5) of 92.0%, Precision of 92.9%, Recall of 94.3%, and $F1-score$ of 93.6% on the test set. The proposed method can efficiently achieve the identification of CVs in test samples and search for CV candidates in unlabeled images. The image data vastly outnumber the spectra in the SDSS-released data. With supplementary follow-up observations or spectra, the proposed model can help astronomers in seeking and detecting CVs in a new manner to ensure that a more extensive CV catalog can be built. The proposed model may also be applied to the detection of other kinds of celestial objects.

Astronomy & Astrophysics↗

GALACTIC S STARS: INVESTIGATIONS OF COLOR, MOTION, AND SPECTRAL FEATURES

Known bright S stars, recognized as such by their enhanced s-process abundances and C/O ratio, are typically members of the asymptotic giant branch (AGB) or the red giant branch. Few modern digital spectra for these objects have been published, from which intermediate resolution spectral indices and classifications could be derived. For published S stars, we find accurate positions using the Two-Micron All Sky Survey (2MASS), and use the FAST spectrograph of the Tillinghast reflector on Mt. Hopkins to obtain the spectra of 57 objects. We make available a digital S star spectral atlas consisting of 14 spectra of S stars with diverse spectral features. We define and derive basic spectral indices that can help distinguish S stars from late-type (M) giants and carbon stars. We convolve all our spectra with the Sloan Digital Sky Survey bandpasses, and employ the resulting gri magnitudes together with 2MASS JHK{sub s} mags to investigate S star colors. These objects have colors similar to carbon and M stars, and are therefore difficult to distinguish by color alone. Using near- and mid-infrared colors from IRAS and Akari, we identify some of the stars as intrinsic (AGB) or extrinsic (with abundances enhanced by past mass transfer). We also use V band and 2MASS magnitudes to calculate a temperature index for stars in the sample. We analyze the proper motions and parallaxes of our sample stars to determine upper and lower limit absolute magnitudes and distances, and confirm that most are probably giants.

79 ASTRONOMY AND ASTROPHYSICS↗

TU-FG-209-07: Medical Physics 1.0 Versus Medical Physics 2.0: A Case Study

Purpose: To illustrate how performance analytics can identify performance decrement in digital radiography systems. Methods: Subsequent to a radiologist’s image quality complaint, four different advanced methods contributed to root cause analysis. Our system was a GE Revolution XQi digital radiography unit. Initially, we reviewed weekly GE Quality Assurance Procedures (QAP) results in a database dating from 2001. Next, we evaluated objective image quality metrics of individual PA Chest radiographs acquired. These images were anonymized, securely transferred, and analyzed by the Duke University Clinical Imaging Physics Group with software previously described{sup 1} and validated{sup 2}. Third, we compared the exposure-dependent SNR{sup 2} (NEQ) of the unit with previously established confidence limits{sup 3}. Finally, we explored our service database to reveal events that might affect detector performance. Results: QAP reported a decrease in CNR reflected in a significant increase in lung noise(Ln), mediastinum noise(Mn), and subdiaphragm-lung contrast(Slc) with a significant decrease in lung grey level(Lgl) after detector replacement. Most change occurred during week 1, before the QAP indicated one-half the ultimate decrease in CNR. After detector recalibration, QAP CNR improved, but was not restored to previous levels. Lgl and Slc were no longer significantly different from before, however Ln and Mn remained significantly different. Exposure-dependent SNR2 show the detector to be operating within limits in October 2006 but subsequently became miscalibrated sometime before acquisition of the 2011–2014 data. Service records revealed catastrophic failure of the Image Detection Controller that contained the 2007 calibration. Traditional metrics did not indicate that the system was performing outside of normal limits. Conclusion: Performance analytics are powerful tools whose proper application could allow early intervention in degraded system performance. The image-quality metrics appear to be highly sensitive to system performance and are reported with every acquisition rather than at arbitrary intervals. Confidence intervals may require customization for individual systems or detectors.

60 APPLIED LIFE SCIENCES↗

SU-E-J-136: Multimodality-Image-Based Target Delineation for Dose Painting of Pancreatic Cancer

Purpose: Dose escalated RT may provide improved disease local-control for selected unresectable pancreatic cancer. Accurate delineation of the gross tumor volume (GTV) inside pancreatic head or body would allow safe dose escalation considering the tolerances of adjacent organs at risk (OAR). Here we explore the potential of multi-modality imaging (DCE-MRI, ADC-MRI, and FDG-PET) to define the GTV for dose painting of pancreatic cancer. Volumetric variations of DCE-MRI, ADC-MRI and FDG-PET defined GTVs were assessed in comparison to the findings on CT, and to pathology specimens for resectable and borderline reseactable cases of pancreatic cancer. Methods: A total of 19 representative patients with DCE-MRI, ADC-MRI and FDG-PET data were analyzed. Of these, 8 patients had pathological specimens. GTV, inside pancreatic head/neck, or body, were delineated on MRI (denoted GTVDCE, and GTVADC), on FDG-PET using SUV of 2.5, 40% SUVmax, and 50% SUVmax (denoted GTV2.5, GTV40%, and GTV50%). A Kruskal-Wallis test was used to determine whether significant differences existed between GTV volumes. Results: Significant statistical differences were found between the GTVs defined by DCE-MRI, ADC-MRI, and FDG-PET, with a mean and range of 4.73 (1.00–9.79), 14.52 (3.21–25.49), 22.04 (1.00–45.69), 19.10 (4.84–45.59), and 9.80 (0.32–35.21) cm3 (p<0.0001) for GTVDCE, GTVADC, GTV2.5, GTV40%, and GTV50%, respectively. The mean difference and range in the measurements of maximum dimension of GTVs based on DCE-MRI, ADC-MRI, SUV2.5, 40% SUVmax, and 50% SUVmax compared with pathologic specimens were −0.84 (−2.24 to 0.9), 0.41 (−0.15 to 2.3), 0.58 (−1.41 to 3.69), 0.66 (−0.67 to 1.32), and 0.15 (−1.53 to 2.38) cm, respectively. Conclusion: Differences exists between DCE, ADC, and PET defined target volumes for RT of pancreatic cancer. Further studies combined with pathological specimens are required to identify the optimal imaging modality and/or acquisition method to define the GTV.

60 APPLIED LIFE SCIENCES↗

Taxonomy for Common-Cause Failure Vulnerability and Mitigation

Applying current guidance and practices for common-cause failure (CCF) mitigation to digital instrumentation and control (I&C) systems has proven problematic, and the regulatory environment has been unpredictable. The potential for CCF vulnerability inhibits I&C modernization, thereby challenging the long-term sustainability of existing plants. For new plants and advanced reactor concepts, concern about CCF vulnerability in highly integrated digital I&C systems imposes a design burden that results in higher costs and increased complexity. The regulatory uncertainty in determining which mitigation strategies will be acceptable (e.g., what diversity is needed and how much is sufficient) drives designers to adopt complicated, costly solutions devised for existing plants. To address the conditions that constrain the transition to digital I&C technology by the US nuclear industry, crosscutting research is needed to resolve uncertainty, demonstrate necessary characteristics, and establish an objective basis for qualification of digital technology for nuclear power plant (NPP) I&C applications. To fulfill this research need, Oak Ridge National Laboratory is investigating mitigation of CCF vulnerability for nuclear-qualified applications. The outcome of this research is expected to contribute to a fundamentally sound, comprehensive basis to qualify digital technology for nuclear power applications. This report documents the development of a CCF taxonomy. The basis for the CCF taxonomy was generated by determining consistent terminology and establishing a classification approach. The terminology is based on definitions from standards, guides, and relevant nuclear power industry technical reports. The classification approach is derived from identified classification schemes focused on I&C systems and key characteristics, including failure modes. The CCF taxonomy provides the basis for a systematic organization of key systems aspects relevant to analyzing the potential for CCF vulnerability and the suitability of mitigation techniques. Development of an effective CCF taxonomy will help to provide a framework for establishing the objective analysis and assessment capabilities desired to facilitate rigorous identification of fault types and triggers that are the fundamental elements of CCF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Three moving groups detected in the LAMOST DR1 archive

We analyze the kinematics of thick disk and halo stars observed by the Large Sky Area Multi-Object Fiber Spectroscopic Telescope. We have constructed a sample of 7993 F, G, and K nearby main-sequence stars (d < 2 kpc) with estimates of position (x, y, z) and space velocity (U, V, W) based on color and proper motion from the Sloan Digital Sky Survey DR9 catalog. Three 'phase-space overdensities' are identified in (V, √(U{sup 2}+2V{sup 2})) with significance levels of σ > 3. Two of them (the Hyades-Pleiades stream and the Arcturus-AF06 stream) have been identified previously. We also find evidence for a new stream (centered at V ∼ –180 km s{sup –1}) in the halo. The formation mechanisms of these three streams are analyzed. Our results support the hypothesis that the Arcturus-AF06 stream and the new stream originated from the debris of a disrupted satellite, while the Hyades-Pleiades stream has a dynamical origin.

79 ASTRONOMY AND ASTROPHYSICS↗

Morpho-Hawk

Morpho-Hawk applies projectional mathematical morphology in a fundamentally new way. Morpho-Hawk extracts object information from digital images by filtering with simple geometrical figures such as rectangles or simple curves. Two core algorithms are used to accomplish this: 1) Object Detection and Feature Extraction from Images: Using projectional morphology, Morpho-Hawk finds features of interest within an image, such as contours, shapes, colors, infrared spectra, and more. Because Morpho-Hawk identifies features based on shape or form, the method can uniquely handle different image or object conditions and directions. MorphoHawk can evaluate all possible images of the analyzed scene using the same transformations that are applied just to one image of that scene. Hence, recognizing a defect within an image or part of an image provides information to assist in recognizing other objects in the image. In addition, known background image information can be morphologically subtracted out in order to focus on the appearance or disappearance of the features of interest. 2) Object Analysis: Upon detection of an object of interest, Morpho-Hawk can analyze the object based learned information from prior images or end-user defined criteria for certain object of special interest by selecting feature (e.g., color, size, shape, apparent volume) and/or symbol (e.g., letter, number). The novel algorithm can analyze targeted objects, even as conditions of such as illumination, shadows, and spectral regions change strongly in following images as compared to the original image. This enables robust recognition, interpolation and prediction. As the analysis shows the presence of these features in the optical signal, the algorithm can make a determination based on user defined probability. The object information can be stored for later analysis using simple morphological data compression methods and/or retention of the original optical images.

Glazoff, MichaelV.↗

Design and Implementation of Smart Buildings: A Review of Current Research Trend

The building sector is one of the largest contributors to the world’s total energy use and greenhouse gas emissions. Advancements in building energy technologies have played a critical role in enhancing the energy sustainability of the built environment. Extensive research and new techniques in energy and environmental systems for buildings have recently emerged to address the global challenges. This study reviews existing articles in the literature, mostly since 2000, to explore technological advancement in building energy and environmental systems that can be applied to smart homes and buildings. This review study focuses on an overview of the design and implementation of energy-related smart building technologies, including energy management systems, renewable energy applications, and current advanced smart technologies for optimal function and energy-efficient performance. To review the advancement in building energy-related technologies, a systematic review process is adopted based on available published reviews and research types of articles. Review-type articles are first assessed to explore the current literature on the relevant keywords and to capture major research scopes. Research-type papers are then examined to investigate associated keywords and work scopes, including objectives, focuses, limitations, and future needs. Throughout the comprehensive literature review, this study identifies various techniques of smart home/building applications that have provided detailed solutions or guidelines in different applications to enhance the quality of people’s daily activities and the sustainability of the built environmental system. This paper shows trends in human activities and technology advancements in digital solutions with energy management systems and practical designs. Understanding the overall energy flow between a building and its environmentally connected systems is also important for future buildings and community levels. This paper assists in understanding the pathway toward future smart homes/buildings and their technologies for researchers in related research fields.

renewable system integration↗

The High-redshift Clusters Occupied by Bent Radio AGN (COBRA) Survey: The Spitzer Catalog

We present 190 galaxy cluster candidates (most at high redshift) based on galaxy overdensity measurements in the Spitzer/IRAC imaging of the fields surrounding 646 bent, double-lobed radio sources drawn from the Clusters Occupied by Bent Radio AGN (COBRA) Survey. The COBRA sources were chosen as objects in the Very Large Array FIRST survey that lack optical counterparts in the Sloan Digital Sky Survey to a limit of m {sub r} = 22, making them likely to lie at high redshift. This is confirmed by our observations: the redshift distribution of COBRA sources with estimated redshifts peaks near z = 1 and extends out to z≈3. Cluster candidates were identified by comparing our target fields to a background field and searching for statistically significant (⩾2σ) excesses in the galaxy number counts surrounding the radio sources; 190 fields satisfy the ⩾2σ limit. We find that 530 fields (82.0%) have a net positive excess of galaxies surrounding the radio source. Many of the fields with positive excesses but below the 2σ cutoff are likely to be galaxy groups. Forty-one COBRA sources are quasars with known spectroscopic redshifts, which may be tracers of some of the most distant clusters known.

79 ASTRONOMY AND ASTROPHYSICS↗

Automated identification of 2612 LATE-K and M dwarfs in the lamost commissioning data using classification template fits

We develop a template-fit method to automatically identify and classify late-type K and M dwarfs in spectra from the Large Sky Area Multi-object Fiber Spectroscopic Telescope (LAMOST). A search of the commissioning data, acquired in 2009–2010, yields the identification of 2612 late-K and M dwarfs. The template fit method also provides spectral classification to half a subtype, classifies the stars along the dwarf–subdwarf (dM/sdM/esdM/usdM) metallicity sequence, and provides improved metallicity/gravity information on a finer scale. The automated search and classification is performed using a set of cool star templates assembled from the Sloan Digital Sky Survey spectroscopic database. We show that the stars can be efficiently classified despite shortcomings in the LAMOST commissioning data which include bright sky lines in the red. In particular we find that the absolute and relative strengths of the critical TiO and CaH molecular bands around 7000 Å are cleanly measured, which provides accurate spectral typing from late-K to mid-M, and makes it possible to estimate metallicity classes in a way that is more efficient and reliable than with the use of spectral indices or spectral-index based parameters such as ζ{sub TiO/CaH}. Most of the cool dwarfs observed by LAMOST are found to be metal-rich dwarfs (dM). However, we identify 52 metal-poor M subdwarfs (sdM), 5 very metal-poor extreme subdwarfs (esdM) and 1 probable ultra metal-poor subdwarf (usdM). We use a calibration of spectral type to absolute magnitude and estimate spectroscopic distances for all the stars; we also recover proper motions from the SUPERBLINK and PPMXL catalogs. Our analysis of the estimated transverse motions suggests a mean velocity and standard deviation for the UVW components of velocity to be: 〈U〉=−9.8 km s{sup −1}, σ{sub U} = 35.6 km s{sup −1}; 〈V〉=−22.8 km s{sup −1}, σ{sub V}=30.6 km s{sup −1}; 〈W〉=−7.9 km s{sup −1}, σ{sub W} = 28.4 km s{sup −1}. The resulting values are in general agreement with previous reported results, which yields confidence in our spectral classification and spectroscopic distance estimates, and illustrates the potential for using LAMOST spectra of K and M dwarfs for investigating the chemo-kinematics of the local Galactic disk and halo.

79 ASTRONOMY AND ASTROPHYSICS↗

Searching for binary supermassive black holes via variable broad emission line shifts: low binary fraction

Supermassive black hole binaries (SMBHs) are expected to result from galaxy mergers, and thus are natural byproducts (and probes) of hierarchical structure formation in the universe. They are also the primary expected source of low-frequency gravitational wave emission. We search for binary BHs using time-variable velocity shifts in broad Mg ii emission lines of quasars with multi-epoch observations. First, we inspect velocity shifts of the binary SMBH candidates identified in Ju et al., using Sloan Digital Sky Survey spectra with an additional epoch of data that lengthens the typical baseline to ∼10 yr. We find variations in the line of sight velocity shifts over 10 yr that are comparable to the shifts observed over 1–2 yr, ruling out the binary model for the bulk of our candidates. We then analyze 1438 objects with eight-year median time baselines, from which we would expect to see velocity shifts >1000 km s{sup −1} from sub-parsec binaries. We find only one object with an outlying velocity of 448 km s{sup −1}, indicating—based on our modeling—that ≲1% (the value varies with different assumptions) of SMBHs that are active as quasars reside in binaries with ∼0.1 pc separations. Binaries either sweep rapidly through these small separations or stall at larger radii.

79 ASTRONOMY AND ASTROPHYSICS↗

CHARACTERIZING THE MID-INFRARED EXTRAGALACTIC SKY WITH WISE AND SDSS

The Wide-field Infrared Survey Explorer (WISE) has completed its all-sky survey in four channels at 3.4-22 {mu}m, detecting hundreds of millions of objects. We merge the WISE mid-infrared data with optical data from the Sloan Digital Sky Survey (SDSS) and provide a phenomenological characterization of WISE extragalactic sources. WISE is most sensitive at 3.4 {mu}m (W1) and least sensitive at 22 {mu}m (W4). The W1 band probes massive early-type galaxies out to z {approx}> 1. This is more distant than SDSS identified early-type galaxies, consistent with the fact that 28% of 3.4 {mu}m sources have faint or no r-band counterparts (r > 22.2). In contrast, 92%-95% of 12 {mu}m and 22 {mu}m sources have SDSS optical counterparts with r {<=} 22.2. WISE 3.4 {mu}m detects 89.8% of the entire SDSS QSO catalog at S/N{sub W1} >7{sigma}, but only 18.9% at 22 {mu}m with S/N{sub W4} > 5{sigma}. We show that WISE colors alone are effective in isolating stars (or local early-type galaxies), star-forming galaxies, and strong active galactic nuclei (AGNs)/QSOs at z {approx}< 3. We highlight three major applications of WISE colors: (1) Selection of strong AGNs/QSOs at z {<=} 3 using W1 - W2 > 0.8 and W2 < 15.2 criteria, producing a better census of this population. The surface density of these strong AGN/QSO candidates is 67.5 {+-} 0.14 deg{sup -2}. (2) Selection of dust-obscured, type-2 AGN/QSO candidates. We show that WISE W1 - W2 > 0.8, W2 < 15.2 combined with r - W2 > 6 (Vega) colors can be used to identify type-2 AGN candidates. The fraction of these type-2 AGN candidates is one-third of all WISE color-selected AGNs. (3) Selection of ultraluminous infrared galaxies (ULIRGs) at z {approx} 2 with extremely red colors, r - W4 > 14 or well-detected 22 {mu}m sources lacking detections in the 3.4 and 4.6 {mu}m bands. The surface density of z {approx} 2 ULIRG candidates selected with r - W4 > 14 is 0.9 {+-} 0.07 deg{sup -2} at S/N{sub W4} {>=} 5 (the corresponding, lowest flux density of 2.5 mJy), which is consistent with that inferred from smaller area Spitzer surveys. Optical spectroscopy of a small number of these high-redshift ULIRG candidates confirms our selection, and reveals a possible trend that optically fainter or r - W4 redder candidates are at higher redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗