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Crystal Plasticity Modeling and Experimental Validation with an Orientation Distribution Function for Ti-7Al Alloy

An orientation distribution function based model is used for micromechanical modeling of the titanium-aluminum alloys, Ti-0 wt % Al and Ti-7 wt % Al, which are in demand for many aerospace applications. This probability descriptor based modeling approach is different than crystal plasticity finite element techniques since it computes the averaged material properties using upper bound averaging. A rate-independent single-crystal plasticity model is implemented to compute the effect of macroscopic strain on the polycrystal. An optimization problem is defined for calibrating the basal, prismatic, pyramidal slip system and twin parameters using the available tension and compression experimental data. The crystal plasticity parameters of Ti-7 wt % Al are not studied extensively in literature, and therefore the optimization results for the crystal plasticity model realization produce unique data, which will be beneficial to future studies in the field. The sensitivities of the slip and twin parameters to the design objectives are also investigated to identify the most critical slip system parameters. Using the optimum design parameters, the microstructural textures, during the tension test, are predicted by the crystal plasticity finite element simulations, and compared to the available experimental texture and scanning electron microscope—digital image correlation data.

36 MATERIALS SCIENCE↗

The Sloan Digital Sky Survey Quasar Catalog: Twelfth data release

In this paper, we present the Data Release 12 Quasar catalog (DR12Q) from the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey III. This catalog includes all SDSS-III/BOSS objects that were spectroscopically targeted as quasar candidates during the full survey and that are confirmed as quasars via visual inspection of the spectra, have luminosities M i [z = 2] < -20.5 (in a ΛCDM cosmology with H 0 = 70 km s -1 Mpc -1 , Ω M = 0.3, and Ω Λ = 0.7), and either display at least one emission line with a full width at half maximum (FWHM) larger than 500 km s -1 or, if not, have interesting/complex absorption features. The catalog also includes previously known quasars (mostly from SDSS-I and II) that were reobserved by BOSS. The catalog contains 297 301 quasars (272 026 are new discoveries since the beginning of SDSS-III) detected over 9376 deg 2 with robust identification and redshift measured by a combination of principal component eigenspectra. The number of quasars with z > 2.15 (184 101, of which 167 742 are new discoveries) is about an order of magnitude greater than the number of z > 2.15 quasars known prior to BOSS. Redshifts and FWHMs are provided for the strongest emission lines (C iv, C iii], Mg ii). The catalog identifies 29 580 broad absorption line quasars and lists their characteristics. For each object, the catalog presents five-band (u, g, r, i, z) CCD-based photometry with typical accuracy of 0.03 mag together with some information on the optical morphology and the selection criteria. When available, the catalog also provides information on the optical variability of quasars using SDSS and Palomar Transient Factory multi-epoch photometry. The catalog also contains X-ray, ultraviolet, near-infrared, and radio emission properties of the quasars, when available, from other large-area surveys. The calibrated digital spectra, covering the wavelength region 3600–10 500 Å at a spectral resolution in the range 1300 < R < 2500, can be retrieved from the SDSS Catalog Archive Server. Finally, we also provide a supplemental list of an additional 4841 quasars that have been identified serendipitously outside of the superset defined to derive the main quasar catalog.

79 ASTRONOMY AND ASTROPHYSICS↗

Digital Information Platform (DIP) Overview

On March 24, 2021, NASA’s Digital Information Platform (DIP) released a Request for Information (RFI) to the aviation community. The RFI was intended to request two things: 1) DIP concept input such as current challenges and needs for data and services and 2) Interest in participating in collaborative demonstrations. On July 29, 2021, DIP team will meet with Airlines for America (A4A) to share a summary of information received from the RFI responses. The objective of the meeting is to follow up with respondents with takeaways the DIP team identified that will inform the concept and demonstration plans. The forum will give participants an opportunity to add on and provide feedback to the summary. The meeting will also describe the roadmap for the Collaborative Demonstrations and next steps for partner engagement.

Digital Information Platform (DIP) RFI summary↗

ADAPTIVE OPTICS IMAGING OF QUASI-STELLAR OBJECTS WITH DOUBLE-PEAKED NARROW LINES: ARE THEY DUAL ACTIVE GALACTIC NUCLEI?

Active galaxies hosting two accreting and merging supermassive black holes (SMBHs)-dual active galactic nuclei (AGNs)-are predicted by many current and popular models of black-hole-galaxy co-evolution. We present here the results of a program that has identified a set of probable dual AGN candidates based on near-infrared laser guide star adaptive optics imaging with the Keck II telescope. These candidates are selected from a complete sample of radio-quiet quasi-stellar objects (QSOs) drawn from the Sloan Digital Sky Survey (SDSS), which show double-peaked narrow AGN emission lines. Of the 12 AGNs imaged, we find 6 with double galaxy structure, of which four are in galaxy mergers. We measure the ionization of the two velocity components in the narrow AGN lines to test the hypothesis that both velocity components come from an active nucleus. The combination of a well-defined parent sample and high-quality imaging allows us to place constraints on the fraction of SDSS QSOs that host dual accreting black holes separated on kiloparsec scales: {approx}0.3%-0.65%. We derive from this fraction the time spent in a QSO phase during a typical merger and find a value that is much lower than estimates that arise from QSO space densities and galaxy merger statistics. We discuss possible reasons for this difference. Finally, we compare the SMBH mass distributions of single and dual AGNs and find little difference between the two within the limited statistics of our program, hinting that most SMBH growth happens in the later stages of a merger process.

79 ASTRONOMY AND ASTROPHYSICS↗

OPTOM: Optimization of Parabolic Trough - Operations & Maintenance

The US Department of Energy’s SunShot goals look to reduce the cost of Concentrating Solar Power (CSP) technology to 5¢/kWh for baseload plants. This is about a 50% reduction from current costs. To achieve this cost target, a significant reduction in operation and maintenance (O&M) costs of 40 to 50% is likely needed. Advances are needed in the O&M practices of CSP plants if the technology is to achieve the SunShot cost goals. Digitization of plant performance and O&M data has become a new best practice in the world of renewable energy asset management. Owners and operators of large photovoltaic and wind power plants are working to digitize performance and O&M data at their existing assets, to improve their management of the facilities, to increase performance, reduce O&M costs, and lower the overall life cycle cost of ownership. CSP power plants are behind the curve of other technologies on the digitization of plant information to aid in the plant asset management. This project directly addresses the objective of digitizing the O&M data of the solar field, focusing on three areas: 1) creating a framework for sharing data and information, 2) creating a system for monitoring and managing the maintenance of the solar field collectors, and 3) developing analytic tools to identify issues in the solar field. According to the NREL CSP Best Practices Study, the current practice at many CSP plants is to rely on paper lists, spreadsheets, and email for monitoring and managing problems and maintenance in the solar field. The key element to digitize solar field O&M is the creation of a centralized data archive that all users and systems can interface with. This project developed a centralized relational database framework that allows users and applications to access and share data. Conventional power plants utilize Computerized Maintenance Management Systems (CMMSs) to track the corrective, preventive (scheduled), and predictive maintenance of equipment and subsystems in the power plant. CSP plants use these systems in the power block, but while these systems specialize at tracking maintenance on up to thousands of pieces of equipment, they are not well suited for tracking the tens or hundreds of thousands of components in large commercial CSP or photovoltaic solar fields. In this project we developed a new software application referred to as FieldStatus (TM). This is a specialized database program that is used to track the status of each collector and its components. This application is designed to complement the existing CMMS to enable improved tracking and management of maintenance activities in the solar field. One of the major maintenance tasks for solar fields is maintaining the cleanliness of the mirrors. Although seemingly a relatively straight forward task, it has often proven challenging to maintain high levels of cleanliness in an efficient and cost-effective manner. This project developed new tools and metrics for monitoring and optimizing solar field cleaning resources and overall solar field cleanliness.

14 SOLAR ENERGY↗

Development of Gamma Background Radiation Digital Twin with Machine Learning Algorithms: Application of Unsupervised Machine Learning to Detection of Anomalies and Nuisances in Gamma Background Radiation Environmental Screening Data

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for development of a digital twin of gamma radiation background, and for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. In one segment of work, we developed a gamma background estimation model using a Longshort term memory (LSTM) network for one-step CPS time series prediction. The LSTM model was validated with two data sets of measurements from two independent NaI detectors positioned on a mobile platform. The data sets contained background radiation only and no orphan isotope sources. The LSTM model was constructed and tested using data from one of the detectors. Performance of the LSTM model was validate through one-step prediction of CPS time series of another NaI detector without re-training. This approach allows to create a digital twin for nuclear background estimation. Using LSTM, it could be possible to detect a source through subtraction of the estimated counts from the measured background. In another segment of work, we investigated detection of gamma emitting sources in the presence of complex background using unsupervised machine learning. Spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

54 ENVIRONMENTAL SCIENCES↗

The Digital Astronaut Project Bone Remodeling Model

One of the main objectives is to provide a tool to help HHC address Bone Gap Osteo 4: We don't know the contribution of each risk factor on bone loss and recovery of bone strength and which factors are the best targets for countermeasure application; and Osteo7: We need to identify options for mitigation of early onset osteoporosis before, during, and after spaceflight.

Pennline, J. A.↗

White dwarf and subdwarf stars in the Sloan Digital Sky Survey Data Release 16

ABSTRACT White dwarfs are the end state of the evolution of more than 97 per cent of all stars, and therefore carry information on the structure and evolution of the Galaxy through their luminosity function and initial-to-final mass relation. Examining the new spectra of all white or blue stars in the Sloan Digital Sky Survey Data Release 16, we report the spectral classification of 2410 stars, down to our identification cut-off of signal-to-noise ratio equal to three. We newly identify 1404 DAs, 189 DZs, 103 DCs, 12 DBs, and nine CVs. The remaining objects are a mix of carbon or L stars (dC/L), narrow-lined hydrogen-dominated stars (sdA), dwarf F stars, and P Cyg objects. As white dwarf stars were not targeted by SDSS DR16, the number of new discoveries is much smaller than in previous releases. We also report atmospheric parameters and masses for a subset consisting of 555 new DAs, 10 new DBs, and 85 DZs for spectra with signal-to-noise ratio larger than 10.

Kepler, S. O. (ORCID:0000000274705703)↗

Brochure for the DOE Office of Science Workshop on Envisioning Frontiers in AI and Computing for Biological Research

In February of 2025 a joint ASCR/BER workshop was held to identify key transformational research directions for understanding biology using artificial intelligence (AI), digital twins and high-performance (HPC) computational methods to facilitate scientific discovery and innovation in support of the Department of Energy mission. AI technologies offer exciting new groundbreaking methods to analyze large volumes of complex biological data, thereby greatly accelerating the ability to understand, predict, and design biological processes for beneficial purposes. In the laboratory, the bridging of AI-enabled automated experimental technologies, HPC and digital twins will provide potent tools for researchers to explore the fundamental nature of biology and harness its inherent metabolic potential for a variety of beneficial purposes. The focus of this workshop was on how high-performance computational methods can impact this objective by exploring digital twins, foundational models, and data-driven approaches with applications to advance automated laboratory experiments, modeling of complex living systems and engineering new functions into plants and microbial systems relevant to DOE mission. Workshop attendees with expertise in plant science, microbiology, mathematics, computer science, and AI assessed the current state of the science, trends, and AI challenges at the interface of plant and microbial systems biology and computational science to identify opportunities for high-impact research. This collaborative effort capitalized on ASCR's advancements in applied mathematics, computer science, and Exascale systems, and BER's expertise in basic genomics-enabled research on DOE relevant plant and microbial systems. The workshop culminated in four key priority research directions to guide future research and development within DOE Office of Science programs.

59 BASIC BIOLOGICAL SCIENCES↗

PREPARING FOR ADVANCED LIGO: A STAR–GALAXY SEPARATION CATALOG FOR THE PALOMAR TRANSIENT FACTORY

The search for fast optical transients, such as the expected electromagnetic counterparts to binary neutron star mergers, is riddled with false positives (FPs) ranging from asteroids to stellar flares. While moving objects are readily rejected via image pairs separated by ∼1 hr, stellar flares represent a challenging foreground, significantly outnumbering rapidly evolving explosions. Identifying stellar sources close to and fainter than the transient detection limit can eliminate these FPs. Here, we present a method to reliably identify stars in deep co-adds of Palomar Transient Factory (PTF) imaging. Our machine-learning methodology utilizes the random forest (RF) algorithm, which is trained using >3×10{sup 6} sources with Sloan Digital Sky Survey (SDSS) spectra. When evaluated on an independent test set, the PTF RF model outperforms the SExtractor star classifier by ∼4%. For faint sources (r{sup ′}⩾21 mag), which dominate the field population, the PTF RF model produces a ∼19% improvement over SExtractor. To avoid false negatives in the PTF transient-candidate stream, we adopt a conservative stellar classification threshold, corresponding to a galaxy misclassification rate of 0.005. Ultimately, ∼1.70×10{sup 8} objects are included in our PTF point-source catalog, of which only ∼10{sup 6} are expected to be galaxies. We demonstrate that the PTF RF catalog reveals transients that otherwise would have been missed. To leverage its superior image quality, we additionally create an SDSS point-source catalog, which is also tuned to have a galaxy misclassification rate of 0.005. These catalogs have been incorporated into the PTF real-time pipelines to automatically reject stellar sources as non-extragalactic transients.

79 ASTRONOMY AND ASTROPHYSICS↗

SHOCKED POSTSTARBUST GALAXY SURVEY. I. CANDIDATE POST-STARBUST GALAXIES WITH EMISSION LINE RATIOS CONSISTENT WITH SHOCKS

There are many mechanisms by which galaxies can transform from blue, star-forming spirals, to red, quiescent early-type galaxies, but our current census of them does not form a complete picture. Recent observations of nearby case studies have identified a population of galaxies that quench “quietly.” Traditional poststarburst searches seem to catch galaxies only after they have quenched and transformed, and thus miss any objects with additional ionization mechanisms exciting the remaining gas. The Shocked POststarburst Galaxy Survey (SPOGS) aims to identify transforming galaxies, in which the nebular lines are excited via shocks instead of through star formation processes. Utilizing the Oh-Sarzi-Schawinski-Yi (OSSY) measurements on the Sloan Digital Sky Survey Data Release 7 catalog, we applied Balmer absorption and shock boundary criteria to identify 1067 SPOG candidates (SPOGs*) within z = 0.2. SPOGs* represent 0.2% of the OSSY sample galaxies that exceed the continuum signal-to-noise cut (and 0.7% of the emission line galaxy sample). SPOGs* colors suggest that they are in an earlier phase of transition than OSSY galaxies that meet an “E+A” selection. SPOGs* have a 13% 1.4 GHz detection rate from the Faint Images of the Radio Sky at Twenty Centimeters Survey, higher than most other subsamples, and comparable only to low-ionization nuclear emission line region hosts, suggestive of the presence of active galactic nuclei (AGNs). SPOGs* also have stronger Na i D absorption than predicted from the stellar population, suggestive of cool gas being driven out in galactic winds. It appears that SPOGs* represent an earlier phase in galaxy transformation than traditionally selected poststarburst galaxies, and that a large proportion of SPOGs* also have properties consistent with disruption of their interstellar media, a key component to galaxy transformation. It is likely that many of the known pathways to transformation undergo a SPOG phase. Studying this sample of SPOGs* further, including their morphologies, AGN properties, and environments, has the potential for us to build a more complete picture of the initial conditions that can lead to a galaxy evolving.

79 ASTRONOMY AND ASTROPHYSICS↗

Constructing a working taxonomy of functional Ada software components for real-time embedded system applications

A major impediment to a systematic attack on Ada software reusability is the lack of an effective taxonomy for software component functions. The scope of all possible applications of Ada software is considered too great to allow the practical development of a working taxonomy. Instead, for the purposes herein, the scope of Ada software application is limited to device and subsystem control in real-time embedded systems. A functional approach is taken in constructing the taxonomy tree for identified Ada domain. The use of modular software functions as a starting point fits well with the object oriented programming philosophy of Ada. Examples of the types of functions represented within the working taxonomy are real time kernels, interrupt service routines, synchronization and message passing, data conversion, digital filtering and signal conditioning, and device control. The constructed taxonomy is proposed as a framework from which a need analysis can be performed to reveal voids in current Ada real-time embedded programming efforts for Space Station.

Wallace, Robert↗

Feasibility of automated dropsize distributions from holographic data using digital image processing techniques

An automated technique for measuring particle diameters and their spatial coordinates from holographic reconstructions is being developed. Preliminary tests on actual cold-flow holograms of impinging jets indicate that a suitable discriminant algorithm consists of a Fourier-Gaussian noise filter and a contour thresholding technique. This process identifies circular as well as noncircular objects. The desired objects (in this case, circular or possibly ellipsoidal) are then selected automatically from the above set and stored with their parametric representations. From this data, dropsize distributions as a function of spatial coordinates can be generated and combustion effects due to hardware and/or physical variables studied.

Feinstein, S. P.↗

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↗

Application of SIR-B data for groundwater exploration in the Arabian shield and sand-drift monitoring in the AN Nafud and Al Jafurah fringe areas, Kingdom of Saudi Arabia

The primary objectives of the investigation are to determine fully the utility of Shuttle Imaging Radar-B (SIR-B) images for providing valuable surface indicators for ground-water prospecting in the Arabian shield and to identify and assess defining characteristics of sand sheets, sand streaks, and sand dunes in the fringe areas of An Nafud and Al Jafurah. Specific objectives include the determination of the incremental contribution of incidence angle to the total information that can be extracted from SIR-B standard and digitally-enhanced images in the AL Jafurah fringe area; the determination of the incremental contribution of digitally-registered multisensor images; and the development of a groundwater exploration plan for the Ha'il test area in the Arabian Shield.

Berlin, G. L.↗

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↗