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The award described here was used to support operations for the extended Baryon Oscillation Spectroscopic Survey (eBOSS). Operating from July 2014 through March 2019, eBOSS was the cosmological component of the fourth generation of the Sloan Digital Sky Survey (SDSS).
The search for special and rare celestial objects has always played an important role in astronomy. Cataclysmic Variables (CVs) are special and rare binary systems with accretion disks. Most CVs are in the quiescent period, and their spectra have the emission lines of Balmer series, HeI, and HeII. A few CVs in the outburst period have the absorption lines of Balmer series. Owing to the scarcity of numbers, expanding the spectral data of CVs is of positive significance for studying the formation of accretion disks and the evolution of binary star system models. At present, the research for astronomical spectra has entered the era of Big Data. The Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST) has produced more than tens of millions of spectral data. the latest released LAMOST-DR7 includes 10.6 million low-resolution spectral data in 4926 sky regions, providing ideal data support for searching CV candidates. To process and analyze the massive amounts of spectral data, this study employed the Light Gradient Boosting Machine (LightGBM) algorithm, which is based on the ensemble tree model to automatically conduct the search in LAMOST-DR7. Finally, 225 CV candidates were found and four new CV candidates were verified by SIMBAD and published catalogs. This study also built the Gradient Boosting Decision Tree (GBDT), Adaptive Boosting (AdaBoost), and eXtreme Gradient Boosting (XGBoost) models and used Accuracy, Precision, Recall, the F1-score, and the ROC curve to compare the four models comprehensively. Experimental results showed that LightGBM is more efficient. The search for CVs based on LightGBM not only enriches the existing CV spectral library, but also provides a reference for the data mining of other rare celestial objects in massive spectral data.
Correlated measurements of red-shifted iron line emission and apparent surface brightness are suggested for unambiguously defining intrinsic X-ray characteristics for clusters of galaxies up to z greater than or equal to 1. If some of the weak unidentified high galactic latitude X-ray sources are clusters at z approximately 1-3, then such correlated measurements should be feasible witin the complement of instruments aboard the HEAO-B orbiting X-ray telescope observatory. In addition, those clusters at z less than 1 would require spectral data from broader bandwidth experiments, such as the all-sky survey to be provided by the proportional counters aboard the first mission of the High Energy Astronomy Observatory (HEAO-A).
Correlated measurements of redshifted iron line emission and apparent surface brightness are suggested for unambiguously defining intrinsic X-ray characteristics for clusters of galaxies up to z not less than 1. If some of the weak unidentified high-galactic-latitude X-ray sources are clusters at z roughly equal to 1-3, then such correlated measurements should be feasible within the complement of instruments aboard the HEAO-B orbiting X-ray telescope observatory. In addition, those clusters at z less than 1 would require spectral data from broader bandwidth experiments, such as the all-sky survey to be provided by the proportional counters aboard the first mission of the High Energy Astronomy Observatory (HEAO-A).
A linear correlation was found between the infrared cirrus at 100 or 60 microns and neutral atomic hydrogen near the galactic plane. Infrared Astronomy Satellite (IRAS) Sky Brightness images were compared to the 0.5 deg resolution Weaver-Williams HI survey in two regions of the outer Galaxy near l = 125 deg and l = 215 deg. The dust temperature inferred is nearly uniform and in reasonable agreement with theoretical predictions of thermal dust emission.
Gamma Ray Observatories, Gamma-Ray Astrophysics, GeV TeV Sky Survey, Galaxy, Galactic Plane, Source Distribution, The gamma-ray sky is currently well-monitored with good survey coverage. Many instruments from different waveband/messenger (X rays, gamma rays, neutrinos, gravitational waves) available for simultaneous observations. Both wide-field and pointing instruments in development and coming online in the next decade LIGO
This report covers the initial activities and deliberations of a continuing working group asked to assist the SETI Program Office at NASA. Seven chapters present the group's consensus on objectives, strategies, and plans for instrumental R&D and for a microwave search for extraterrestrial in intelligence (SETI) projected for the end of this decade. Thirteen appendixes reflect the views of their individual authors. Included are discussions of the 8-million-channel spectrum analyzer architecture and the proof-of-concept device under development; signal detection, recognition, and identification on-line in the presence of noise and radio interference; the 1-10 GHz sky survey and the 1-3 GHz targeted search envisaged; and the mutual interests of SETI and radio astronomy. The report ends with a selective, annotated SETI reading list of pro and contra SETI publications.
Precise measurements of the black hole mass are essential to gain insight on the black hole and host galaxy co-evolution. A direct measure of the black hole mass is often restricted to nearest galaxies and instead, an indirect method using the single-epoch virial black hole mass estimation is used for objects at high redshifts. However, this method is subjected to biases and uncertainties as it is reliant on the scaling relation from a small sample of local active galactic nuclei. In this study, we propose the application of conformalized quantile regression (CQR) to quantify the uncertainties of the black hole predictions in a machine learning setting. We compare CQR with various prediction interval techniques and demonstrated that CQR can provide a more useful prediction interval indicator. In contrast to baseline approaches for prediction interval estimation, we show that the CQR method provides prediction intervals that adjust to the black hole mass and its related properties. That is it yields a tighter constraint on the prediction interval (hence more certain) for a larger black hole mass, and accordingly, bright and broad spectral line width source. Using a combination of neural network model and CQR framework, the recovered virial black hole mass predictions and uncertainties are comparable to those measured from the Sloan Digital Sky Survey. The code is publicly available.
Because high-energy gamma rays are primarily produced by high-energy particle interactions, the gamma-ray survey of the sky by the Fermi Gamma-ray Space Telescope offers a view of sites of cosmic ray production and interactions. Gamma-ray bursts, pulsars, pulsar wind nebulae, binary sources, and Active Galactic Nuclei are all phenomena that reveal particle acceleration through their gamma-ray emission. Diffuse Galactic gamma radiation, Solar System gamma-ray sources, and energetic radiation from supernova remnants are likely tracers of high-energy particle interactions with matter and photon fields. This paper will present a broad overview of the constantly changing sky seen with the Large Area Telescope (LAT) on the Fermi spacecraft.
We have conducted a search for strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 9. This is the third paper in a series. These surveys together cover ~19,000 deg 2 visible from the Northern Hemisphere, reaching a z-band AB magnitude of ~22.5. We use a deep residual neural network, trained on a compilation of known lensing systems and high-grade candidates as well as nonlenses in the same footprint. After applying our trained neural network to the survey data, we visually inspect and rank images with probabilities above a threshold which has been chosen to balance precision and recall. We have found 1895 lens candidates, of which 1512 are identified for the first time. Combining the discoveries from this work with those from Papers I (335) and II (1210), we have discovered a total of 3057 new candidates in the Legacy Surveys.
The Sloan Extension for Galactic Understanding and Exploration 2 (SEGUE-2) obtained 128,288 low-resolution spectra (R ~ 1800) of 118,958 unique stars in the first year of the Sloan Digital Sky Survey III (2008–2009). SEGUE-2 targeted prioritized distant halo tracers (blue horizontal-branch stars, K giants, and M giants) and metal-poor or kinematically hot populations. The main goal of SEGUE-2 was to target stars in the distant halo and measure their kinematics and chemical abundances to learn about the formation and evolution of the Milky Way. We present the SEGUE-2 field placement and target selection strategies. We discuss the success rate of the targeting based on the SEGUE-2 spectra and other spectroscopic and astrometric surveys. We describe the final SEGUE-2/SDSS-III improvements to the stellar parameter determinations based on the SEGUE Stellar Parameter Pipeline. We report a (g - i) color-effective temperature relation calibrated to the IRFM. We evaluate the accuracy and uncertainties associated with these stellar parameters by comparing with fundamental parameters, a sample of high-resolution spectra of SEGUE stars analyzed homogeneously, stars in well-studied clusters, and stars observed in common by the APOGEE survey. The final SEGUE spectra, calibration data, and derived parameters described here were released in SDSS-III Data Release 9 and continue to be included in all subsequent SDSS Data Releases. Because of its faint limiting magnitude and emphasis on the distant halo, the public SEGUE-2 data remain an important resource for the spectroscopy of stars in the Milky Way.
Advances in data collection technology for optical astronomy, such as the Dark Energy Camera, have facilitated the collection of some of the largest astronomical datasets in terms of sky area, depth, number of objects, number of observations, and frequency of observations. Consequentially, physical systems that have been historically rare become represented in small, but discoverable, numbers. I have developed techniques to identify rare physical systems (counterparts to high-energy neutrinos, counterparts to gravitational waves, and gravitationally lensed supernovae) that can shed new light on the physical processes that govern the Universe. For each system of interest, I collect new or search archival observations with the Dark Energy Camera, develop selection methodologies to find the system of interest in the observations, and quantify the efficiency of the search using simulations. Each of the three analyses has its own scientific implications: I constrain the observing program required to determine the contribution of supernovae to the diffuse high-energy neutrino flux; I set constraints on the physical properties of an optical counterpart to a compact object merger; and I identify candidate lensed supernovae using a novel machine learning technique. Looking forward, the work presented in this dissertation informs future rare object searches and facilitates measurements of the underlying properties of the Universe during the next era of optical survey astronomy.
The Energetic X-ray Observatory on Space Station (EXOSS) is a mission concept for high-sensitivity coded-aperture sky surveys and studies of the spectral and temporal behavior of astrophysical sources from approximately 3 keV to 1 MeV. The scientific motivation for the mission and the instrument requirements, including the need for high angular resolution to resolve and identify numerous detectable sources, are summarized. Two baseline telescopes are described: one employing a 1.4-sq-m array of Xe gas imaging proportional counters to cover the 3 to 100 keV range with 1 arcmin resolution; the second using a 2.8-sq-m array of NaI/CsI imaging phoswich detectors to span the 20 keV to MeV range with 12 arcmin resolution.
Sky survey in two IR spectral ranges, obtaining unbiased census of objects emitting in atmospheric window
Abstract With the advent of billion-galaxy surveys with complex data, the need of the hour is to efficiently model galaxy spectral energy distributions (SEDs) with robust uncertainty quantification. The combination of simulation-based inference (SBI) and amortized neural posterior estimation (NPE) has been successfully used to analyse simulated and real galaxy photometry both precisely and efficiently. In this work, we utilise this combination and build on existing literature to analyse simulated noisy galaxy spectra. Here, we demonstrate a proof-of-concept study of spectra that is (a) an efficient analysis of galaxy SEDs and inference of galaxy parameters with physically interpretable uncertainties; and (b) amortized calculations of posterior distributions of said galaxy parameters at the modest cost of a few galaxy fits with Markov chain Monte Carlo (MCMC) methods. We utilise the SED generator and inference framework Prospector to generate simulated spectra, and train a dataset of 2 × 10 6 spectra (corresponding to a five-parameter SED model) with NPE. We show that SBI—with its combination of fast and amortized posterior estimations—is capable of inferring accurate galaxy stellar masses and metallicities. Our uncertainty constraints are comparable to or moderately weaker than traditional inverse-modelling with Bayesian MCMC methods (e.g. 0.17 and 0.26 dex in stellar mass and metallicity for a given galaxy, respectively). We also find that our inference framework conducts rapid SED inference (0.9–1.2 × 10 5 galaxy spectra via SBI/NPE at the cost of 1 MCMC-based fit). With this work, we set the stage for further work that focuses of SED fitting of galaxy spectra with SBI, in the era of JWST galaxy survey programs and the wide-field Roman Space Telescope spectroscopic surveys.
The history of extreme ultraviolet (EUV) astronomy is briefly reviewed, and an overview of the Extreme Ultraviolet Explorer mission, launched into a near-earth (550 km) orbit on June 7, 1992, is presented. First, the principal objective of the mission are summarized. The instrumentation and operation of the mission are then described, with particular attention given to the sky survey instruments, the deep survey instrument, and the spectrometers. The discussion also covers the current view of the interstellar medium, early results from the mission, and future prospects for EUV astronomy.
There are expected to be millions of isolated black holes in the galaxy resulting from the deaths of massive stars. Measuring the abundance and properties of this remnant population would shed light on the end stages of stellar evolution and the evolution paths of black hole systems. Detecting isolated black holes is currently only possible via gravitational microlensing, which has so far yielded one definitive detection. The difficulty in finding microlensing black holes lies in having to choose a small subset of events, based on characteristics of their light curves, to allocate expensive and scarce follow-up resources to confirm the identity of the lens. Current methods either rely on simple cuts in parameter space without using the full distribution information or are only effective on small subsets of events. In this paper, we present a new lens classification method. The classifier takes in posterior constraints on light-curve parameters and combines them with a Galactic simulation to estimate the lens class probability. This method is flexible and can be used with any set of microlensing light-curve parameters, making it applicable to large samples of events. We make this classification framework available via the popclass Python package. We apply the classifier to ~10,000 microlensing events from the Optical Gravitational Lensing Experiment survey and find 23 high-probability black hole candidates. Our classifier also suggests that the only known isolated black hole is an observational outlier, according to current Galactic models, and the allocation of astrometric follow-up on this event was a high-risk strategy.
The spectral window at L-band (1.4 GHz) is important for passive remote sensing of soil moisture and ocean salinity from space, parameters that are needed to understand the hydrologic cycle and ocean circulation. At this frequency, radiation from extraterrestrial (mostly galactic) sources is strong and, unlike the constant cosmic background, this radiation is spatially variable. This paper presents a modern radiometric map of the celestial sky at L-band and a solution for the problem of determining what portion of the sky is seen by a radiometer in orbit. The data for the radiometric map is derived from recent radio astronomy surveys and is presented as equivalent brightness temperature suitable for remote sensing applications. Examples using orbits and antennas representative of those contemplated for remote sensing of soil moisture and sea surface salinity from space are presented to illustrate the signal levels to be expected. Near the galactic plane, the contribution can exceed several Kelvin.