There is a large degree of variety in the optical variability of quasars and it is unclear whether this is all attributable to a single (set of) physical mechanism(s). We present the results of a systematic search for major flares in active galactic nucleus (AGN) in the Catalina Real-time Transient Survey as part of a broader study into extreme quasar variability. Such flares are defined in a quantitative manner as being atop of the normal, stochastic variability of quasars. We have identified 51 events from over 900 000 known quasars and high-probability quasar candidates, typically lasting 900 d and with a median peak amplitude of Delta m = 1.25 mag. Characterizing the flare profile with a Weibull distribution, we find that nine of the sources are well described by a single-point single-lens model. This supports the proposal by Lawrence et al. that microlensing is a plausible physical mechanism for extreme variability. However, we attribute the majority of our events to explosive stellar-related activity in the accretion disc: superluminous supernovae, tidal disruption events and mergers of stellar mass black holes.

The astronomical size of spectral data cubes that will result from the SKA pathfinders planned large HI surveys such as LADUMA; Fornax HI survey; DINGO; WALLABY; etc. necessitate fully automated three-dimensional (3D) source finding and parametrization tools. A fraction of the percentage difference in the performance of these automated tools corresponds to a significant number of galaxies being detected or undetected. Failure or success to resolve satellites around big spirals will affect both the low and the high mass end of the HI mass function. As a result, the performance and efficiency of these automated tools are of great importance, especially in the epoch of big data. Here I present the comprehensive comparison of performance between the fully automated source identification and parametrization software: SOFIA, the visual galaxy identification method and the semi-automated galaxy identification method. Each galaxy identification method has been applied to the same ∼ 35 gigabytes 3D HI data cube. The data cube results from the blind HI imaging survey conducted using the Westerbork Synthesis Radio Telescope (WSRT). The survey mapped the overdensity corresponding to the Perseus-Pisces Supercluster filament crossing the Zone-of-Avoidance (ZoA), at (`, b) ≈ (160◦ , 0.5◦ ). A total of 211 galaxies detected using the semi-automated method by Ramatsoku et al. [2016]. In this work, I detected 194 galaxies (using the visual identification method) of which 89.7% (174) have cross-matches/counterparts on the galaxy catalogue produced through semi-automated identification method. A total of 130 detections were made using SOFIA of which 89 were also identified by the two other methods. I used the sample of 174 visual detections with semi-automated counterparts as a Testbed to calculate the reliability and completeness achieved by SOFIA. The achieved reliability is ∼ 0.68 whereas completeness is ∼ 0.51. Further parameter fine-tuning is necessary to have a better handle on all SOFIA parameters and achieve higher reliability and completeness values.

We use the shear catalogue from the CFHT Stripe-82 Survey to measure the subhalo masses of satellite galaxies in redMaPPer clusters. Assuming a Chabrier initial mass function and a truncated NFW model for the subhalo mass distribution, we find that the subhalo mass to galaxy stellar mass ratio increases as a function of projected halo-centric radius r(p), from M-sub/M-star = 4.43(-2.23)(+6.63) at r(p) is an element of [0.1, 0.3] h(-1) Mpc toM(sub)/M-star = 75.40(-19.09)(+19.73) at r(p) is an element of [0.6, 0.9] h(-1) Mpc. We also investigate the dependence of subhalo masses on stellar mass by splitting satellite galaxies into two stellar mass bins: 10 < log (M-star/h(-1) M-circle dot) < 10.5 and 11 < log (M-star/h(-1) M-circle dot) < 12. The best-fitting subhalomass of the more massive satellite galaxy bin is larger than that of the lessmassive satellites: log(M-sub/h(-1) M-circle dot) = 11.14(-0.73)(+0.66) (M-sub/M-star = 19.5(-17.9)(+19.8)) versus log(M-sub/h(-1) M-circle dot) = 12.38(-0.16)(+0.16) (M-sub/M-star = 21.1(-7.7)(+7.4)).

The NASA K2 mission uses photometry to find planets transiting stars of various types. M dwarfs are of high interest since they host more short-period planets than any other type of main-sequence star and transiting planets around M dwarfs have deeper transits compared to other main-sequence stars. In this paper, we present stellar parameters from K and M dwarfs hosting transiting planet candidates discovered by our team. Using the SOFI spectrograph on the European Southern Observatory's New Technology Telescope, we obtained R approximate to 1000 J-, H-, and K-band (0.95-2.52 mu m) spectra of 34 late-type K2 planet and candidate planet host systems and 12 bright K4-M5 dwarfs with interferometrically measured radii and effective temperatures. Out of our 34 late-type K2 targets, we identify 27 of these stars as M dwarfs. We measure equivalent widths of spectral features, derive calibration relations using stars with interferometric measurements, and estimate stellar radii, effective temperatures, masses, and luminosities for the K2 planet hosts. Our calibrations provide radii and temperatures with median uncertainties of 0.059 R-circle dot (16.09%) and 160 K (4.33%), respectively. We then reassess the radii and equilibrium temperatures of known and candidate planets based on our spectroscopically derived stellar parameters. Since a planet's radius and equilibrium temperature depend on the parameters of its host star, our study provides more precise planetary parameters for planets and candidates orbiting late-type stars observed with K2. We find a median planet radius and an equilibrium temperature of approximately 3 R-circle plus and 500 K, respectively, with several systems (K2-18b and K2-72e) receiving near-Earth-like levels of incident irradiation.

We present results from MMT/Hectochelle spectroscopy of 390 red giant candidate stars along the line of sight to the recently discovered Galactic satellite Crater 2. Modeling the joint distribution of stellar positions, velocities, and metallicities as a mixture of Crater 2 and Galactic foreground populations, we identify similar to 62 members of Crater 2, for which we resolve a line-of-sight velocity dispersion of sigma(nu los) = 2.7(-0.3)(+0.3) km s(-1) and a. mean velocity of <nu(los)> = 87.5(-0.4)(+0.4) km s(-1) (solar rest frame). We also resolve a metallicity dispersion of sigma([Fe/H]) = 0.22(-0.03)(+0.04) dex and a mean of <[Fe/H]> = 1.98(-0.1)(+0.1) dex that is 0.28 +/- 0.14 dex poorer than estimated from photometry. Despite Crater 2's relatively large size (projected halflight radius R-h similar to 1 kpc) and intermediate luminosity (M-V similar to -8), its velocity dispersion is the coldest that has been resolved for any dwarf galaxy. These properties make Crater 2 the most extreme low-density outlier in dynamical as well as structural scaling relations among the Milky Way's dwarf spheroidals. Even so, under assumptions of dynamical equilibrium and negligible contamination by unresolved binary stars, the observed velocity distribution implies a gravitationally dominant dark matter halo, with a dynamical mass of. 4.4(-0.9)(+1.2) x 10(6) M-circle dot and a mass-to-light ratio of 53(-11)(+15) M-circle dot/L-V,L-circle dot enclosed within a radius of similar to 1 kpc, where the equivalent circular velocity is 4.3(-0.5)(+0.5) km s(-1).

Aims. This article describes the implementation of a focal plane based wavefront control loop on the high-contrast imaging instrument SCExAO (Subaru Coronagraphic Extreme Adaptive Optics). The sensor relies on the Fourier analysis of conventional focal-plane images acquired after an asymmetric mask is introduced in the pupil of the instrument. Methods. This absolute sensor is used here in a closed-loop to compensate for the non-common path errors that normally affects any imaging system relying on an upstream adaptive optics system. This specific implementation was used to control low-order modes corresponding to eight zernike modes (from focus to spherical). Results. This loop was successfully run on-sky at the Subaru Telescope and is used to offset the SCExAO deformable mirror shape used as a zero-point by the high-order wavefront sensor. The paper details the range of errors this wavefront-sensing approach can operate within and explores the impact of saturation of the data and how it can be bypassed, at a cost in performance. Conclusions. Beyond this application, because of its low hardware impact, the asymmetric pupil Fourier wavefront sensor (APF-WFS) can easily be ported in a wide variety of wavefront sensing contexts, for ground-as well space-borne telescopes, and for telescope pupils that can be continuous, segmented or even sparse. The technique is powerful because it measures the wavefront where it really matters, at the level of the science detector.

The Apache Point Observatory Galactic Evolution Experiment (APOGEE) has built the largest moderately high-resolution (R approximate to 22,500) spectroscopic map of the stars across the Milky Way, and including dust-obscured areas. The APOGEE Stellar Parameter and Chemical Abundances Pipeline (ASPCAP) is the software developed for the automated analysis of these spectra. ASPCAP determines atmospheric parameters and chemical abundances from observed spectra by comparing observed spectra to libraries of theoretical spectra, using. 2 minimization in a multidimensional parameter space. The package consists of a FORTRAN90 code that does the actual minimization and a wrapper IDL code for book-keeping and data handling. This paper explains in detail the ASPCAP components and functionality, and presents results from a number of tests designed to check its performance. ASPCAP provides stellar effective temperatures, surface gravities, and metallicities precise to 2%, 0.1 dex, and 0.05 dex, respectively, for most APOGEE stars, which are predominantly giants. It also provides abundances for up to 15 chemical elements with various levels of precision, typically under 0.1 dex. The final data release (DR12) of the Sloan Digital Sky Survey III contains an APOGEE database of more than 150,000 stars. ASPCAP development continues in the SDSS-IV APOGEE-2 survey.

Yes / A workshop was recently held at Nagoya University (31 October – 02 November 2017), sponsored by the Center for International Collaborative Research, at the Institute for Space-Earth Environmental Research, Nagoya University, Japan, to quantitatively compare the performance of today’s operational solar flare forecasting facilities. Building upon Paper I of this series (Barnes et al. 2016), in Paper II (Leka et al. 2019) we described the participating methods for this latest comparison effort, the evaluation methodology, and presented quantitative comparisons. In this paper we focus on the behavior and performance of the methods when evaluated in the context of broad implementation differences. Acknowledging the short testing interval available and the small number of methods available, we do find that forecast performance: 1) appears to improve by including persistence or prior flare activity, region evolution, and a human “forecaster in the loop”; 2) is hurt by restricting data to disk-center observations; 3) may benefit from long-term statistics, but mostly when then combined with modern data sources and statistical approaches. These trends are arguably weak and must be viewed with numerous caveats, as discussed both here and in Paper II. Following this present work, we present in Paper IV a novel analysis method to evaluate temporal patterns of forecasting errors of both types (i.e., misses and false alarms; Park et al. 2019). Hence, most importantly, with this series of papers we demonstrate the techniques for facilitating comparisons in the interest of establishing performance-positive methodologies. / We wish to acknowledge funding from the Institute for Space-Earth Environmental Research, Nagoya University for supporting the workshop and its participants. We would also like to acknowledge the “big picture” perspective brought by Dr. M. Leila Mays during her participation in the workshop. K.D.L. and G.B. acknowledge that the DAFFS and DAFFS-G tools were developed under NOAA SBIR contracts WC-133R-13-CN-0079 (Phase-I) and WC-133R-14-CN-0103 (PhaseII) with additional support from Lockheed-Martin Space Systems contract #4103056734 for Solar-B FPP Phase E support. A.E.McC. was supported by an Irish Research Council Government of Ireland Postgraduate Scholarship. D.S.B. and M.K.G were supported by the European Union Horizon 2020 research and innovation programme under grant agreement No. 640216 (FLARECAST project; http://flarecast.eu). MKG also acknowledges research performed under the A-EFFort project and subsequent service implementation, supported under ESA Contract number 4000111994/14/D/ MPR. S. A. M. is supported by the Irish Research Council Postdoctoral Fellowship Programme and the US Air Force Office of Scientific Research award FA9550-17-1-039. The operational Space Weather services of ROB/SIDC are partially funded through the STCE, a collaborative framework funded by the Belgian Science Policy Office.

Diss. (sammanfattning) Uppsala : Sveriges lantbruksuniv., 2008. / Härtill 5 uppsatser.

Title: Shell-like structures in the ISM: Observation versus simulations Author: Vojtěch Sidorin (vojtech.sidorin@gmail.com)1 Department: Astronomical Institute of Charles University2 Supervisor: Prof. RNDr. Jan Palouš, DrSc. (palous@asu.cas.cz), Astronomical Institute of the Czech Academy of Sciences3 Abstract: Shell-like structures are objects found in large numbers in the inter- stellar medium (ISM). They usually appear as bubbles or segments of bubbles and are believed to result from the deposition of mass and energy into the ISM by stars, gamma-ray bursts, or high-velocity clouds. Interstellar turbulence may play a role in their creation too. These structures influence the dynamics of the ISM and are also linked to star formation. In this thesis, I review our current knowledge of the ISM, interstellar turbulence, and shell-like structures in the ISM. Then I present the research into the GLIMPSE bubble N107 conducted in collaboration with my colleagues. N107 is a dusty shell-like structure found in our Galaxy. We explored its atomic, molecular, and radio-continuum components; derived its distance (3.6 kpc), size (radius of 12 pc), and expansion velocity (8 km s−1 ); and identified 49 associated molecular clumps. Using numerical simulations, we estimated the conditions under which N107 formed and concluded...