adsabs/WIESP2022-NER huggingface dataset:
Paper: 2020A&A...634A.116V (fulltext)
H β +[OIII] lines after the subtraction of the continuum. The red curve represents the best-fit retrieval model from MC fits, and the shaded area encompass 68% of the MC sample; the black curve shows the [OIII] best fit obtained by Shen (2016) . Table B.1. [OIII] best-fit parameters. Notes. For each component, we report the amplitude (in erg s −1 cm −2 Å −1 ), the centroid, and the width of the best-fit Gaussian profile. B.1. Modelling rest-frame optical spectra The H α +[NII]+[SII] and H β +[OIII]+FeII systems of J0149+1501, J1421+2241, J1431+0535, J1436+6336, and J1220+0004 are redshifted in the K and H bands, respectively. We simultaneously fitted the continuum and all emission lines to reduce the degeneracies between BLR, NLR, and FeII emission. In short, we fitted a (single) power-law continuum, an optical FeII template ( Kovačević et al. 2010 ), and a combination of Gaussian functions to model BLR and NLR emission lines. In particular, depending on the complexity of FeII emission, we considered one or two FeII templates (see e.g. Vietri et al. 2018 ). These were convolved with a Gaussian; the width of this Gaussian, the amplitude normalisations, and velocity offset of the FeII templates were free variables in our fit (see Perna et al. 2017a for further details). Gaussian components were used to reproduce the emission lines. Specifically, we used (1) a systemic narrow ( F W H M 700 km s −1 ) Gaussian component for the [OIII] doublet and for the H β , H α , [NII], and [SII] doublets associated with unperturbed NLR emission; (2) a broad ( F W H M > 2000 km s −1 ) Gaussian component to fit the BLR H β and H α emission; and (3) an outflow ( F W H M > 700 km s −1 ) Gaussian component for all forbidden and permitted emission lines to reproduce prominent and asymmetric wings associated with outflowing gas. One or more additional sets of Gaussian components were considered to reproduce more complex profiles, for instance, asymmetric BLR emission lines (see e.g. J1421+2241, Fig. B.1 ) and extremely broad [OIII] profiles (e.g. J0843+0750, Fig. B.2 ; see also Fig. 11 in Coatman et al. 2019 ). Fig. B.2. Parametrisation of the MgII+FeII+FeIII ( left ) and H β +[OIII]+FeII ( middle and right panels ) of z > 2.5 QSO1 from the sample of Shen (2016) . The red lines show the best-fit from multiple systemic, outflow, and broad Gaussian profiles to the line features, together with a two local power laws to the continuum and one (two) template(s) to the FeII features (see text). Each curve with a different colour represent a distinct Gaussian set (or a FeII template) with same kinematic properties, as labeled in the figure. In the right panel we show, for each target, the spectrum around the H β +[OIII] lines after the subtraction of the continuum. The red curve represents the best-fit retrieval model from MC fits, and the shaded area encompass 68% of the MC sample; the black curve shows the [OIII] best-fit obtained by Shen (2016) . For J2238−0921, we do not
Paper: 2017MNRAS.464..946S (acknowledgments)
We thank Joshua Bloom, Saavik Ford, Kohei Inayoshi, Barry McKernan, and Cole Miller for useful discussions. BDM gratefully acknowledges support from NASA Fermi grant NNX14AQ68G, NSF grant AST-1410950, and the Alfred P. Sloan Foundation. Financial support was provided to NCS by NASA through Einstein Postdoctoral Fellowship Award Number PF5-160145 and to ZH by NASA ATP grants NNX11AE05G and NNX15AB19G. ZH gratefully acknowledges support from a Simons Fellowship in Theoretical Physics.
Paper: 2017MNRAS.472.1946S (acknowledgments)
Acknowledgements MS thanks Keiichi Umetsu and Peter Melchior for useful discussions. SE and MS acknowledge the financial contribution from contracts ASI-INAF I/009/10/0, PRIN-INAF 2012 ‘A unique dataset to address the most compelling open questions about X-Ray Galaxy Clusters’, and PRIN-INAF 2014 1.05.01.94.02 ‘Glittering Kaleidoscopes in the sky: the multifaceted nature and role of galaxy clusters’. SE acknowledges the financial contribution from contracts NARO15 ASI-INAF I/037/12/0 and ASI 2015-046-R.0. This research has made use of NASA's Astrophysics Data System (ADS) and of the NASA/IPAC Extragalactic Database (NED), which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. This work is based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/IRFU, at the Canada–France–Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This research used the facilities of the Canadian Astronomy Data Centre operated by the National Research Council of Canada with the support of the Canadian Space Agency. CFHTLenS and RCSLenS data processing was made possible, thanks to significant computing support from the NSERC Research Tools and Instruments grant program.
Paper: 2020ApJ...889L..32Z (fulltext)
repeated for 10 shots. This plot indicates that for increasing bias voltage (which is proportional to the axial magnetic field), the wavelength increases. This phenomenon is consistent with the MRTI theory, since Equation ( 5 ) shows that the increase of magnetic field causes the corresponding fastest-growing wavelength to increase. For a sufficiently large magnetic field, the wavelength is larger than the loop dimensions and the MRTI cannot occur. This is most likely the reason for the absence of the MRTI in previous solar loop simulation experiments where a much larger axial magnetic field was used (e.g., Stenson Bellan 2012 ; Wongwaitayakornkul et al. 2017 ). In Equation ( 5 ), besides B 0 , the other two parameters, ρ , g , also influence the fastest-growing wavelength. In order to remove the influence of these parameters and verify that the increasing wavelength corresponds with the MRTI theory, we introduce the parameter s = λρg . Using Equation ( 5 ), the fastest-growing mode corresponds toTo determine s , the quantities λ and g are obtained from the image measurement, while n is determined as a relative density from the light intensity that scales as n 2 . Keeping other experimental parameters the same, we set V b = 30, 40, 50, 60 V for 10 shots at each voltage to obtain s . Figure 3 (c) shows s plotted versus . The error bars are determined by the shot-to-shot variation of measured data and the line shows the best fit. From this figure, it is clear that s scales as as predicted by Equation ( 10 ). As the geometry of the experiment is more like a cylinder, the experimental results can also be used to compare with the MRTI under cylindrical geometry derived by Zhai Bellan ( 2016 ). Using the notation in Zhai Bellan ( 2016 ), the growth rate iswhere , , , and a is the radius of the cylinder. Consider a system with certain values Φ 2 and α subject to a random perturbation that contains all possible x = ka . The component x that gives the largest is defined as x *, and the fastest growth rate is defined as γ *. Figure 4 (a) shows the dependence of the fastest-growing mode on α for fixed Φ 2 = 3.77. Note that α is proportional to the axial magnetic field and x corresponds to 1/ λ . Figure 4 (a) shows that with the increase of axial magnetic field, the wavelength increases and the growth rate decreases, the same trend as predicted for the MRTI in planar geometry. Figure 4. (a) x * and γ * vs. α with Φ 2 = 3.77. (b)–(f) Comparison between the observed growth rate and the calculated growth rate from the MRTI theory under cylindrical geometry (each data point is from 10 shots and the error bar represents the spread over these shots). We assumed all of the experiments have the same parameters except for axial field with , , I = 10 4 A, , and that the observed mode is the fastest-growing mode. The only free parameter in the determination of Φ 2 is a . From the experimental results, x * can be obtained and the corresponding α and γ * can be
Paper: 2019MNRAS.489.5413M (fulltext)
may favour jet production. If a jet is launched, it is likely to dominate the power output of the event if viewed on-axis, where the radiation will likely be non-thermal, whereas off-axis emission is likely to be thermal. There is also the possibility of radiatively driven winds originating from the accretion disc, but we do not consider these here. Following MacLeod et al. ( 2014 ), if t visc > t fb , no longer traces , with viscous expansion of the disc modifying accretion time-scales according to (Cannizzo Gehrels 2009 ; Cannizzo, Troja Lodato 2011 ): where and α = 0.1 for thick discs. The form of during its rise is currently not well constrained; we model it crudely here using a half-Gaussian centred on t peak with σ = t peak /4, and normalize its peak to L Edd . In this work, we assume that the observable X-ray light curve will trace and plot examples of our simulated light curves following the above description in Fig. 1 . Figure 1. Simulated light curves for WTDEs based on the theory described in Section 2.1 . Higher M bh have faster rises to peak L , with fastest decay rates in light curve for BHs. For comparison of peak luminosities of these events, we normalize each light curve by L 5, peak , the Eddington luminosity of a BH. The WF experiences extreme compression perpendicular to the orbital plane, with this being maximized as it crosses pericenter. This is expected to trigger thermonuclear burning if its time-scale is much shorter than the dynamical time-scale (see eg. Luminet Pichon 1989a ; Brassart Luminet 2008 ; Rosswog et al. 2009 ; Haas et al. 2012 ). This burning originates in the tidal debris, with emission likely resembling type 1a SNe-like light curves in the optical band (Rosswog et al. 2008 , 2009 ; MacLeod et al. 2016 ; Kawana et al. 2018 ). Whilst thermonuclear burning may affect the amount of bound debris and subsequent accretion rate, no robust models of this currently exist and we neglect its impact in this work. 2.1.2 Spectral properties Following the modelling of emission from thick accretion discs (see Balbus Hawley 1998 for a review), the innermost sections of the disc, R 5 R S (as in Ulmer 1999 and Khabibullin et al. 2014 ), radiate as a blackbody at temperature: where L Edd is the Eddington luminosity of the BH. For IMBHs with masses of , this results in X-ray spectra with temperatures 0.2 keV. The soft emission from these events can be significantly affected by the interstellar medium’s (ISM’s) absorption along the line of sight (Auchettl, Guillochon Ramirez-Ruiz 2017 ). For each TDE, we set the Galactic neutral hydrogen column density, N H , to , close to the estimated extra-galactic median of N H (Esquej et al. 2008 ). We model the WTDE’s spectrum using the xspec model tbabs(zbbody) , but neglect modelling any spectral evolution. An optically thick extended envelope may form from stellar debris around the BH, reprocessing a fraction of the X-ray accretion flare into the UV and optical bands (eg. Loeb
Paper: 2016MNRAS.455L.104G (acknowledgments)
We thank the anonymous reviewer for comments that improved this Letter. This work has been supported by Polish National Science Centre MAESTRO grant DEC-2012/06/A/ST9/00276. KG thanks the Poznań Supercomputer and Network Centre for computing grant no. 195. We acknowledge the use of the HPC cluster HAL9000 of the Computing Centre of the Faculty of Mathematics and Physics at the University of Szczecin.
Paper: 2019A&A...625A..23C (acknowledgments)
We are grateful to the anonymous referee for her/his constructive critical comments and suggestions, which helped improving the paper.
Paper: 2020MNRAS.492..384C (acknowledgments)
ACKNOWLEDGEMENTS K. C-j has been supported by the Kim Il Sung University during this investigation, and would like to thank Jo Jong-won for providing Korean historical data and Mun Ui-ri for help with the English. The authors are grateful to an anonymous referee for detailed and helpful comments.
Paper: 2016A&A...586A.132P (acknowledgments)
The development of Planck has been supported by: ESA; CNES and CNRS/INSU-IN2P3-INP (France); ASI, CNR, and INAF (Italy); NASA and DoE (USA); STFC and UKSA (UK); CSIC, MICINN, JA, and RES (Spain); Tekes, AoF, and CSC (Finland); DLR and MPG (Germany); CSA (Canada); DTU Space (Denmark); SER/SSO (Switzerland); RCN (Norway); SFI (Ireland); FCT/MCTES (Portugal); and PRACE (EU). A description of the Planck Collaboration and a list of its members, including the technical or scientific activities in which they have been involved, can be found at http://www.sciops.esa.int/index.php?project=planckpage=Planck_Collaboration . The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/20072013)/ERC grant agreement No. 267934.
Paper: 2020ApJ...900...34H (fulltext)
e.g., or Mm, the 1027 line reaches higher layers. We also included, as reference, an isothermal contour at 7000 K that seems to follow relatively closely the height where the optical depth is unity for these lines. In the case of Ca ii , the near-UV transition forms at heights similar to those covered by the O i lines, while the infrared spectral line scans lower layers in the low to mid chromosphere. In the region , magnetic loops are stratified and the TR shifts to higher layers. Following this trend, the spectral lines also form higher in the atmosphere, with the exception of Ca ii IR, which is sensitive to the low chromosphere. 3.3.3. Inferring the LOS Velocity One of the main targets of future spectroscopic observations (e.g., done by Solar-C (EUVST) and SO/SPICE) is to examine the dynamics of the solar phenomena from the chromosphere to the outer atmosphere. We aim to estimate the capabilities of the spectral lines of interest to tackle this task. We do this by computing the Doppler shift of the line core of Lyman β and the two O i 1027 and 1028 Å lines. We believe a single Gaussian fitting is not accurate enough for Lyman β because the line shows multiple lobes, similar to the Mg ii UV spectral lines. Therefore, using the analysis of the IRIS observations as a reference, we perform the following steps. First, we detect the extrema of each spectral profile. Among them, we select the extremum that is nearest to the line core rest wavelength, and we perform a parabola fitting around the extremum to obtain the corresponding line core wavelength. In the case of the O i transitions, we compute the line core Doppler shift using a single Gaussian fitting of the intensity profile. We tried more complex procedures than we do for Lyman β , but we did not achieve noticeable improvements. The inferred LOS velocities for the entire snapshot FOV are plotted in the upper row of Figure 9 . We include in the middle row the LOS velocity at the height where the optical depth is unity for the line core wavelength (similar to what we did for the temperature in Figure 6 ). Additionally, we show in the bottom row the joint probability density functions (JPDFs) of the velocity obtained by the fitting and that from the B ifrost atmosphere (top and middle rows). In some pixels, the derived velocities were larger than 20 km s −1 . We believe those large values correspond to a bad fit of our method. The pixels where the velocity is larger than 20 km s −1 were excluded from the JPDF plots and from the computation of the Pearson correlation rate (although they are shown in the top row panels). Examining the JPDF results, we can say that both methods provide a similar spatial distribution of the LOS velocity for the three spectral lines. We can trace the velocities along the loop-like structures as well as inside the magnetic field elements. The differences among these LOS velocities can be seen in the JPDF plots and the Pearson correlation between both cases. For the
Paper: 2017ApJ...847..116G (fulltext)
dominates the fit below 1 keV, while the zeroth-order spectrum (MYTorusZ) dominates above 1 keV, with the scattered (MYTorusS) and line emission (MYTorusL) contributing at a significantly lower level. We present the soft (0.5–2 keV), hard (2–10 keV), and full (0.5–10 keV) X-ray fluxes of our quasars based on the MYTorus fits to our spectra in Table 4 . We also compute the intrinsic luminosities, which are corrected for absorption, scattering, and reflection, in Table 5 . Table 4 Observed X-Ray Fluxes Table 5 Absorption-corrected, Rest-frame X-Ray and Infrared Luminosities Note. a The 6 μ m luminosity was estimated by interpolating between the Wide-field Infrared Survey Explorer (WISE) photometric bands. 4. Discussion 4.1. The <inline-formula> <tex-math> </tex-math> <inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjaa88acieqn94.gif"></inline-graphic> </inline-formula> Relation Urrutia et al. ( 2012 ) used SED modeling to determine the bolometric luminosities of the quasars in our sample. When combined with broad line widths measured from our optical and near-infrared spectroscopy, their accretion rates are estimated and listed in Table 1 as . The X-ray photon index, Γ, has been shown to correlate with the BH accretion rate, , for high luminosity quasars ( e.g., Piconcelli et al. 2005 ; Shemmer et al. 2006 , 2008 ). In Figure 5 , we plot our derived Γ's versus , along with luminous unabsorbed quasars from Piconcelli et al. ( 2005 ), Shemmer et al. ( 2006 ), and Shemmer et al. ( 2008 ), as well as Compton-thick AGN from Brightman et al. ( 2016 ). The red quasars fall below the best-fit line from Shemmer et al. ( 2008 ), although they are largely consistent given the uncertainties on Γ. It is unclear if there is a systematic offset in the relation for red quasars given the small size of our sample. However, the trend of steepening photon index with increased accretion rate is apparent. Figure 5. X-ray photon index, Γ, vs. Eddington ratio, for luminous quasars. Gray filled squares are luminous unobscured quasars from Shemmer et al. ( 2006 , 2008 ). Open circles are Palomar-Green (PG) quasars with Γ from Piconcelli et al. ( 2005 ) and from Inoue et al. ( 2007 ). Gray filled triangles are local Compton-thick AGN from Brightman et al. ( 2016 ). Filled black circles are F2M quasars. The red line is the relation from Shemmer et al. ( 2008 ). The blue line is the Trakhtenbrot et al. ( 2017 ) relation based on their BCES (Y–X) and FITEXY linear regression analysis methods. Red quasars appear to have flatter Γ's relative to their optical/IR derived accretion rates, but obey the general trend of steeper Γ with increasing accretion rate. We note that a recent study by Trakhtenbrot et al. ( 2017 ), using a large set of low-redshift AGN with high-quality optical and X-ray data spanning 0.3–195 keV ( Swift /BAT AGN; Baumgartner et al. 2013 ), found weak to no correlation between the two quantities when Γ is computed over the full
Paper: 2016MNRAS.462..429G (acknowledgments)
This work was supported by the Science Development Foundation under the President of the Republic of Azerbaijan –Grant No EIF-2013-9(15)-46/14/11 .
Paper: 2017ApJ...849..112L (acknowledgments)
This research was supported by the Recruitment Program of Global Experts of China, NSFC under grants 41374173 and 41774179, and the Specialized Research Fund for State Key Laboratories of China. We acknowledge the use of data from SOHO , Wind , ACE , Ulysses , and GOES .
Paper: 2017MNRAS.470.1881P (fulltext)
signatures associated with relativistic protons. In this study, we have demonstrated how high-energy neutrino observations may be used to assess p at SN shocks propagating in dense CSM. In particular, the IceCubes measurement of the diffuse neutrino flux already constrains p 0.3(0.04/) or p 0.2(0.04/) when including the up-going muon neutrino sample from the Northern Sky (Section 3.1 ). Even more stringent constraints on the acceleration efficiency may be placed by direct observations of close-by SNe IIn with neutrino telescopes (Section 3.2 ). The neutrino flux from an SN IIn depends on its distance, shock velocity, mass-loading parameter and proton acceleration efficiency (Section 3.2 ). All parameters, except for the latter, can be, in principle, inferred from radio and optical observations of SNe IIn. For example, v sh is routinely inferred from the width of optical emission lines, while K w can be derived by the fitting of radio observations (Chevalier 1998 ; Chevalier, Fransson Nymark 2006 ; Chandra etal. 2015 ). Besides the intrinsic source parameters that affect the neutrino luminosity, as exemplified through scenarios S1 and S2, the actual distance of the source has the strongest impact on the IceCube expected neutrino rate (see equation 12 ). The IceCube event number expected within the first year in both scenarios discussed in Section 3.2 is plotted in Fig. 9 (bottom panel) as a function of the source distance. Different types of lines correspond to three values of the proton acceleration efficiency marked on the plot. The curves are obtained after scaling the total number of muon neutrinos obtained in S1 and S2 (see Table 2 ) with the source distance and p . The top panel in Fig. 9 shows the all-sky number of SNe IIn expected over 8years up to a distance D L (black thick line); the number is derived using the CC SN rate of HB06 and 0.04. For p values allowed by the diffuse flux measurements, i.e. p 0.2(0.04/), only S1-like SNe IIn at distances 18Mpc are strong enough neutrino emitters to constrain less efficient acceleration scenarios, in agreement with the predictions by Murase etal. ( 2011 ). If p 0.2, IceCube would be capable of claiming a neutrino detection from an S1-like SN IIn exploding at 10Mpc. For SNe IIn with lower mass-loading parameter K w , as discussed in S2, the neutrino rate decreases significantly, even for p 0.2. This restricts the accessible distance to no more than 4Mpc. Figure 9. Bottom panel: Expected IceCube event number as a function of luminosity distance D L for the two SN scenarios discussed in the text (S1: blue lines; S2: cyan lines). For the second scenario, the number of neutrinos expected only within the first year is shown. For both scenarios, the results for three different values of the proton acceleration efficiency are presented (see the legend). The horizontal black and red lines indicate the number of neutrinos required to reach IceCubes sensitivity and 5 discovery potential,
Paper: 2019A&A...629A.138K (acknowledgments)
The THÉMIS observations were supported by the Programme National Soleil-Terre (PNST) of the French Centre National de la Recherche Scientifique (CNRS).