adsabs/WIESP2022-NER huggingface dataset:
Paper: 2016MNRAS.459.2690H (fulltext)
giant component fractions imply the fundamental difference in the pathway topology between Snap100 and Lévy fractals; Snap100 has more efficient pathways to connect all galaxies at a shorter linking length than Lévy fractals. Very likely, this is due to the filamentary structures in Snap100, lacking in Lévy fractals. The middle panel of Fig. 2 shows the diameters. We can again see clear separations of Snap100 from the Lévy walk models. Snap100 reaches the maximum diameter, 300, at the linking length, 1.1 h −1 Mpc, while Lévy walk models reach the maximum diameters around 200 for linking lengths near 2.0 h −1 Mpc. Even for 100 Lévy walk realizations, none of the Lévy walk models can match the diameter measurements of Snap100. Hence, both the size of the giant component and diameter are network measures that discriminate the Lévy walk topologies from the Illustris simulation, despite the data sets being constructed to have matching abundance and two-point correlation statistics. The linking length for maximum diameter is related to the inflection point of the growth curve of giant component fractions; the rate of growth of the giant component decreases after reaching the maximum diameter. This transitioning feature occurs due to the ‘saturation’ of connecting edges. At first (i.e. small linking length values), increasing the linking length results in adding new vertices and increasing the size of the connected network components. However, once the largest diameter is reached, increasing the linking length tends to form new pathways within the existing structure between more far-flung members and only slowly increases the overall size of the connected structure. Therefore, the diameter is maximized at this critical scale, transitioning from ‘growing phase’ to ‘saturating phase’. The previous percolation studies are closely related to this maximum diameter scale, though they have not measured these specific diameters. If the system size is infinite, the diameter measurements transit from finite values to an infinity near this scale. The bottom panel of Fig. 2 shows transitivity results. Again, none of Lévy walk models mimics the transitivity curve of Snap100. We note that the statistical variances of transitivity measurements are much smaller than the other measurements as shown in Fig. 2 , since a single realization of the network is statistically large enough for counting triangles. Hence, the difference of transitivities between Snap100 and Lévy fractals also suggests that Snap100 is topologically very different from Lévy fractals. An interesting feature is the difference of convexities between Snap100 (concave or ‘cup’) and Lévy fractals (convex or ‘hat’). The transitivities of Snap100 are high for small linking lengths, then decrease to a minimum transitivity at 0.4 h −1 Mpc as the linking length increases. After this, the transitivities slowly increase to 0.8. This transitivity trend of Snap100 is related to the transition between the
Paper: 2016MNRAS.456.4377X (fulltext)
0.02, respectively. These values are also within the typical range obtained in the study of GRB afterglows (Medvedev 2006 ). We note that different values of ε e and ε B will only change the normalization, but not the slope, of the η jet – relationship (cf. equation 3 below). We then calculate the synchrotron emission from these accelerated electrons. Like any other jet models in literature, our jet model is phenomenological. Besides, we assume that all the jet parameters remain unchanged for different sources and accretion rates, which is certainly a strong assumption. This is partly because we still do not have good constraint on them. To conclude, the only free parameter in our jet model is its mass-loss rate . We note that the L R is found to be a power-law function of (see also Heinz Sunyaev 2003 ). 2.2 Hot accretion flow model Depending on the accretion rate, two types of hot accretion flow exist. They are the advection-dominated accretion flow (ADAF; Narayan Yi 1994 , 1995 ; Abramowicz et al. 1995 ) below certain critical accretion rate and the luminous hot accretion flow (LHAF; Yuan 2001 ) above it (see review by Yuan Narayan 2014 ). LHAF is thermally unstable (Yuan 2003 ). But if accretion rate is relatively low, , the growth time-scale of the thermal instability is larger than the accretion time-scale, so the gas can remain hot throughout the flow. We call it type-I LHAF. Above , the growth time-scale of the thermal instability is shorter than the accretion time-scale thus some cold dense clumps should be formed, embedded in the hot phase medium. We call it type-II LHAF or two-phase accretion flow. We follow the standard approach to calculate the dynamical structure and the emitted spectrum of ADAFs and type-I LHAF (e.g. YCN05 ). The L X at 3–9 keV band is then derived from the spectrum. For the two-phase accretion flow, optical/UV radiation from cold clumps will provide additional (likely dominant) seed photons for the inverse Compton scattering process, to generate the X-ray emission. The whole process is obviously complicated, depending on the detailed dynamics of the two-phases accretion flow such as the filling factor and temperature of clumps and so on. Following Yuan Zdziarski ( 2004 ), we simplify the problem by replacing the electron energy equation with the Compton y -parameter. With the assumption that the electron advection term is zero in the two-phase flow, we can calculate the radiative cooling rate. The bolometric luminosity can then be derived (Xie Yuan 2012 ). In order to derive 3–9 keV L X , we assume the spectrum to be a simple power law with exponential cutoffs at both the high and low ends, i.e. F E ∼ E 1−Γ exp (− E min / E )exp (− E / E max ), where the photon index Γ is constrained by the Compton y -parameter. E min is set arbitrarily to be 0.02 keV. E max is numerically determined by the electron temperature, i.e. E max = kT e , at the location where most of the radiation comes out (Yuan Zdziarski 2004 ).
Paper: 2021MNRAS.505.1940K (fulltext)
γ-ray telescopes, and, possibly, by some of the currently operating ones. To our knowledge, these results have never been reported before. We have discussed how different choice of parameters (such as source redshift, primary proton energy and angular distribution, extragalactic magnetic field, and extragalactic background light models) would change the observable spectra. We have also provided a qualitative discussion of the main stages of cascade development and the effects of additional processes. This study could significantly facilitate future axion-like particle searches in the optically thick region of blazar spectra. In addition, our work might be useful in extreme TeV blazar studies as well as in several related branches of γ-ray astronomy, including extragalactic background light and extragalactic magnetic field measurements. APPENDIX A: THE IMPACT OF FLUCTUATIONS ON THE OBSERVABLE SPECTRA The observable spectrum in the framework of the MHCM depends on the EGMF structure, in particular, on the number of proton trajectories used in our study. In Fig. A1 , we show the observable SEDs averaged over various numbers of proton trajectories. We conclude that the statistics of 10 2 trajectories is sufficient to obtain a stable enough average observable spectrum for E 10 TeV, and the use of 10 3 trajectories already allows one to robustly determine the shape of the spectrum for E 30 TeV. Figure A1. Average observable SEDs for the KD10 EBL model option and the following numbers of trajectories: 10 (black curve), 100 (red curve), 10 3 (green curve), and 10 4 (blue curve). In addition, we have calculated the observable SEDs for 10 2 individual proton trajectories to demonstrate the impact of fluctuations on the shape of the observable spectrum (see Fig. A2 ). The blue-to-red gradient of colours gives a visual representation to the values of the ratios of different individual SEDs at two benchmark energies: 10 TeV and 100 GeV. Blue colours represent lower ratios, while red colours – higher ones. We note that at E = 5 TeV, the maximal difference between the flux corresponding to 95 per cent of the trajectories is limited to the factor of 2.5. Figure A2. Observable SEDs for the KD10 EBL model option and 10 2 individual trajectories; colours represent the ratios of individual SEDs at 10 TeV and 100 GeV. APPENDIX B: DISTRIBUTION OF THE CRITICAL DISTANCE In Fig. B1 , we present a histogram of a distribution on ‘the critical distance’ L cr (see Section 4.1 for definition of this parameter). The normalization of this histogram corresponds to the case of discrete probability density function, i.e. with summation over the bins of the histogram, with the N th bin containing the largest value of L cr . Figure B1. Histogram of the critical distance L cr distribution (red curve). APPENDIX C: SPECTRA WITH AND WITHOUT TPP, URB, and DPP In Fig. C1 , we present histograms of the observable spectra of γ-rays and electrons calculated with the CRPropa3 code for
Paper: 2016ApJ...832...99L (acknowledgments)
We are grateful to the anonymous referee for a number of helpful suggestions. Support for this work was provided by the National Research Foundation of Korea to the Center for Galaxy Evolution Research, and by KASI under the RD program (Project No. 2014-1-600-05) supervised by the Ministry of Science, ICT and future Planning. M.P. acknowledges support from Mid-career Researcher Program (No. 2015-008049) through the National Research Foundation (NRF) of Korea. Software: IRAF, DAOPHOT II/ALLFRAME (Stetson 1987 , 1994 ).
Paper: 2016A&A...592A..19C (acknowledgments)
The authors thank the anonymous referee for the useful comments and suggestions, which helped to improve the paper. We are grateful to Emanuele Daddi for useful discussion, Maria Cebrián for providing the effective radii from the NYU-VAGC catalogue and Helena Domínguez-Sánchez, Kenneth Duncan, Andrea Grazian, Chiara Mancini and Adam Muzzin for providing their mass functions. A.C. is also gratetful to Alfonso Veropalumbo for helpful discussion. We also acknowledge the support of the grant PRIN MIUR 2010 The dark Universe and the cosmic evolution of baryons: from current surveys to Euclid. Funding for the SDSS and SDSS-II has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, the US Department of Energy, the National Aeronautics and Space Administration, the Japanese Monbukagakusho, the Max Planck Society, and the Higher Education Funding Council for England. The SDSS Web Site is http://www.sdss.org/ . The SDSS is managed by the Astrophysical Research Consortium for the Participating Institutions. The Participating Institutions are the American Museum of Natural History, Astrophysical Institute Potsdam, University of Basel, University of Cambridge, Case Western Reserve University, University of Chicago, Drexel University, Fermilab, the Institute for Advanced Study, the Japan Participation Group, Johns Hopkins University, the Joint Institute for Nuclear Astrophysics, the Kavli Institute for Particle Astrophysics and Cosmology, the Korean Scientist Group, the Chinese Academy of Sciences (LAMOST), Los Alamos National Laboratory, the Max-Planck-Institute for Astronomy (MPIA), the Max-Planck-Institute for Astrophysics (MPA), New Mexico State University, Ohio State University, University of Pittsburgh, University of Portsmouth, Princeton University, the United States Naval Observatory, and the University of Washington.
Paper: 2015ApJ...809..114L (acknowledgments)
Hinode is a Japanese mission developed and launched by ISAS/JAXA, with NAOJ as domestic partner and NASA and STFC (UK) as international partners. It is operated by these agencies in cooperation with ESA and the NSC (Norway). CHIANTI is a collaborative project involving the following Universities: Cambridge (UK), George Mason, and Michigan (USA). This work was partially supported by the JSPS Core-to-Core Program 22001. The work of D.H.B. was performed under contract with the Naval Research Laboratory and was funded by the NASA Hinode program.
Paper: 2017A&A...606A..94D (acknowledgments)
E.D.M., V.Zh.A., N.C.S., and S.G.S. acknowledge the support from Fundação para a Ciência e a Tecnologia (FCT) through national funds and from FEDER through COMPETE2020 by the following grants UID/FIS/04434/2013 POCI–01–0145-FEDER–007672, PTDC/FIS-AST/7073/2014 POCI–01–0145-FEDER–016880, and PTDC/FIS-AST/1526/2014 POCI–01–0145-FEDER–016886. E.D.M. acknowledges the support from the fellowship SFRH/BPD/76606/2011 funded by FCT (Portugal) and from the Investigador FCT contract IF/00849/2015/CP1273/CT0003. V.Zh.A., N.C.S., and S.G.S. also acknowledge the support from FCT through Investigador FCT contracts IF/00650/2015/CP1273/CT0001, IF/00169/2012/ CP0150/CT0002, and IF/00028/2014/CP1215/CT0002 funded by FCT (Portugal) and POPH/FSE (EC). J.I.G.H. acknowledges financial support from the Spanish Ministry of Economy and Competitiveness (MINECO) under the 2013 Ramón y Cajal program MINECO RYC–2013–14875, and the Spanish ministry project MINECO AYA2014–56359-P. We thank Sara Bisterzo and Donatella Romano for kindly providing their GCE models. This research has made use of the SIMBAD database operated at CDS, Strasbourg (France), the IRAF facility, and the VALD3 database. Finally, we are sincerely grateful to the anonymous referee, whose careful review helped to improve this paper.
Paper: 2018ApJ...852L..29R (fulltext)
be given elsewhere (D. Radice et al. 2017, in preparation). A summary of the simulations is given in Table 1 . Table 1 Gravitational and Baryonic Masses, Compactnesses, Tidal Deformability Parameters, BH Formation Time, and Disk and Ejecta Masses Notes. Disk and ejecta masses are given at the final simulation time. a NS gravitational mass. b NS baryonic mass. c NS compactness, . d Dimensionless quadrupolar tidal parameters, Equation ( 2 ). e Dimensionless tidal parameter, Equation ( 1 ). f Gravitationally bound material with outside of the apparent horizon. g Dynamic ejecta mass, computed as from the flux of unbound matter through the coordinate-sphere . h BH formation time, in milliseconds after merger. i Final simulation time, in milliseconds after merger. We compute the mass of the dynamic ejecta and of the remnant accretion disk for each model. Our results are shown in Table 1 and Figure 1 . The typical dynamic ejecta masses in our simulations are of the order of , in good qualitative agreement with previous numerical-relativity results. We do not find any clear indication of a trend in the dynamic ejecta masses as a function of the binary parameters or EOS. However, we find a clear correlation between the disk masses and the tidal parameter . According to our simulations, binaries with inevitably produce BHs with small accretion disks. These cases are incompatible with the infrared data for AT2017gfo, even under the assumption that all of the matter left outside of the event horizon will be ejected. Figure 1. Remnant disk plus dynamic ejecta masses (upper panel) and BH formation time (lower panel) plotted against the tidal parameter (Equation ( 1 )). For models that do not collapse during our simulation time, we give a lower limit. The horizontal dashed line shows a conservative lower limit for AT2017gfo, , obtained assuming that the entire disk is unbound. The vertical dotted line is . Errors on and are estimated following Equation ( 3 ) and are added in quadrature. The reason for this trend is easily understood from the lower panel of Figure 1 . The NS dimensionless quadrupolar tidal parameters depend on the negative-fifth power of the NS compactness ( Equation ( 2 )). Consequently, small values of are associated with binary systems having compact NSs that result in rapid or prompt BH formation. In these cases, the collapse happens on a shorter timescale than the hydrodynamic processes responsible for the formation of the disk. Consequently, only a small amount of mass is left outside of the event horizon at the end of the simulations. Binaries with larger values of produce more massive disks, up to , and longer lived remnants. In these cases, neutrino driven winds and viscous and magnetic processes in the disk are expected to unbind sufficient material to explain the optical and infrared observations for AT2017gfo (Perego et al. 2014 ; Wu et al. 2016 ; Siegel Metzger 2017 ). 4. Discussion On the basis of our simulations and the
Paper: 2017A&A...599A..24W (fulltext)
of mag, with mag. The power law removes any degeneracy in the slope of the dust extinction law, and thus excludes the possibility of significant grey dust. Another example is GRB 120815A , whose SED is fit by a power law and SMC-like extinction to give an value of 0.08 mag, which is significantly smaller than the of 0.44 mag. We find that GRB 121024A is also best fit with a power law. Indeed, Fig. 9 shows that only one object that has an overpredicted was fit with a broken power law. Although there is strong evidence for dust destruction caused by the GRB itself ( Morgan et al. 2014 ), this would not cause a discrepancy between and . Any dust that extinguishes the GRB would also be visible in depletion, so if that dust is destroyed it is no longer visible in depletion or extinction. Fig. 9 as measured directly from the SED against that calculated from the DTM. The green line indicates a 1:1 conversion between the two. Blue circles represent SEDs best fit with a simple power-law, whereas red triangles are used for broken power-law fits. Empty points refer to depletion measured from low-resolution spectra. Large error bars are due to significant errors in several measured parameters being combined in quadrature. Intervening systems such as absorbers are known to contain similar quantities of dust as galaxies (e.g. Ménard Fukugita 2012 ), although QSO-DLAs tend to show very little reddening ( Krogager et al. 2016 ; De Cia et al. 2016 ). For the group (2) objects, we notice that 050820A , 100219A , 111008A , and 130408A all have intervening absorbing systems. Should these objects have a high dust content, they could significantly affect the SED of the GRB afterglow, such that the reddening caused by dust in the host galaxy itself is indeed smaller, and thus pushes these objects towards the 1:1 line. However, for these intervening systems to be the reason for a much higher than from DTM, they would need to contribute around 80% of the extinction along the line of sight, whereas the systems in our sample are much weaker in metal line absorption than the host DLA (e.g. in GRB 100219A, Thöne et al. 2013 ). We therefore find it unlikely that a significant amount of the extra extinction is caused by intervening systems. 6.5. Equivalent dust column density Having established that depletion is a good tracer of the dust, and with being accurate and reliable, we look to the relation used to calculate , Eq. ( 10 ). This is based upon the relation between hydrogen and dust in the Galaxy, where a column of cm results in an of 0.45. We note that the value of the Galactic gas-to-dust ratio varies depending on the sample and technique used to measure it. We use the result of Watson (2011) . Measurements of this value have been consistent over the past few decades, and include those by Bohlin et al. (1978) , Predehl Schmitt (1995) , and Güver Özel (2009) . The value used does not alter the fact that a significant discrepancy is observed. In DLAs, the hydrogen
Paper: 2018ApJ...853..153M (acknowledgments)
This work was performed using HPC resources from GENCI-IDRIS (grant 2017-040219). It has been supported by Programme National Soleil-Terre (PNST/INSU/CNRS).
Paper: 2018ApJ...865..150Z (acknowledgments)
E.Z. and J.H. acknowledge support from NASA grant NNX16AG83G. R.K. was partially supported by the Max-Planck/Princeton Center for Plasma Physics and NSF grant AST-1517638. This work was also carried out as part of the IBEX mission, which is part of NASA’s Explorer program. The work reported in this paper was performed at the TIGRESS High Performance Computing Center at Princeton University, which is jointly supported by the Princeton Institute for Computational Science and Engineering and the Princeton University Office of Information Technology’s Research Computing department.
Paper: 2019ApJ...877...88C (acknowledgments)
We would like to thank the staff of the East Asian Observatory for their invaluable support in the completion of the BISTRO survey. We also wish to thank the people of Hawai’i for granting us access to the unique geographical site of the Maunakea observatory. Furthermore, we are grateful to the GAS Consortium for generously granting us access to their spectroscopic data. We also thank the anonymous reviewer for their helpful and detailed comments. Finally, we thank B.-G. Andersson, Kelvin Au, Jordan Guerra Aguilera, James Lane, Anna Ordog, Amélie Simon, Ian Stephens, and Julien Vandeportal for helpful discussions. This research was conducted in part at the SOFIA Science Center, which is operated by the Universities Space Research Association under contract NNA17BF53C with the National Aeronautics and Space Administration. The James Clerk Maxwell Telescope is operated by the East Asian Observatory on behalf of the National Astronomical Observatory of Japan, Academia Sinica Institute of Astronomy and Astrophysics, the Korea Astronomy and Space Science Institute, and the Center for Astronomical Mega-Science (as well as the National Key RD Program of China with No. 2017YFA0402700). Additional funding support is provided by the Science and Technology Facilities Council of the United Kingdom and participating universities in the United Kingdom and Canada. SCUBA-2 and POL-2 were built through grants from the Canada Foundation for Innovation. 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. This research has also made use of the simbad database and of NASA’s Astrophysics Data System Bibliographic Services. The Starlink software (Currie et al. 2014 ) is currently supported by the East Asian Observatory. M.K. was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT Future Planning (NRF-2015R1C1A1A01052160). W.K. was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF-2016R1C1B2013642). C.W.L. was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF-2016R1A2B4012593). D.L and K.Q. are supported by National Key RD Program of China No. 2017YFA0402600 and acknowledge the support from the National Natural Science Foundation of China (NSFC) through grants U1731237, 11473011, 11590781, 11629302, and 11725313. Software: S tarlink (Currie et al. 2014 ; Parsons et al. 2017 ; Chapin et al. 2013 ), The IDL Astronomy User’s Library (Landsman 1993 ).
Paper: 2015A&A...580A..62S (acknowledgments)
A.R.G.S. acknowledges the support from FCT (Portugal) through the grant reference SFRH/BD/88032/2012. M.S.C. and P.P.A. are supported by FCT through the Investigador FCT contracts of reference IF/00894/2012 and IF/00863/2012 and POPH/FSE (EC) by FEDER funding through the program COMPETE. Funds for this work were provided also by the EC, under FP7, through the projects FP7-SPACE-2012-31284 and PIRSES-GA-2010-269194. T.L.C. acknowledges the support of the UK Science and Technology Facilities Council (STFC).