adsabs/WIESP2022-NER huggingface dataset:
Paper: 2021A&A...646A.148G (fulltext)
only occur with a libration period, T , in years given by with and H θθ = − R θθ , which can be calculated numerically, and both H II , H θθ are evaluated at the stable equilibrium point. Fig. 1 Level curves of a fictitious Hamiltonian. O indicates a stable equilibrium point at ( θ s = 60°, I 0 = 2) and X an unstable equilibrium point at ( θ u = 240°, I 0 = 2). The arrows show the total resonance width, which is 2( I sep − I 0 ), where I sep = 2.44. To obtain the width of the resonance in terms of Δ I , we follow the same reasoning as in Gallardo (2020) . Figure 1 shows that the resonance half-width is equal to the difference between I 0 and I sep , where I sep is defined by the separatrix such that where θ s and θ u are the stable and unstable equilibrium points. When we assume that the domain of the resonance is symmetric with respect to the nominal position, I 0 , the total width is twice Δ I . In some cases, asymmetrieswith respect to I = I 0 are present and a precise examination of the Hamiltonian level curves is required to obtain the exact width. In general, however, because Δ H = H ( θ s , I sep ) − H ( θ s , I 0 ), we can approximate Evaluating the derivatives at the stable equilibrium point ( θ s , I 0 ) and using Eq. ( 14 ), we have Using Eq. ( 6 ), the left-hand side is while is given by Eq. ( 13 ), then We recall that Δ I is in fact Δ I 1 . Strength is commonly defined as SR = ⟨ R ⟩− R min ( Gallardo 2006 ), which can be associated with the coefficient multiplying cos ( σ ) when R is a well-behaved cosine-like function, but in general, R could be very different from a simple cosine. In these situations, SR therefore is a reliable estimate of the sensitivity of R with σ . The strength is a global property of the resonance, as are the libration center and period. It is an indicator of the dynamical relevance of the resonance, and it generates different Δ a on each planet. The width in terms of Δ a 1 is obtained from the definition of I 1 in Eq. ( 4 ) and Δ a 2 is obtained from I 2 = constant and is evaluated at the center of the resonance. We obtain the half-widths in au: The higher the planetary mass m i , the narrower the relative width Δ a i ∕ a i . The resonance is the same dynamical mechanism that affects the two planets, but stronger effects are present in the planet with the lower mass. It is important to stress that Δ a i are given interms of Poincaré elements, but for planetary systems, the computed widths Δ a i in Poincaré elements arevery similar to the widths in astrocentric elements. Moreover, the widths obtained by the formulae above are correct as long as Δ a ≪ a . If large widths are obtained using these formulae, it is convenient to recalculate the resonance limits ( I max , I min ) by a numerical procedure that considers the separatrix obtained from the Hamiltonian given by Eq. ( 6 ). In this circumstance, it is possible to observe asymmetries between the two limits of the resonance around the exact (nominal)
Paper: 2017A&A...598A.111R (fulltext)
and neutrinos), which is observationally indistinguishable at that redshift from the EdS value of . 2.2. Key equations Since the spherical collapse overdensity threshold is several hundred, volume-weighted averaging, together with assumptions (iii) and (iv), implies that the average expansion rate is close to that of the underdense regions, especially at late times, and can be rewritten as where is the peculiar expansion rate of voids, or in other words, the expansion rate above that of the extrapolated high-redshift background EdS model (cf. Eq. (32) of Buchert Carfora 2008 ; Eq. (2.27) of Roukema et al. 2013 ). At early epochs, before the main virialisation epoch, the expansion is dominated by the EdS background model, that is, while at the present, the effective local expansion (measured by local estimates of the Hubble constant) is the sum of the background expansion rate and the peculiar expansion rate of voids, which reads Since we have an early-epoch EdS model that we extrapolate to later epochs (assumption (i)), matter conservation gives the effective present-day matter density parameter (e.g. Eq. (6), Buchert Carfora 2008 ) where are the current values of , respectively. Equation ( 6 ) has solutions A high-redshift () model that contracts would not be physically realistic, so that we have positive . We have a void-dominated model, therefore we also have positive . Thus, the solution of physical interest is We can now estimate the effective scalar curvature. The Hamiltonian constraint (e.g. Eq. (7), Buchert Carfora 2008 ) at the current epoch gives where is the effective (averaged) present-day scalar (3-Ricci) curvature parameter and is the effective (averaged) present-day kinematical backreaction parameter. See for example Eq. (2.9), Roukema et al. (2013) . The sum (Sect. 2.4.1, Buchert 2008 ) is not only a relativistic alternative to dark energy on large scales, it may also provide a relativistic contribution to dark matter on small scales. As summarised in Sect. 1 , observational constraints on recently evolved average spatial hyberbolicity remain weak, and we comment on this further in Sect. 5 . The FLRW equivalents of two of the parameters in Eq. ( 7 )- and -have been the subject of low-redshift observational work for many decades. In Eqs. ( 9 ) and ( 10 ) below, we show that adding a third long-studied observational parameter, , lets us observationally estimate both and when we use the CDM model as a proxy, in the sense that it provides a phenomenological fit to many observations. 3. <inline-formula specific-use="simple-math">Λ</inline-formula>CDM as an observational proxy With the aim of using CDM as an extragalactic observational proxy, we can use Eq. ( 1 ) and assumption (i) to write in alternative form to that in Eq. ( 7 ), and using Eqs ( 1 ) and ( 7 ), we can now write as Thus, Eqs. ( 9 ) and ( 10 ) show that and are constrained by the values of , and , estimated either by methods that minimise model dependence, or
Paper: 2017MNRAS.466.1733B (acknowledgments)
We thank the anonymous referee for taking the time to review this manuscript. JRB and CAH were supported by the Science and Technology Facilities Council (STFC) under the grant ST/L000776/1. SVJ acknowledges research funding by the Deutsche Forschungsgemeinschaft (DFG) under grant SFB 963/1, project A16. HRAJ MT and FF are supported by the Leverhulme Trust grant, RPG-2014-281, and the STFC grant, ST/M001008/1. JSJ acknowledges funding by Fondo Nacional de Desarrollo Cientfico y Tecnolgico (FONDECYT) through grants 1161218 and 3110004, and partial support from CATA-Basal (PB06, Comisin Nacional de Investigacin Cientfica y Tecnolgica (CONICYT)), the GEMINI-CONICYT FUND and from the Comit Mixto ESO-GOBIERNO DE CHILE.
Paper: 2017MNRAS.469L..99F (fulltext)
(King 2008 , 2009 ). Moreover, we assumed L L X for the sake of simplicity, but in fact the bolometric correction of the inferred X-ray luminosity might vary from system to system. This might depend e.g. on the line of sight through the outflow, as hinted by the change in spectral hardness among the ULXs considered in Table 1 , as well as by the conjectured connection with ultraluminous supersoft sources (Middleton etal. 2011 , 2015 ; Pinto etal. 2017 ). According to this scenario, NGC 1313 X-1 is likely to be seen more face-on because of the harder spectrum, and therefore L L X is a reasonable assumption (but it is more likely to suffer from beaming though), while NGC 55 ULX and NGC 5408 X-1 have softer spectra that may come from the reprocessing of the harder radiation from the inner edge of the disc (and perhaps by a close hot corona) by the optically thick wind, for which L X L . This latter correction might partially compensate the effect of beaming, but note that L X as well is assumed isotropic and neglects beaming effects. None the less, even when reduced by a factor 23, our inferred masses are consistent with previous estimates of similar systems as well as with the aforementioned scenario of ULX formation. Our calculations also neglect general relativistic effects, such as spinning BHs, and magnetic fields. We explored the impact of a spinning BH by changing the inner boundary condition and the normalizing radiative efficiency . We find values of M up to 20percent lower than in the no spin cases, owing to larger values of and at similar accretion rates. Magnetic fields might also contribute to accelerate the outflow (Blandford Payne 1982 ), effectively lowering w and increasing L for the same accretion rate. This might also lower the value of the inferred central mass. Regardless of their masses, BHs are not the only possible accretors powering ULXs. Indeed, the light curves of three ULXs show sinusoidal pulses with a period 1s that are a distinctive signature of neutron stars (Bachetti etal. 2014 ; Frst etal. 2016 ; Israel etal. 2017 ). Recently, King Lasota ( 2016 ) and King, Lasota Kluzniak ( 2017 ) argued that neutron stars may actually power a fraction of ULXs larger than previously expected. According to their analysis, pulsations may only be observed during a rather short phase of the ULX evolution, preventing an easy detection. However, the variability of the optical spectrum has revealed the existence of a massive stellar BH, likely 2030M , in M101 ULX-1 (Liu etal. 2013 ) and perhaps also in X-ray binaries associated with WolfRayet stars (Prestwich etal. 2007 ; Crowther etal. 2010 ; but see also Laycock etal. 2015 ). Therefore, it appears evident that ULXs comprise a diverse variety of accreting objects, and whether the majority is represented by BHs or neutron stars must be scrutinized further. Clearly, our analysis can be applied only to the subset of ULXs with outflows that probably host an accreting BH; none the less,
Paper: 2019MNRAS.489.1423Z (acknowledgments)
ACKNOWLEDGEMENTS This article is based on observations made in the Observatorios de Canarias del IAC with the WHT operated on the island of La Palma by the Isaac Newton Group of Telescopes in the Observatorio del los Muchachos. Based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere under ESO programmes 096.C-0130 and 098.D-0222. This work presents results from the European Space Agency (ESA) space mission Gaia . Gaia data is being processed by the Gaia Data Processing and Analysis Consortium (DPAC). Funding for the DPAC is provided by national institutions, in particular the institutions participating in the Gaia MultiLateral Agreement (MLA). The Gaia mission website is https://www.cosmos.esa.int/gaia . The Gaia archive website is https://archives.esac.esa.int/gaia . Based on observations obtained as part of the VISTA Hemisphere Survey, ESO Progam, 179.A-2010 (PI: McMahon). Data processing has been contributed by the VISTA Data Flow System at CASU, Cambridge and WFAU, Edinburgh. The VISTA Data Flow System pipeline processing and science archive are described in Irwin et al. ( 2004 ), Hambly et al. ( 2008 ) and Cross et al. ( 2012 ). This publication makes use of data products from the Wide-field Infrared Survey Explorer , which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration. Synthetic spectra used in this paper are calculated by France Allard and Derek Homeier based on BT-Dusty model atmospheres developed by France Allard. ZHZ was supported by the PSL fellowship.
Paper: 2016A&A...587A..61C (fulltext)
with distance estimates (Table A.1 ), as seen from the Galactic pole. Dynamically confirmed black holes are marked in orange circles, whereas BH candidates are indicated by yellow stars. Distance ranges are represented with bars while the systems with lower limits are indicated by arrows that follow the same colour index. Some systems are overlapped with other. Each faint white ring in the background image represents an additional 1.5 kpc from the Sun. Objects seem to concentrate along the direction towards the Galactic centre. The dynamical BHT in the upper right of the figure is BW Cir. Background image credit: NASA/JPL-Caltech/R. Hurt (SSC/Caltech). Fig. 3 Top : the distribution of dynamically confirmed BHs (circles) and BH candidates (stars) in the Galactic plane, using the Hammer projection. (Background image credit: Mellinger 2009 ). Some of the symbols are overlapped by others, especially in the Galactic centre region. Bottom : histogram of the distribution of BH transients in Galactic longitude ( left ) and latitude ( right ). A 10 bin size in longitude and 5 bin in latitude were used respectively. Here we revisit the problem of the size of the Galactic population of BHs, based on the currently observed sample, which is heavily affected by extinction. Duerbeck (1984) modelled the density distribution of several interacting binaries in the Galaxy. In a similar way, we want to obtain the density of Galactic BHTs and analyse the height distribution (; Col. 8 in Table A.1 ). Only 35 out of the 59 detected BHTs have estimated distances. Because of their transient nature, we have only detected those systems that went into outburst. Therefore, in a given period of time, we have only discovered a fraction of them (e.g. the brightest and/or closest BHTs – with the shortest outburst cycles). Thus, to derive the true distribution, we first need to find the maximum radial distance at which completeness of the sample is guaranteed, i.e. such that none of the X-ray outbursts are missed. The completeness of the sample can be obtained from the analysis of the density of objects as a function of the radial distance that is projected onto the Galactic plane (). The latter is derived from the Galactic latitude and the distance listed in Cols. 5 and 6 of Table A.1 . Here, we have used 31 out of the 35 BHTs with a reported distance (we exclude the four systems with lower or upper limits). In addition, we consider a conservative 50% uncertainty in systems with only a rough estimate of distance. To derive the density of objects () up to a radii , we count the number of BHTs lying in cylinders or radius centred at the Sun and infinite height (). However, given the large uncertainties with distance, in some cases an object could be placed in more than a single cylinder within errors. To account for this effect, for each object we randomly generate 10 000 values that assume a Gaussian distribution. Here, we naively assume the distance errors follow this sort of
Paper: 2018MNRAS.475.2051K (fulltext)
detected oscillatory patterns. Double-peaked emitters 3C 390.3 and Arp 102B Our hybrid method made the distinction between these two objects based on the presence (absence) of underlying periodic variability, despite that the differences in the shapes of their spectral lines are subtle. 2D (auto)correlation maps of Arp 102B have a simple linear shape, but for 3C 390.3 a manifold of substructures is superimposed. Namely, our analysis has shown the fluctuations in the interactions between the oscillations in the continuum and the emission lines of 3C 390.3 due to substantially different levels of correlation polarity. The clusters of correlations are divided by gaps of very low (or no) correlations, and the islands of correlations switch their polarity (between positive and negative values). This can be seen as evidence that there is an activation process that reduces correlation coefficients (from positive values up to zero). Later, a different relationship is evoked between the periodicities in light curves (e.g. negative correlations). The break off of the correlation band (on diagonal) may be due to the change of variability in the light curves or due to the modulatory effects of some unknown background factors, which may have certain cycles. We applied the hybrid method to a series of artificially non-linear and non-stationary oscillatory signals simulated by equations ( 6 ) and ( 12 ) with unidirectional and bidirectional coupling. The degree of non-linearity/asymmetry is controlled by the ratio (differing from 1) of the periods (frequencies) of the sinusoids. To introduce the non-stationary mechanism, we assign a random value between 0 and 10 to the amplitude of signals, while they were fixed over trial realization, adding the red noise. The 2D correlation map of bidirectional coupling of three oscillatory processes (see Fig. 12 ) almost matches the map of the real light curves. Figure 12. Simulation of bidirectional coupled three-oscillator network for the case of 3C 390.3. Left: random realization of equation ( 12 ) from two time series (black is U a = OP 1 and red is U c = OP 2) of amplitudes A = 1.954, B = 1.729, C = 2.357, phase φ = φ 1 = 2.359 rad, coupling strengths cp a → b = 0.7, cp a → c = 0.5, cp b → a = 0.2, cp c → a = 0.3, frequencies f a = 1/1000, f b = 1/300, f c = 1/100, and time delay of 100 arbitrary chosen time units. Right: corresponding 2D correlation map, which clearly shows three clusters related to fundamental periods as well as clusters of negative correlation. We cannot produce a correlation image with negative ‘correlation islands’ if the time delays between processes are different. We note that time delays between the continuum and the Hα and Hβ lines are ∼120 and 95 d, respectively, as reported by Shapovalova et al. ( 2010a ). Based on this, one can see the importance of the value of the time lag for the expression of a negative link between oscillations, which implies that physical places of oscillation
Paper: 2017ApJ...849...82H (fulltext)
for EW 0 (Ly α ) and β in A370-L57, and the gray areas represent the 1 σ confidence interval. In the right panel, the same information is represented by the filled star with error bars. The dependence of β on the age and metallicity of the population (middle panel) is more complex. At very young age ( Myr), β is almost independent of t and higher at lower metallicity (due to increased nebular emission). However, as the population ages and the nebular emission decreases, β increases in the Z > 0 populations but decreases for PopIII. By t ∼ 10 Myr the nebular emission has become negligible and β is monotonously higher for higher metallicity. The observed value for β in A370-L57 is consistent with almost any metallicity at some age. However, since t > 3 Myr is ruled out for Z > 4 × 10 −4 by EW 0 (Ly α ), the observed β requires Z ≲ 4 × 10 −4 . The right panel rules out a PopIII-dominated SED for A370-L57, because for the observed β the required EW 0 (Ly α ) would be ∼1000 Å. Despite this, our single population delayed exponential model is likely a gross oversimplification of the actual SFH of the galaxy. While the currently available data do not allow us to test more complex SFHs, a wider range of stellar ages and metallicities may be present. If older or more metallic stars contribute significantly to the UV continuum emission, younger and/or less metallic ones are required to compensate for their lower production rate of LyC photons in order to reproduce the observed Ly α luminosity. A conclusive diagnostic of the source of the Ly α emission in A370-L57 requires the determination of UV emission line ratios. Recently, Vanzella et al. ( 2016 ) measured line ratios C iv /Ly α = 0.25, He ii /Ly α = 0.067, and O iii ]/Ly α = 0.16 in the spectrum of a lensed z = 3.11 LAE with comparably low luminosity ( M UV = −17.0). If A370-L57 has similar line ratios, the C iv λ 1550, He ii λ 1640, and O iii ] λλ 1660, 1666 lines, among others, would be detectable with deep near-IR spectroscopy on current 10 m class telescopes. 9. Conclusions In this work we have taken advantage of strong lensing by the Abell 370 galaxy cluster in combination with deep imaging from the Hubble Frontier Fields and SHARDS Frontier Fields programs and MUSE spectroscopy to perform a detailed analysis of an Ly α emitter. This source would be fainter than magnitude 30 in the continuum if it were not magnified by the gravitational lens. The source, A370-L57, is a z = 5.75 galaxy with a low Ly α luminosity ( L (Ly α ) ∼ 10 42 erg s −1 ), which, however, implies an extreme Ly α EW of ∼420 Å. This value of the EW is exceptional among known galaxies in this luminosity range and redshift. The even fainter source B2, with similar properties and confirmed spectroscopically to be at the same redshift, is just ∼1 kpc away in projection and could be another star-forming region in the same galaxy or a close neighbor. The physical properties of A370-L57 are similar to those of galaxies with
Paper: 2020MNRAS.492..843G (fulltext)
detector, as a function of the neutrino energy E ν and of the source declination. In our analysis, we consider the IceCube effective area for time-dependent searches using muon neutrinos from point sources (Aartsen et al. 2014b ). The area for point sources is found using the results of Aartsen et al. ( 2015 ) and the link https://icecube.wisc.edu/science/data/PS-3years . The number of neutrinos expected from a source at distance of ∼1 Gpc is consistent with the upper limits found by IceCube as shown in He et al. ( 2018 ). 4 FRACTION OF SUPERNOVA OBSERVATIONS WITH DETECTED NEUTRINO COUNTERPART We now estimate the fraction f ν of CCSNe detected electromagnetically that will also be detected via high-energy neutrinos. We convolve N ( r ) with the frequency of occurrence of CCSNe as a function of redshift. Due to the shortness of the lifetime of the progenitors of CCSNe, typically a few million years, we can use star formation history as proxy of the history of the CCSN rate (e.g. Hopkins Beacom 2011 ; Madau Dickinson 2014 ). We find that the expected fraction of supernovae within distance r max that will have a detected astrophysical high-energy neutrino counterpart is where f b is the jet beaming factor, defined as the fraction of the sky in which the jet emits high-energy neutrinos, f jet is the fraction of CCSNe that produces jets, Poiss( k , λ) is the Poisson probability of measuring k for average value λ, and r max is the maximum luminosity distance out to which the CCSN can be detected optically. This fraction depends on the neutrino detection threshold through N ( r ) defined in equation ( 1 ). In this definition, we do not include the possibility that a background neutrino can be coincident by chance with the supernova, which we separately account for below. Here, we consider r max for two representative facilities for ongoing and future observations: the Zwicky Transient Facility (ZTF; Rauch 2019 ) and the Large Synoptic Survey Telescope (LSST; https://www.lsst.org/scientists/scibook ). For ZTF, we assume a magnitude limit of R ∼ 19 for a typical 30 s exposure (Bellm Kulkarni 2017 ; Rauch 2019 ). For LSST, we assume a magnitude limit of R ∼ 24 for a typical exposure of 2 × 15 s (Abell et al. 2009 ). After assuming an absolute magnitude at maximum for CCSNe of M = −17.5 (Patat et al. 1994 ), we find that they can be detected out to r ∼ 200 Mpc with ZTF, and out to r ∼ 1.5 Gpc with LSST. The cosmological effects are taken into account in the analysis. For the LSST case, the redshift effects become important. With these observational limits, using equation ( 2 ) and the model parameters (Model 1) Γ = 100, t = 100 s, and L = 10 51 erg s −1 , we find that a fraction of CCSNe detected by ZTF might produce neutrinos detectable with IceCube or Km3NET. For LSST, this fraction becomes . In order to check the effects of the model parameters on our results, we consider another set of model parameters (Model 2) like Γ = 100, t = 3.3 × 10 4 s,