adsabs/WIESP2022-NER huggingface dataset:
Paper: 2019A&A...626A..45P (fulltext)
Since the Monte Carlo simulations described in step (2) are time consuming, we first constrained the parameter space of interest by testing a wide range of (⟨ β ⟩, rms( β )) values on a coarse sampling of the ranges ⟨ β ⟩ = − 2.2, − 1.0 and rms( β ) = 0.1, 1.5. We then accurately constrained their best-fit and confidence range through the analysis of a 35 × 35 grid in the range ⟨ β ⟩ = − 2.0, −1.4 for both the Gaussian and log-normal distributions, and rms ( β ) = 0.4, 0.8 (for the Gaussian distribution) and rms( β ) = 0.4, 1.0 (log-normal). For each position in the grid and for each magnitude bin, we extracted 25 000 objects from the CB07 library and perturbed magnitudes in all bands as described in 3). We note that the estimate of L in step (4) requires the observed and simulated UV slopes distributions to be binned: the choice of the bin widths was tailored to ensure that the extended but poorly populated tails in the observed distributions are efficiently sampled by the simulations. As shown in Fig. 5 , different bin widths were thus set depending on the 1, 2, 3 σ ranges of the observed distribution so as to reduce numerical noise in our procedure. The best-fit parameters of the Gaussian and log-normal PDF( β ) in each magnitude bin are reported in Table 2 . Confidence regions for the PDF( β ) are shown in Fig. 6 , together with observed and best-fit distributions. It is also highlighted how the latter (blue lines) are reshaped by observational effects (red): only a full modelling approach such as presented in C12 and adopted in this work allows us to recover the intrinsic slope distributions from observations. Table 2. UV slope distribution: best-fit parameters and 68% c.l. uncertainties. Fig. 6. Simulation results for the Gaussian ( left panel ) and log-normal ( right panel ) fit in the two different magnitude bins. In the leftmost column , we show maximum likelihood contours at 68%, 95%, and 99% c.l. in green, blue, and red, respectively; the red cross indicates the position of the best fit parameters. The rightmost column shows the histogram of the observed data and the relevant best-fit distribution. The red continuous line is the intrinsic PDF( β ), which is transformed into the blue continuous line by observational effects. We find that L > L * objects at z ∼ 3 have typical, average UV slopes ∼ − 1.7. No significant variation with UV magnitude is found in the Gaussian case. The log-normal best-fit distributions point to a slightly redder average (∼ − 1.5) in the fainter bin, although with large correlated uncertainties between the parameters. The absence of a strong correlation between UV slope and magnitude is in agreement with what was found by C12 at z ∼ 4, but it disagress with the previous analysis of z ∼ 3 objects by Bouwens et al. (2009) . While it is not possible to determine whether the best assumption is the Gaussian or the log-normal shapes, we note that the latter does not seem to accurately recover objects in the (poorly
Paper: 2021MNRAS.503..660P (fulltext)
that an analytic continuation of B ( c ) to the lower half-plane c , apart from poles of Landau quasi-modes, contains also a pole due to the damped mode c = c − , and near this pole B ( c ) has the form: where For real c , expression ( 23 ) can be decomposed, with the aid of equation ( 21 ), as follows: where Now analytic continuation is obvious, since ε ± ( c ) can be replaced by off the real axis, and g ± are replaced by where, depending on signs ‘’ or ‘’, integration contour passes below or above the singularity at u = c . Note that i.e. this is a decomposition of function g (). Since has one zero in the lower half-plane c = c − , B − ( c ) has a pole at this point leading to ∝exp (− γ k t ) contribution to density decay. Expansion near c = c − gives Finally, substitution to leads to the desired result ( 35 ), if we choose the integration contour along the real u -axis. The input from this pole gives a density decay slower that the Landau damping for k > k * ≈ 0.437, as is seen in Fig. 8 . Note that decomposition ( 37 ) is not unique. Moreover, it is possible to decompose B ( c ) so that parts of new decomposition have no singularities in the upper/lower half-planes (Appendix B ). Gaussian in time density decay occurred for Maxwell B ( c ) (Fig. 6 ) is simply a reflection of the fact that B ( c ) has no singularities in the lower half-plane. 4.3 Power-law decay To understand an appearance of the power-law term (Fig. 7 ), we should re-examine derivation of equations ( 7 ) and ( 8 ). They are obtained as a result of analytic continuation of the integrals over the real u -axis by deformation of the integration contour to the lower half-plane. Since g () is zero for || > * , the cut in the complex plane is finite (Fig. 10 ), and deformation of the contour is not needed for this integral. On the either side of the cut The cut leads to an additional input to density ( 6 ): Integrating by parts, assuming g () is even and real, one obtains for large t : Expression in the square brackets gives sinusoidal oscillations with some phase shift due to the presence of in the denominator. If g ( * ) is small, the power-law decay reveals itself only after a while. Figure 10. Integration contour in ( 6 ) in the complex -plane (blue dashes). ‘+’ signs mark the Landau-damped quasi-modes obtained as zeros of . A wavy line marks the cut on real axis c : − * c * . 5 IMPLICATIONS In this article, we analysed numerical solutions of equations describing perturbations of the homogeneous stellar medium. Although the equilibrium state is problematic in the infinite media and invokes a so-called Jeans swindle (e.g. BT ), it is a good testing ground for many phenomena in stellar dynamics (see Bisnovatyi-Kogan Zel’dovich 1971 , for example of a more realistic set-up). The unexpected behaviour of damped solutions in the unstable domain is associated with the presence of a genuine damped mode, which is complex conjugate to the unstable Jeans mode. The damped mode cannot
Paper: 2018MNRAS.475..570J (acknowledgments)
ACKNOWLEDGEMENTS We would like to thank the anonymous referee for a constructive report that helped to improve the paper. The authors would like to thank the Klaus Tschira Foundation. SJ acknowledges funding by the graduate college Astrophysics of cosmological probes of gravity by Landesgraduiertenakademie Baden-Württemberg. SJ also acknowledges support by the IMPRS for Astronomy and Cosmic Physics at the University of Heidelberg. RP, CMS and VS acknowledge support through the European Research Council under ERCStG grant EXAGAL-308037. VS also acknowledges support through subproject EXAMAG of the Priority Programme 1648 ‘Software for Exascale Computing’ of the German Science Foundation. CP acknowledges support through the European Research Council under ERC-CoG CRAGSMAN-646955.
Paper: 2021MNRAS.504.2420I (fulltext)
of the AM CVn (= SDSS J120841.91+355024.8), two polars (AR UMa in a low state and AP CrB in a high state), and three dwarf novae of the sub-types U Gem, SU UMa, and WZ Sge (= GY Cnc, BZ UMa, and EZ Lyn, respectively) were obtained from SDSS DR16 (Ahumada et al. 2020 ). CV subtypes : The CV Gold Sample contains examples of all six major different sub-types, their respective numbers are listed in Table 4 . The different sub-types form clearly distinct clusters in the Gaia HR diagram (Fig. 8 , left-hand panel); 6 and the location of these clusters closely links to the spectro-photometric properties of each sub-type (Fig. 8 , right-hand panel). Table 4. The number of each type in the CV Gold Sample together with the range of their orbital periods. The novalike variables are characterized by stable high mass transfer rates and hot accretion discs that dominate the optical emission of these systems. Correspondingly, their cluster is located at small absolute magnitudes and blue colours. Two AM CVn stars, HP Lib and the prototype AM CVn itself (Faulkner, Flannery Warner 1972 ) are novalike variables with stable, hot helium discs that are somewhat bluer and fainter than their cousins with hydrogen-rich discs. The three sub-classes of dwarf novae exhibit clear trends in their location within the HR Diagram. The U Gem type dwarf novae have lower mass transfer rates than the novalike variables, their quiescent discs are therefore less luminous and their donor stars can contribute noticeably to the optical flux of the systems, which is reflected in the number of these systems being located close to the main sequence. The donors and accretion discs in the SU UMa systems are less luminous than those in U Gem-type dwarf novae, hence they are concentrated closer to the white dwarf cooling sequence. Finally, the WZ Sge type dwarf novae have the dimmest accretion discs and donor stars; in fact, some of them contain brown dwarf companions (GD552 Unda-Sanzana et al. 2008 ; QZ Lib (Pala et al. 2018 ), 1RXS J105010.3–140431 (Mennickent et al. 2001 ), SDSS J102905.21+485515.2 (Thorstensen, Alper Weil 2016 ), SDSS J143317.78+101123.3 (Hernández Santisteban et al. 2016 ), and SSS J122221.7–311525 (Neustroev et al. 2017 )). WZ Sge are therefore inherently the faintest CVs and merge into the white dwarf cooling sequence. A noticeable outlier among the dwarf novae is V1129 Cen, a long-period (≃21.4 h) CV that exhibits low-amplitude (≃0.6 mag) outbursts about once per year, but no emission lines are detected in its spectrum (Bruch 2017 ). The donor is a luminous F-type+ star, explaining the location in the HR diagram. Magnetic CVs have a larger spread due to their more varied spectral appearances. During states of low mass transfer they resemble the detached WD+M binaries whilst during high states, their optical spectra can contain cyclotron emission lines (Wickramasinghe 1988 ) that will affect their colour and absolute magnitude. Overall, the CV Gold Sample contains a
Paper: 2016A&A...588A...1P (acknowledgments)
R.K. acknowledges support from STFC via ST/L000709/1. J.P. and R.K. acknowledge comments from J. Anderson and C. Gutiérrez on an earlier version. L.D. acknowledges financial support from “Agence Nationale de la Recherche” grant ANR-2011-Blanc-SIMI-5-6-007-01. This work was partly supported by the EU/FP7 programme via ERC grant number 320360 awarded to G. Gilmore. AG-Y’s team is supported by the EU/FP7 via ERC grant no. 307260, the Quantum Universe I-Core program by the Israeli Committee for planning and budgeting and the ISF; by Minerva and ISF grants; by the Weizmann-UK “making connections” program; and by Kimmel and ARCHES awards. S.J.S. acknowledges funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant agreement no [291222] and STFC grants ST/I001123/1 and ST/L000709/1. S.B. is partially supported by the PRIN-INAF 2014 project Transient Universe: unveiling new types of stellar explosions with PESSTO. Support for L.G. is provided by the Ministry of Economy, Development, and Tourism’s Millennium Science Initiative through grant IC120009, awarded to The Millennium Institute of Astrophysics, MAS. L.G. acknowledges support by CONICYT through FONDECYT grant 3140566. M.S. acknowledges support from the Royal Society and EU/FP7-ERC grant number 615929, and STFC via ST/L000679/1. K.T. was supported by CONICYT through the FONDECYT grant 3150473, and by the Ministry of Economy, Development, and Tourism’s Millennium Science Initiative through grant IC12009, awarded to the Millennium Institute of Astrophysics, MAS. This work is based (in part) on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere, Chile as part of PESSTO, (the Public ESO Spectroscopic Survey for Transient Objects) ESO programme 188.D-3003/191.D-0935, and as part of programme 092.D-0586. This work utilises data from the 40-inch ESO Schmidt Telescope at the La Silla Observatory in Chile with the large area QUEST camera built at Yale University and Indiana University. The Liverpool Telescope is operated on the island of La Palma by Liverpool John Moores University in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias with financial support from the UK Science and Technology Facilities Council (proposal ID: PL12B05, P.I. R. Kotak). The William Herschel Telescope is operated on the island of La Palma by the Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias (programme W/2013A/20). This research has made use 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.
Paper: 2017ApJ...845...62G (acknowledgments)
I thank M. Debruyne for many years of technical support at the Elginfield Observatory where the observations were taken and also thank the student observers who took some of the observations. I am grateful to the Natural Sciences and Engineering Research Council of Canada for financial support.
Paper: 2021MNRAS.502.5528L (fulltext)
example, Ganeshaiah Veena et al. ( 2021 ) have shown that massive haloes whose spin is perpendicular to the filament spine rotate on average faster (i.e. have higher spins) than haloes with spins along the filament spine. A similar effect has been pointed out by López et al. ( 2019 ), who have shown that the haloes which experienced the largest amount of spin growth are also more likely to have spin orientations perpendicular to the filaments surrounding them. 5.1 Net angular momentum growth of haloes Here, we follow the López et al. ( 2019 ) approach and define the net spin growth as the ratio between the present-day spin, , and the proto-halo spin, , in the initial conditions, which we take as the matter distribution at redshift z = 80. This definition is motivated by the TTT framework, in which the angular momentum at some time is the initial spin times a time-dependent growth factor (see equation 1 ). Thus, within the TTT approach, the net spin growth is basically the above growth factor. López et al. have shown that haloes with high ratios for their mass are more likely to have collapsed later and thus followed the TTT predictions for longer. This observation holds for the population as a whole, however not necessarily for individual haloes which could have a high ratio due to non-linear effects boosting their late-time spin growth. To keep the analysis simple, we follow the López et al. classification and for each narrow bin in mass we divide the halo population into three subsamples corresponding to the haloes with: highest, medium, and lowest net spin growth. We abbreviate these subsamples as H, M, and L, respectively. Each category corresponds to exactly a third of the haloes in each halo mass bin. This nomenclature is slightly different from the one used in López et al. ( 2019 ), where the same categories are referred as winner (W), median (M), and loser (L). Here, we decide to change the names of the samples (and the abbreviation of the one with the highest net spin growth, W→H) in order to better highlight their properties and the motivation of the classification. This analysis is illustrated in Fig. 8 , where the top panel show the net spin growth, , for individual haloes as a function of their mass. It shows that the ratio increases systematically with halo mass and illustrates why the H, M, and L subsamples need to be selected using narrow mass bins. The selection is further depicted in the bottom left-hand panel in Fig. 8 , which shows the distribution of net spin growth for a narrow mass bin. While most haloes have a narrow range in values, which for the given mass bin cluster around , the distribution has extended wings with a considerable fraction of haloes with ratios an order of magnitude higher or lower. The three subsamples, each containing a third of the haloes, are shown in the panel by the three shaded regions. Figure 8. Top panel: the halo net angular momentum growth (i.e. the present-day angular momentum divided by
Paper: 2019A&A...629A...5C (fulltext)
also provide viable explanations. In any case, the transit of a more extended cloud of material, whether associated with a planet or not, might be more easily detectable. About 20 ks into the XMM-Newton observation (Fig. 2 ), the soft-band count rate drops by ≈35% for ≈800 s, i.e., two data points. This timescale is consistent with the occultation of a point-like source by the hypothesized planetary body of CVSO 30 b. However, the lack of an associated depression in the hard-band light curve makes an eclipse by a solid planetary disk unlikely. A temporary elevation in the absorption column by 10 21 cm −2 (e.g., caused by the transit of an extended planetary atmosphere) produces a count rate drop of 60% in the soft band with only a 10% drop in the hard band. Such a scenario would thus be compatible with the observation. By means of a Student’s t-test, we find that the mean of the two data points in question differs from that of the sample consisting of the two preceding and following points at the 2% significance level. As the ephemerides are uncertain, however, we count about ten similar opportunities during the flare where such an occultation may have happened and be interpreted in the same way. Therefore, the chance to obtain such a result by chance is about 20%, and we conclude that the data remain insufficient to produce a significant result. The hard-band light curve shows an apparent depression about 25 ks into the XMM-Newton observation (Fig. 2 ). This variation has no counterpart in the soft-band light curve, however, and might be more easily explained by the superposition of two flares or secondary heating rather than absorption or occultation of flaring material. 3.4. Planetary irradiation and mass loss Having measured the stellar X-ray flux, we now estimate the expected mass-loss rate of the candidate hot Jupiter CVSO 30 b to see whether such a configuration is physically plausible. A number of values have been proposed for the mass of CVSO 30 b (e.g., Barnes et al. 2013 ; Ciardi et al. 2015 , or Johns-Krull et al. 2016 ). These range from approximately one to seven Jovian masses. We assume here a stellar mass of 0.44 M ⊙ , a planetary mass of 3.9 M J , and a planetary radius of 1.61 R J . These values are based on those given in Table 1 . To remain on the conservative side regarding the planetary mass-loss rate, we increased the nominal mass estimate in Table 1 by its uncertainty and decreased the radius likewise. Both choices increase the assumed planetary density and inhibit mass loss. Kepler’s third law then demands a semimajor axis, a , of 0.00874 AU. The resulting Roche-lobe geometry is shown in Fig. 4 . The shape of the planetary candidate CVSO 30 b is determined by an equipotential surface, the level of which is given by the radius derived from transit modeling. The result clearly demonstrates the expected deviation from spherical geometry. Fig. 4. Roche lobe (solid line) and extent (blue shade) of planetary candidate CVSO
Paper: 2019A&A...628A..93P (fulltext)
first mechanism does not necessarily lead to an immediate terminal SN explosion, it may explain the three-decade-long eruptive phase of SN 2000ch ( Pastorello et al. 2010 ). The second mechanism is promising as it may reproduce the sequence of events leading to SN 2009ip and its subsequent evolution (e.g. Graham et al. 2017 , and references therein). Alternatively, mass loss, driven by waves generated in the convective core during the late nuclear burnings, has also been proposed for moderate-mass ( M ZAMS ∼ 20 M ⊙ ) stars and for very massive stars at low-metallicity regime. This would explain the violent mass ejections observed in some SNe IIn from a decade to a few months prior to core-collapse ( Quataert Shiode 2012 ; Shiode Quataert 2014 ). The modern strategy of SN searches and the availability of big data archives have increased the discoveries of pre-SN outbursts, but the number of events is still of the order of a few tens, and is limited in volume. Future SN searches with big telescopes, in particular the Large Synoptic Survey Telescope ( LSST Science Collaboration 2009 ), will enormously increase the discovery rates, and will provide us with valuable datasets of light curves with coverage of many years. Appendix A: Optical photometry of SN 2018cnf Table A.1. Optical photometry of SN 2018cnf: Johnson-Bessell B , V (Vega mag), Sloan u , g , r , i , z and PanSTARRS y (AB mag). Notes. PS1 = 1.8 m Pan-STARRS Telescope + GPC1 camera (Haleakala, Hawaii Islands, USA); ATLAS = 0.5 m ATLAS-1 Telescope + STA-1600 CCD (Haleakala, Hawaii Islands, USA); ASAS-SN-5 = 0.16 m Payne-Gaposchkin Telescope + FLI ProLine PL230 CCD (Las Cumbres Observatory – South African Astronomical Observatory); ASAS-SN-3 = 0.16 m Paczyński Telescope + FLI ProLine PL230 CCD (Las Cumbres Observatory – Cerro Tololo Inter-American Observatory, Chile); GTC = 10.4 m Gran Telescopio Canarias + OSIRIS (La Palma, Canary Islands, Spain); LT = 2.0 m Liverpool Telescope + IO:O (La Palma, Canary Islands, Spain); fl11 = 1.0 m Telescope (Dome 3) + Sinistro CCD (Las Cumbres Observatory – Siding Spring Observatory, Australia); fl16 = 1.0 m Telescope (Dome 5) + Sinistro CCD (Las Cumbres Observatory – South African Astronomical Observatory); fl03 = 1.0 m Telescope (Dome 4) + Sinistro CCD (Las Cumbres Observatory – Cerro Tololo Inter-American Observatory, Chile); fl15 = 1.0 m Telescope (Dome 2) + Sinistro CCD (Las Cumbres Observatory – Cerro Tololo Inter-American Observatory, Chile); fl06 = 1.0 m Telescope (Dome 7) + Sinistro CCD (Las Cumbres Observatory – South African Astronomical Observatory); fl12 = 1.0 m Telescope (Dome 8) + Sinistro CCD (Las Cumbres Observatory – Siding Spring Observatory, Australia); Copernico = 1.82 m Copernico Telescope + AFOSC (Mt. Ekar, Asiago Observatory, Italy); NTT = 3.58 m New Technology Telescope + EFOSC2 (ESO-La Silla, Chile); NOT = 2.56 m Nordic Optical telescope + ALFOSC (La Palma, Canary Islands, Spain). ( ‡ ) PanSTARRS w band converted to Sloan r ,
Paper: 2016MNRAS.459.2539C (acknowledgments)
MVCD thanks his scholarship from FAPESP (process number 2014/18632-6). LSJ acknowledges the support of FAPESP (2012/00800-4) and CNPq to his work. This work was supported in part by the Consejo Nacional de Investigaciones Científicas y Técnicas de la República Argentina (CONICET), Secretaría de Ciencia y Tecnología de la Universidad de Córdoba and Secretaría de Ciencia y Tecnologíca de la Universidad Nacional de San Juan. Funding for SDSS-III has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, and the U.S. Department of Energy Office of Science. The SDSS-III web site is http://www.sdss3.org/ . SDSS-III is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS-III Collaboration including the University of Arizona, the Brazilian Participation Group, Brookhaven National Laboratory, Carnegie Mellon University, University of Florida, the French Participation Group, the German Participation Group, Harvard University, the Instituto de Astrofisica de Canarias, the Michigan State/Notre Dame/JINA Participation Group, Johns Hopkins University, Lawrence Berkeley National Laboratory, Max Planck Institute for Astrophysics, Max Planck Institute for Extraterrestrial Physics, New Mexico State University, New York University, Ohio State University, Pennsylvania State University, University of Portsmouth, Princeton University, the Spanish Participation Group, University of Tokyo, University of Utah, Vanderbilt University, University of Virginia, University of Washington, and Yale University. This work has made use of the computing facilities of the Laboratory of Astroinformatics (IAG/USP, NAT/Unicsul), whose purchase was made possible by the Brazilian agency FAPESP (grant 2009/54006-4) and the INCT-A.