adsabs/WIESP2022-NER huggingface dataset:
Paper: 2021MNRAS.502.6101M (fulltext)
the size of the halo scatter in GR. For the mapping defined using the effective density field, given by equation ( 17 ), it has been expected that the GR X-ray luminosity should be equal to the f ( R ) gravity value multiplied by the factor . From Fig. 6 , the rescaled data in F5 appear to be higher than in GR by on average for both the non-radiative and the full-physics simulations. A similar level of deviation is also observed for the true density results, where equation ( 22 ) predicts that the GR and f ( R ) gravity X-ray luminosity should be equal after the values in f ( R ) gravity are divided by the factor . Again, the rescaled F5 X-ray luminosity is significantly greater than in GR on average. As for the Y SZ and Y X mappings, the disparity found here can be explained by looking at the gas density profiles in Fig. 2 . For both the non-radiative and full-physics data, the gas density in the inner halo regions is greater for F5 (with appropriate rescaling applied) than for GR. Because the inner regions have a greater contribution to the X-ray luminosity than for other proxies, as described above, this causes these differences in the inner regions to become significant overall, even for the non-radiative data for which the F5 and GR profiles are converged above a lower radius. This results in the general offset for the full range of masses as shown in Fig. 6 . As described above, the X-ray luminosity is also more strongly influenced by feedback processes, which can further increase the offset between F5 and GR if the feedback behaves differently in these two models. Our observation that the mappings have a poorer performance for the X-ray luminosity than for the other proxies is consistent with He Li ( 2016 ), who observed a disparity of . Unless further corrections are applied to account for the unpredictable effects of feedback in the mappings therefore the X-ray luminosity is unlikely to be a reliable proxy for mass determination in accurate cluster tests of f ( R ) gravity. 4.1.4 Further comments As described in Section 3.2 , we have excluded the core region of r 0.15 R 500 when calculating the thermal properties of our simulated FOF groups. We have also experimented excluding core regions of size r 0.1 R 500 and r 0.2 R 500 : for the scaling relations Y SZ – M, Y X – M , and – M , the relative differences between f ( R ) gravity and GR are barely affected; on the other hand, the effect is larger for the L X – M scaling relation, because L X is more sensitive to the inner halo regions than the other proxies. However, the L X – M relation is not ideal for reliable tests of gravity anyway, as noted above, and is mainly included in this work for completeness and for comparison with the other relations. Even if the entire core is included in the calculations, we have found that the effect on the Y SZ – M and Y X – M results is still very small, providing further confirmation that these relations can be used for reliable tests of
Paper: 2021ApJ...907...61R (fulltext)
and is very likely a few degrees. Thus in total we see that the observed bend is ∼70° at angle θ ≈ φ int /1.4. In other words, an intrinsic bend in the jet of only a few degrees will produce the overall projected bend in the jet axis of ∼70° that we see in Figure 4 (c) when viewed from within a few degrees of the jet axis. Of course, the observed bend angle tends to 180° as θ → 0. The simplest possible bending model is a monotonic bend that lies all in a single plane, as assumed above. Given a small viewing angle near the base of the jet, this would normally result in an apparent one-sided jet, due to the strong Doppler boosting of the approaching jet emission and de-boosting of the receding jet emission. The approaching jet would also rapidly fade with distance from the core as the viewing angle increases. However, if the bending plane lies perpendicular to the sky, the jet can cross our line of sight, resulting in apparent emission from the approaching jet on both sides of the core. Statistically, the odds of this alignment appear at first to be low, but in a flux-limited AGN sample, there is a strong preference for those jets that have maximum Doppler boosting factor. The latter occurs when a portion of the jet is pointing directly at us, which is the case for a jet crossing our line of sight. Lister ( 1999 , p99) showed that in fact a simple parabolic bent jet will have a total apparent flux density much larger than a straight jet with identical inner jet viewing angle, provided the bending occurs in a plane nearly perpendicular to our line of sight. One notable case of this azimuthal favoritism is the blazar PKS 1510−089, where Homan et al. ( 2002 ) provide strong evidence of a highly superluminal jet that makes a 180° apparent bend in the sky plane, with resulting collinear jet emission on either side of the AGN core. We do therefore have to consider the possibility that all of the radio emission seen in this blazar is associated with the jet, but just happens to appear to straddle the nuclear core due to projection effects. One clear difference between the radio structures of PKS 1413+135 and PKS 1510−089 is the inner counterjet component C in PKS 1413+135 seen in Figures 4 (c)–(f). An even closer component of the inner counterjet, which is connected to the core component, is seen in the 8.1 GHz and 23.8 GHz images of Figure 5 . No such inner counterjet, close to the core, is seen in PKS 1510−089, and it is very hard to imagine that these two components close-in to the core, which are so well aligned with the jet position angle projected across the core, are actually components of the approaching curving jet that have been projected across the core to the counterjet side after the approaching jet curves through an apparent bend of ∼70° from components N through G as seen in Figure 4 (c). There is also the surface brightness of the components to consider. The components within 10 mas on the northeast side of the core have much higher
Paper: 2019MNRAS.485.3970S (acknowledgments)
ACKNOWLEDGEMENTS AS and AW would like to acknowledge a support of Beethoven Grant No. DFG-NCN 2016/23/G/ST1/04083. KB and KN were supported by NCN Maestro Grant No. 2012/06/A/ST1/00258. We also want to thank the GOES, STEREO, SDO, and SOHO teams for developing and operating the instruments as well as for their open data policy. We are grateful to the referee for extensive and constructive comments and suggestions that helped us to improve the quality of the manuscript.
Paper: 2016A&A...592A.104D (acknowledgments)
We thank the anonymous referee for the helpful comments that helped us to improve the manuscript. This work is based on observations obtained with XMM-Newton , an ESA science mission with instruments and contributions directly funded by ESA Member States and the USA (NASA). M.D. thanks Paola Grandi, Daniele Dallacasa for useful discussions. M.D. and M.C. aknowledge financial support from the Italian Space Agency under grant ASI-INAF I/037/12/0 and extended PRIN INAF 2012. GL acknowledges financial support from the CIG grant “eEASY” No. 321913, from ASI-INAF 2014-045-R.0 and ASI/INAF I/037/12/0–011/13 grants. G.P. thanks the DLR: the Bundesministerium für Wirtschaft und Technologie/Deutsche Zentrum für Luft-und Raumfahrt (BMWI/DLR, FKZ 50 OR 1408).
Paper: 2019A&A...628A.127C (acknowledgments)
Acknowledgements We thank Alexandre Faure for providing collisional excitation rates at low temperatures, and Luca Matrà for sharing the model of the dust radiation field and the ALMA data of CO. We also thank the referee for helpful and thorough comments. HIFI has been designed and built by a consortium of institutes and university departments from across Europe, Canada and the United States under the leadership of SRON Netherlands Institute for Space Research, Groningen, The Netherlands and with major contributions from Germany, France and the US. Consortium members are: Canada: CSA, U.Waterloo; France: CESR, LAB, LERMA, IRAM; Germany: KOSMA, MPIfR, MPS; Ireland, NUI Maynooth; Italy: ASI, IFSI-INAF, Osservatorio Astrofisico di Arcetri-INAF; Netherlands: SRON, TUD; Poland: CAMK, CBK; Spain: Observatorio Astronómico Nacional (IGN), Centro de Astrobiología (CSIC-INTA). Sweden: Chalmers University of Technology - MC2, RSS GARD; Onsala Space Observatory; Swedish National Space Board, Stockholm University - Stockholm Observatory; Switzerland: ETH Zurich, FHNW; USA: Caltech, JPL, NHSC. This work was supported by the Momentum grant of the MTA CSFK Lendület Disk Research Group and by JSPS KAKENHI Grant Number JP16F16770. This research has made use of NASA’s Astrophysics Data System.
Paper: 2015MNRAS.449.2059C (acknowledgments)
We thank David Bacon, Alan Heavens, Enrique Gaztanaga, Catherine Heymans and Elisabeth Krause for useful conversations. RC and FP acknowledge support from STFC grant ST/H002774/1. This work was also supported in part by the National Science Foundation under Grant No. PHYS-1066293 and the hospitality of the Aspen Center for Physics.
Paper: 2015MNRAS.448.2301M (acknowledgments)
We enthusiastically thank the staff of Siding Spring Observatory and the W. M. Keck Observatory and its AO team, for their dedication and hard work. The authors wish to pay their respects to the Elders – past, present and future – of the traditional lands on which Siding Spring Observatory stands and to those of Hawai'ian ancestry on whose sacred mountain we are privileged to be guests. Without their generous hospitality, these observations would not have been possible. AMM, LJK, and MAD acknowledge the support of the Australian Research Council (ARC) through Discovery project DP130103925. This work was also partially funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, under grant no. (5-130/1433 HiCi). The authors acknowledge this financial support from KAU. AMM and CEM also acknowledge support by the National Science Foundation under award number AST-0908796.
Paper: 2020A&A...635A.190S (fulltext)
magnitude, but also on the stopping time. Fig. 11 Rootmean square of in the midplane as a function of r (lower abscissa) and the dimensionless gas pressure gradient parameter Π in the midplane (upper abscissa). The root mean square is calculated using the mass-weighted mean over 500 yr after an equilibrium value of the dust scale height is reached. In the simulation adi_Z=0.02_Lr=90au_taustop=0.1 (blue line), in which the dimensionless dust stopping time τ stop is fixed at 0.1, the Mach number increases with the pressure gradient parameter if Π ≲ 0.09, but is approximately constant if the pressure gradient is stronger. The Mach number in this one and the simulation adi_Z=0.02_Lr=90au (green line), in which the stopping time increases from 0.046 to 0.46, is comparable at all radii. That is, the turbulent strength does not depend significantly on the stopping time in this stopping time regime. The Mach number is lower overall, but depends more strongly on the radius in the simulation adi_Z=0.02_Lr=90au_a=3mm (orange line) in which the stopping time ranges from 0.0046 to 0.046. In this regime, the turbulent strength increases with both the strength of the pressure gradient and the stopping time. 5.3 Radial gas velocity In Fig. 12 , we show the radial velocity of the gas. The gas moves outward on average as a consequence of the inward radial drift of the dust and, as the total angular momentum is conserved, the transfer of angular momentum from the dust to the gas. Yet, the turbulent motions that are induced by the streaming instability lead to the variance in the gas velocity being greater thanthe speed of this mean outward motion. That is, the streaming instability does not cause a sustained inward transport of gas mass (and outward transport of angular momentum) that contributes to the observed stellar accretion ( Alcalá et al. 2017 ). 6 Discussion 6.1 Implications for turbulence and planetesimal formation in protoplanetary disks We have studied the interaction of two instabilities, the vertical shear instability and the streaming instability. Both instabilities appear to be robust: operation of the vertical shear instability requires a vertical rotation profile and a sufficiently short gas cooling timescale. Lin Youdin (2015) show that in the MMSN model, the instability can grow between r ≈ 5 and 50 au. On the other hand, only dust and a radial gas pressure gradient are necessary for the streaming instability to be active. Fig. 12 Radial gas velocity (solid line) as a function of r in the simulations adi_Z=0.02_Lr=9au and adi_Z=0.02_Lr=90au . (The dashed lines marks the boundary between the domains of the two simulations.) The velocity is computed as the mass-weighted average over the vertical domain extent and a time-span of 50 and 500 yr, respectively,after an equilibrium dust scale height has been attained in each simulation. The average radial velocity at r ≥ 3 au is plotted as a dotted line and amounts to 0.035 m s −1 . This outward
Paper: 2021ApJ...911...51L (fulltext)
two very weak periods were also detected, at 20 minutes and 90 minutes, but cannot be confirmed. Figure 10. Multiband PDM analysis of the oscillatory variation on a timescale of days. A period of 3.9 ± 0.005 days is clearly detected (upper panel) from light curves based on the superposition of two independent observations. The bottom panel is the phased light curves folded with the detected 3.9 day period, in which the symbols are the same as in Figure 2 , revealing a sinusoidally shaped light curve. Figure 11. Variability of HO Pup down to a timescale of hours. Panel (a) presents the SLT r -band photometric data taken from 2019 December to 2020 March. The blue curve represents the 3.9 day cycle fitted with a sinusoidal function (see Figure 10 ). To uncover the variability shorter than one day, a sinusoidal function of 3.9 days has been subtracted from this light curve and the residuals are displayed in panel (b). After removing the 3.9 day cyclic variations, we found a new cycle of 50 minute variations using Lomb–Scargle periodogram analysis, based on the light-curve data taken from 2019 December to 2020 January, as shown in panel (c). As can be seen from this panel, the variation signal is well above the false-alarm probability (FAP, indicated by the red and cyan dashed lines for the 95% and 99% FAPs, respectively). The variability with 50 minute period can be easily seen in the phased light curve as presented in panel (e). However, the 50 minute variations were barely resolved or undetected for the data collected between 2020 February and March, as evident in panels (d) and (f). Instead, complicated variations can be seen in the nightly chunks of light-curve data during this period of observations. 3.6. Polarization Variation We have also observed variations in polarization for HO Pup. Based on polarization level P and position angle θ measured from Lulin Observatory (see Table 3 ), a small and yet significant polarization was observed on 2018 October 24 and 26. However, the polarization drops back to an insignificant value on 2018 October 25 and 2018 October 28. The observed variation in polarization suggested that HO Pup exhibits intrinsic polarization. 4. Discussion 4.1. Spectral-energy-distribution Fitting Prior to our work, classification of HO Pup in the literature was done via inspection of its light curves, either as a Be star with GCAS-type variability (Samus et al. 2017 ) or as an IW And-type DN (Kimura et al. 2020a ). Here, we first estimated its spectral and luminous class using spectral-energy-distribution fitting together with distance estimation based on the parallax measurement from Gaia Data Release 2 (DR2) (1.6165 ± 0.0311 mas, or d = 618.6 pc, Gaia Collaboration et al. 2018 ). The observed SED of HO Pup was constructed using available broadband photometry covering from near-UV (NUV) to mid-infrared. In Table 5 we list all available broadband photometric data on HO Pup queried within 1′′ radius using the VizieR
Paper: 2018ApJ...869..105B (acknowledgments)
We thank the referee for the constructive report, which greatly improved the manuscript. We thank Patrick Ogle for the helpful comments. This work uses observations obtained with XMM-Newton , an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA. In this work, the NASA/IPAC Extragalactic Database (NED) have been used. Á.B., C.J., W.R.F, and R.K. acknowledge support from the Smithsonian Institution.
Paper: 2016MNRAS.461.1076C (fulltext)
the inhomogeneous Universe, in particular, by using the baryon acoustic oscillation (BAO) as a standard ruler (e.g. Cole et al. 2005 ; Eisenstein et al. 2005 ). The Baryonic Oscillation Spectroscopic Survey (BOSS) experiment demonstrated the ability of BAO measurements to provide a standard ruler to the per cent level at redshift 0.5 (Anderson et al. 2014 ). Though the BAO is known to be largely free of systematic errors (e.g. Vargas-Magaña et al. 2014 ; Ross, Percival Manera 2015 ), precise measurement requires surveys of a large number of sources over a large cosmic volume. The current and future dark energy surveys aim to efficiently sample tens of millions of faint galaxies/quasars at redshift 0.5 ≲ z ≲ 2.3 over the entire observable sky to measure BAO at the per cent level (e.g. eBOSS, 1 DESI, 2 PFS, 3 4MOST, 4 EUCLID . 5 ) The eBOSS survey (Dawson et al. 2016 ) in the SDSS-IV (Blanton et al., in preparation), started in Fall 2014 and is currently mapping the large-scale structure at redshift z > 0.6 with four different tracers: luminous red galaxies (LRGs; Prakash et al. 2015 ), emission line galaxies (ELGs; Comparat et al. 2015a ), QSOs, and Lyα absorption (Myers et al. 2015 ; Palanque-Delabrouille et al. 2016 ). It will provide the first density map covering the redshift range 0.6 z 2.5 over a large portion of the sky (7500 deg 2 of LRGs and QSOs, 1500 deg 2 of ELGs). To achieve these goals with a 2.5-metre telescope, eBOSS requires efficient methods to pre-select targets using both magnitude and colour cuts. For ELGs, there is an additional source of complication: their redshifts will be mainly determined by emission lines, and it is therefore important to characterize the sampling efficiency of ELGs with broad-band magnitude and colour selections (e.g. Comparat et al. 2015a ; Raichoor et al. 2016 ). Studies have shown that the future ELG surveys will sample the or the Hα emitters in an incomplete manner (Comparat et al. 2015b ; Tonegawa et al. 2015 ). A more precise quantification of this incompleteness is critical for a more detailed understanding of the selection effects and to enable more precise cosmological analysis. In the redshift range targeted by eBOSS (0.6 z 1.2 for ELGs), the strongest emission lines that can be observed in the optical are the oxygen , lines and the hydrogen Hβ (λ4861) Balmer line. All other lines are either outside of the optical window at these redshifts, or an order of magnitude weaker and therefore will not drive the completeness of the ELG survey. Of these three line luminosity functions (LFs), the LF is the most well-known. Its LF has been measured from redshift 0 to 4.7 (e.g. Ly et al. 2007 ; Zhu, Moustakas Blanton 2009 ; Gilbank et al. 2010 ; Bayliss et al. 2011 ; Sobral et al. 2012 ; Comparat et al. 2015b ; Khostovan et al. 2015 ), mostly due to interests in using as an empirical star formation rate (SFR) indicator (see Kennicutt 1998 ; Kewley, Geller Jansen 2004 ; Moustakas, Kennicutt Tremonti
Paper: 2016ApJ...823...13K (acknowledgments)
We thank the referee for constructive suggestions. We also thank R.J. van Weeren for comments on the manuscript. H.K. was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2014R1A1A2057940). D.R. was supported by the National Research Foundation of Korea through grant NRF-2014M1A7A1A03029872.
Paper: 2015ApJ...801...41R (acknowledgments)
I would like to especially thank Geoff Marcy for extensive discussions and advice, Howard Isaacson for sharing samples from his MCMC fits to the Keck RV data, and an anonymous reviewer whose comments helped to improve this manuscript. I am also grateful for helpful discussions with Lauren Weiss, Rebekah Dawson, Tim Morton, Brice-Olivier Demory, Brian Jackson, Jack Lissauer, Tom Loredo, Eric Ford, David Hogg, and John Johnson. I acknowledge support provided by NASA through Hubble Fellowship grant #HF-51313 awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS 5–26555. This work also benefited from the Summer Program on Modern Statistical and Computational Methods for Analysis of Kepler Data, held at SAMSI, Research Triangle Park, NC in 2013 June. This research has made use of the Exoplanet Orbit Database and the Exoplanet Data Explorer at exoplanets.org.
Paper: 2019MNRAS.489L...7S (fulltext)
constituting a plasma. Importantly, the observed β = 1 and the obtained Γ = 4/3 indicate that the longitudinal current, though in general not obliged to conserve along the magnetic tube, appears as an exact integral of motion at the scales under consideration, Since ρ ∝ r −2 − β = r −3 , we have for a hot flow h ∝ ρ Γ − 1 = ρ 1/3 ∝ r −1 ; therefore, by equation ( 2 ) the equality ( 49 ) holds, whatever the nature of the force balance in the jet. Energy conservation ( 10 ) then leads us to the above conclusion. This is direct evidence of a stable longitudinal current structure in the jet. It is interesting to consider what happens at 8 marcsec. Mertens et al. ( 2016 ), taking into account the results of Lyubarsky ( 2009 ), discuss that the jet may there enter a non-equilibrium regime or rather exhibit an early saturation of Poynting-flux conversion. Meanwhile, an alternative explanation may be a change of the jet thermodynamics. The relativistic gas is not characterized by a single polytropic index, and the general expression for its enthalpy is h = K 3 (1/Θ)/ K 2 (1/Θ), where K ν ( z ) is the Macdonald function of order ν and Θ = p /ρ is the temperature (Synge 1957 ). Useful simpler analytic approximations of the exact expression are presented in Mathews ( 1971 ), Meliani et al. ( 2004 ), Chattopadhyay Ryu ( 2009 ). In the two opposite limiting cases it corresponds to a polytrope with index Γ = 4/3 when Θ ≫ 1 and with index Γ = 5/3 when Θ ≪ 1. From equations ( 2 ) and ( 3 ) we have which allows us to formally estimate the polytropic index, respectively, for the case of a dominating longitudinal magnetic, transverse electromagnetic, and centrifugal pressure: Since Γ TEM = Γ CH 4/3, a hot flow with a dominating transverse electromagnetic or centrifugal pressure is not realized over 8 marcsec. The two other indices correspond to a cold flow: Γ LM is close to but yet slightly larger than the maximum possible 5/3, while, surprisingly, Γ CC almost coincides with 5/3 ≈ 1.67. Therefore, a transition from γ ∝ z 0.58 to γ ∝ z 0.16 at z ∼ 8 marcsec may be explained by the plasma cooling and transition from a hot flow with p ∝ ρ 4/3 to a cold flow with p ∝ ρ 5/3 . Over 8 marcsec we likely have a cold flow whose pressure is determined mainly by centrifugal forces, possibly with some contribution from the pressure of longitudinal magnetic field, while transverse electromagnetic fields give forces that almost compensate each other and result in a modest net effect. Determination of Γ from the jet acceleration and collimation profiles has power in revealing plasma composition, which is important for conclusions about exact mechanisms of jet launching. The transition directly from 4/3 to 5/3 as cooling occurs may be a sign of a pure electron–positron plasma component: electrons and positrons have the same mass and behave as the mentioned single-component perfect Synge gas. In the case of an electron–proton plasma, however, the transition from 4/3 to 5/3