adsabs/WIESP2022-NER huggingface dataset:
Paper: 2020ApJ...890...17Z (fulltext)
On the other hand, when V 0 = −2 V A (Figure 1 (c)), the forward LH-polarized Alfvén/proton-cyclotron wave at V 0 = 0 becomes backward RH-polarized mode, and the forward RH-polarized fast-magnetosonic/whistler wave with λ p k 1 at V 0 = 0 turns to the backward LH-polarized mode. For the forward fast-magnetosonic/whistler wave with λ p k > 1, its polarization remains the same as that at V 0 = 0. Comparing the ratio of to in the plasma frame to that in the spacecraft frame, we find that this ratio is independent of V 0 . Note that this conclusion can be confirmed by the expressions ( 6 )–( 8 ). Therefore, the correlation coefficient between B ⊥ and V ⊥ () is a useful parameter to identify the direction of the observed wave in the plasma frame, e.g., corresponding to the backward wave and for the forward wave. Then, by combining the information of the polarization and the direction of S ∥ , we can clearly identify the nature of the electromagnetic wave in the spacecraft frame. As shown in Table 1 , Alfvén/proton-cyclotron and fast-magnetosonic/whistler waves have different behaviors in the parameter space of , S ∥ , and polarization. Table 1 Linear Responses of Low-frequency Electromagnetic Waves in the Spacecraft Frame where V 0 > V A ( V 0 − V A ) 3. Application: Two Observation Events Figure 2 shows two events containing both LH- and RH-polarized low-frequency electromagnetic waves in the Earth’s magnetosheath by using Magnetospheric Multiscale ( MMS ) spacecraft observations (Burch et al. 2016 ). The particle moments are measured from the Fast Plasma Investigation (Pollock et al. 2016 ). The electric and magnetic fields are from the Electric Double Probe (Ergun et al. 2016 ; Lindqvist et al. 2016 ) and the FluxGate Magnetometer (Russell et al. 2016 ). These two events have the same distribution, that is, the waves with the ellipticity ∼−1 have frequencies larger than that with the ellipticity ∼1. The former and latter correspond to the LH-polarized and RH-polarized waves, respectively. Note that the ellipticity is defined as the ratio of the intermediate variance value to the maximum variance value in performing minimum variance analysis to the magnetic field. For nearly parallel and antiparallel waves, the definition of the ellipticity is consistent with the polarization defined in the field-aligned coordinates. The parallel Poynting flux is different for these two events, that is, in Event 1 and in Event 2. In these two events, ions have the perpendicular temperature anisotropy , and electrons exhibit the parallel temperature anisotropy . Furthermore, using the bulk ion flow velocity and the magnetic field data in Figure 2 , we find in Event 1 and in Event 2. Figure 2. Two examples of the wave event containing both LH- and RH-polarized low-frequency electromagnetic waves observed by MMS : (I) Event 1 occurred in the time interval of 12:27:00 UT−12:37:00 UT on 2018 October 7, and (II) Event 2 during 08:30:00 UT−09:00:00 UT on 2018 November
Paper: 2020MNRAS.498.3429G (fulltext)
keV counts cm −2 s −1 , where the effective area of the XRT and NICER were taken as 110 and 1900 cm 2 , respectively. The optical and UV magnitudes have been dereddened. The first clear detection of SAX J1808.4−3658 with NICER during the rise was made on August 6, 22:00 utc , when the net (background-subtracted) count rate was 9.16 ± 0.16 counts s −1 . We fit the spectrum of that GTI with an absorbed power law ( tbnew × pegpwrlw in xspec ), with the photoionization cross-section set to vern and the abundances set to wilm . Our best fit (χ 2 = 88 for 108 degrees of freedom) yields an N H of 0.33 ± 0.03 atoms cm −2 , a power-law photon index of 2.43 ± 0.07, and an unabsorbed 0.5–10 keV flux of (2.91 ± 0.11) × 10 −11 erg cm −2 s −1 . A potential detection was made one GTI earlier, on August 5 22:46 utc , when the net count rate (1.44 ± 0.06 counts s −1 ) was higher than during all observations preceding it (maximum of 0.85 counts s −1 ). However, comparison to contemporaneous background measurements indicated that the flux was still background dominated, and there was no statistically significant detection. Between July 30 and August 5, the net count rates varied between −0.22 and 1.44 counts s −1 , with an average of 0.402 ± 0.003 counts s −1 . This rate is significantly above zero, possibly due to contaminating sources in NICER’s ∼30 arcmin 2 field of view. The variations in the pre-outburst net count rate are likely due to limitations of the background model (which is still being refined). The 1σ standard deviation in the net count rate before the first detection is 0.32 counts s −1 . We consider the average pre-outburst net count rate plus three times the 1σ standard deviation, 1.37 counts s −1 , to be a good general estimate of the NICER detection limit of SAX J1808.4−3658. Using the best-fitting model to the spectrum of the first detection, this count rate corresponds to an unabsorbed 0.5–10 keV flux of ∼4 × 10 −12 erg cm −2 s −1 . 3 RESULTS The multiwavelength light curve of the 2019 rise to outburst of SAX J1808.4−3658 is shown in Fig. 1 . Activity of the source was first noticed in the optical i ′ -band observations, beginning July 25 (MJD 58689), as the i ′ -band magnitude fluctuated between 0.7 and 1.0 mag brighter than the quiescent level of approximately 19.8 mag. Then, between August 3.85 and 5.98 (MJD 58698.85 and 58700.98), the i ′ -band intensity increased to approximately 2 mag brighter than the quiescent level, and continued to increase over the coming days as the outburst progressed. The peak of the 2019 outburst was reached at around August 10 (MJD 58705) in optical, and August 14 (MJD 58709) in X-ray (Fig. 1 ). The first Swift /UVOT detection occurred on August 4 (MJD 58699.71), 10 d after the first sign of increased optical activity in the source, and 2 d before the first X-ray detection. The UV magnitude in all bands rose sharply by approximately 3 mag over the next 4 d until the outburst peak was reached. We note that
Paper: 2020MNRAS.492.5620B (acknowledgments)
ACKNOWLEDGEMENTS AKB, TD, and ADM were supported by the National Science Foundation through grant number 1616168. TDM acknowledges funding from NSF ACI-1614853, NSF AST-1517593, NASA ATP NNX17AK56G, and NASA ATP 17-0123. The BLUETIDES simulation was run on the BlueWaters facility at the National Center for Supercomputing Applications. ADM also acknowledges support through the U.S. Department of Energy, Office of Science, High Energy Physics, under Award Number DE-SC0019022.
Paper: 2021MNRAS.503.3371B (fulltext)
the NSs and BHs form according to the ‘rapid’ and ‘delayed’ SN models of Fryer et al. ( 2012 ) and pulsation pair-instability SN (PPSN) and pair-instability SN (PSN) models of Belczynski et al. ( 2016b ). The NSs and BHs receive natal kicks based on SN fallback on to them, as in Belczynski et al. ( 2008 ). Such fallback slows down the remnants, causing BHs of ≳10 M ⊙ ( Paper I ) to retain in the clusters right after their birth. Furthermore, NSs formed via electron-capture SN (Podsiadlowski et al. 2004 ) also receive small natal kicks and retain in the clusters. In , the PN treatment is handled by the algorithm (Mikkola Tanikawa 1999 ; Mikkola Merritt 2008 ). Such a PN treatment allows for GR evolution of the innermost NS- and/or BH-containing binary of an in-cluster (i.e. gravitationally bound to the cluster) triple or higher order compact subsystem, in tandem with the Newtonian-dynamical evolution of the subsystem (Kozai–Lidov oscillation or chaotic three-body interaction), potentially leading to the binary’s (in-cluster) GR in-spiral and merger. The treatment also undertakes the GR evolution of in-cluster NS/BH-containing binaries that are not a part of a higher order subsystem. As discussed in Paper II (see also the references therein), the moderate density and velocity dispersion in the model clusters make them efficient factories of dynamically assembling PN subsystems, particularly, those comprising BHs. As also discussed in Paper II (see also Anagnostou, Trenti Melatos 2020 ), the vast majority of the GR mergers from these computed model clusters are in-cluster BBH mergers. As also demonstrated therein (see also Banerjee 2020 ), the final in-spiralling phases of such merging BBHs sweep through the LISA and deci-Hertz GW frequency bands before merging in the LVK band. 2.2 Calculation of intrinsic merger rate density from computed model clusters To obtain the intrinsic merger rate density at the present cosmic epoch, ‘mock detection experiments’ are performed in a ‘Model Universe’ that is constructed out of the computed model clusters of Paper II . An ideal GW detector (a detector with zero noise floor) is considered that can detect GW arriving from all GR mergers within a comoving volume whose boundary is at a redshift z max . z max represents an (artificial) horizon, for average source inclination, for a realistic GW detector like LVK. For LVC O1/O2 observing runs, z max ≈ 1 (Abbott et al. 2019b ; Chen et al. 2021 ). However, since an ideal GW detector is considered here, z max will be varied to also address future, ground-based GW detectors of > Hz frequency band (e.g. LIGO A+ upgrade, Einstein Telescope, Cosmic Explorer). If the GR compact-binary merger rate density (per unit comoving volume), , in the Universe has an inherent dependence on the merger event redshift, z event , then the present-day, intrinsic merger rate density, , would depend on the detector horizon, z max (Abadie et al. 2010 ; Abbott et al. 2019b ). Conversely,
Paper: 2017MNRAS.469L..73L (fulltext)
estimates of the relative abundances of the COMs detected in L1157-B1. With this goal in mind, we obtained their excitation conditions and column density carrying out a simple rotational diagram analysis. We computed the molecular abundances with respect to H 2 by using the whole CO column density in the B1 direction, as estimated by Lefloch etal. ( 2012 ), N (CO) = and assuming a standard relative CO abundance X (CO) = N (CO)/ N (H 2 ) = 10 4 . The obtained temperatures, column densities and abundances are summarized in Table 1 . The rotational diagrams of the newly detected COMs are shown in Fig. 2 . For all the detected species, the line emission can be reasonably well fitted by one single gas component whose rotational temperature is around 2030K (Table 1 ). Glycolaldehyde has a slightly larger rotational temperature (50K) but also a larger error bar (10K). Considering only the lines observed with E up , a lower rotational temperature () would provide a very good fitting. Figure 2. Rotational diagrams of COMs detected towards L1157-B1. From the top to bottom: C 2 H 5 OH, H 2 CCO, HCOCH 2 OH and CH 3 OCH 3 . The best fit is drawn by the red line. For HCOCH 2 OH, the fit to the transitions with is drawn by the blue dashed line. Column densities vary from 210 12 cm 2 (formamide) to 110 15 cm 2 (methanol). Incidentally, the column density of the other COMs shows a relatively small range of variation, from 2 to 510 13 cm 2 , namely less than a factor of 3. In other words, with the exception of formamide, which is significantly less abundant, the other detected COMs have abundances a factor of 2050 lower than methanol. We searched for acetic acid (CH 3 COOH), the other isomer of glycolaldehyde and methyl formate, using the frequencies given in Ilyushin, Kleiner Lovas ( 2008 ). We failed to detect it. We could place an upper limit on its abundance, adopting T rot similar to that of methyl formate () and glycolaldehyde (), and the partition function given by Calcutt etal. (in preparation). We obtain a 3 upper limit of 510 9 at (10 8 at ): Acetic acid is less abundant by a factor of 35 with respect to methyl formate. 3.3 Comparison with hot corinos When compared to other solar-like star-forming regions where these COMs were previously detected (IRAS 162932422: Jaber etal. 2014 ; Coutens etal. 2015 ; Jrgensen etal. 2016 ; IRAS 2A and IRAS 4A: Taquet etal. 2015 ), L1157-B1 appears to be a site were COMs are very efficiently produced. The molecular abundances are higher in the shock than in the hot corinos by a factor of 210, depending on the species. The dimethyl ether abundance measured in IRAS 162932422 is the only exception. We note that only relatively small COMs are detected in the shock region, whereas larger COMs, for example, propanone (CH 3 COCH 3 ) and ethylene glycol [(CH 2 OH) 2 ], are detected in the inner protostellar environments (e.g. Maury etal. 2014 ; Jrgensen etal. 2016 ) but not yet in the shock. More observational data from
Paper: 2019MNRAS.487.4114Y (fulltext)
of the angular velocity of the black hole. This could lead to quasi-periodic signatures in the observed radiation, especially if the radiation mechanism at the current sheet is to some extent beamed. However, in an actual accretion disc the flux tubes may be much more irregular and variable, leading to more stochasticity in the observed signal. The main dissipation mechanism is likely to be reconnection at these current sheets. Since the environment around the black hole is filled by soft optical/UV photons from the accretion disc, particles accelerated in the reconnection process will be quickly cooled through inverse Compton scatterings and may also initiate pair cascades on the soft photons. The reconnection outflow may be strongly Compton dragged, and the reconnection proceeds in a regime as described by Beloborodov ( 2017 ) where the spectrum is dominated by bulk Comptonization from the reconnection outflow and has a high-energy cut-off near the pair production threshold. To get an estimation of the dissipation rate in realistic systems, let us consider a typical Seyfert galaxy, MCG-6-30-15, which has a supermassive black hole of mass M = 2 × 10 6 M ⊙ , bolometric luminosity , and X-ray luminosity (Reynolds et al. 1997 ). Measuring B in terms of the characteristic field G (Phinney 1983 ), we get If the magnetic field near the black hole reaches a value B ∼ B Edd , then the amount of power dissipated due to the kink instability will be enough to account for all the X-ray emission. The kind of relatively strong magnetic field with small coherence length-scales may be a generic outcome of MRI in the accretion disc, or associated with hotspots on the accretion disc as the flux tubes emerge buoyantly similar to solar magnetosphere. As we have seen from GRMHD simulations, when the accretion disc is threaded by a strong net magnetic flux, it tends to become magnetically arrested and form a powerful jet (McKinney Blandford 2009 ; Avara, McKinney Reynolds 2016 ); however, in situations where the net magnetic flux is small, the disc magnetic field may be dominated by the locally amplified components. MRI and the subsequent buoyancy or gravitational instabilities can produce fields with alternating polarities (e.g. Davis, Stone Pessah 2010 ; Zhu Stone 2018 ); they may also be quite asymmetric. As these structures are fed to the black hole, we may see continuous flux tube inflation and kink instability happening on a much more stochastic basis. We have seen from the simulations that the kink instability tends to happen when the confinement from the surrounding field is strong; this confinement can be produced by magnetic field from currents in the outer disc, or a disc wind that exerts pressure towards the central axis region. We have so far approximated the black hole as a resistive membrane in a flat space–time model. Whether the other GR effects are important will be tested using a time-dependent, GR force-free code in the future. Meanwhile,
Paper: 2017ApJ...835...39H (fulltext)
by allowing toroidal fields of opposite sign to exist on the two sides of the equator more easily. One way of capturing the physics of this in a 3D non-axisymmetric model may be to include a quenching of turbulent diffusivity in the regions of strong magnetic field. We plan to explore the effect of this in future. With these two opposite results at hand, one crucial question is: which of the two results is closer to reality? Although we cannot assert this with confidence at this stage, we believe that the 2D kinematic dynamo result that the dipolar parity is preferred on increasing diffusivity is the more appropriate result. Although in this paper we are taking account of the 3D nature of magnetic buoyancy and, in that sense, treating magnetic buoyancy more realistically, we still have not taken account of flux depletion from the convection zone and its bottom in an appropriate way. This is probably one important reason why our results are not matching with the results of previous 2D models (Chatterjee et al. 2004 ; Hotta Yokoyama 2010 ). We are right now exploring possible schemes to take account of the flux depletion due to magnetic buoyancy in a realistic way. We believe that this flux depletion is quite important in the solar dynamo. Choudhuri Hazra ( 2016 ) found that the Waldmeier effect cannot be reproduced from a theoretical dynamo model unless the flux depletion is taken into account. We have a future plan of incorporating flux loss due to magnetic buoyancy in a realistic way in our 3D kinematic dynamo model and then studying the parity issue more carefully. Since we are interested in a dynamo solution which has dipolar parity, we have converged on the reference solution presented here. If we decrease diffusivity, then we are led to the case where the meridional circulation provides the main transport mechanism for the poloidal field. On the other hand, if we increase diffusivity, then we obtain the quadrupolar mode. This is what has led us to choose the value 5 × 10 11 cm 2 s −1 for diffusivity inside the convection zone. 4. THE BUILD-UP OF THE POLAR FIELD After constructing the self-excited dynamo model, we now study how individual sunspot pairs contribute to the building up of the polar field and address the question of whether our understanding gained from this study necessitates the revision of some insights we have from SFT models. For this study, we shall put individual sunspot pairs on the solar surface by hand and look at the evolution of the magnetic field. In other words, we shall now not try to construct self-excited periodic solutions, although we shall keep using the same values of different parameters that we had used for constructing the self-excited periodic solution. We start our simulation by putting a single pair of bipolar sunspots in the northern hemisphere at different emergence angles λ emg and let it evolve under the axisymmetric mean flows and diffusion to see the development of the polar field. We have
Paper: 2017ApJ...834...40H (acknowledgments)
We thank Bill Harris and Eric Pelligrini for interesting discussions. C.S.H. and R.E.P. thank the the Zentrum für Astronomie der Universität Heidelberg (ZAH), Institut für Theoretische Astrophysik (ITA), and the Max-Planck-Institut für Astronomie (MPIA), for their generous support during R.E.P.’s sabbatical leave (2015/16) and C.S.H.'s extended visit (2015 October–November). R.E.P. is supported by Discovery Grants from the Natural Sciences and Engineering Research Council (NSERC) of Canada. C.S.H. acknowledges financial support provided by the Natural Sciences and Engineering Research Council (NSERC) through a postgraduate scholarship. The FLASH code was in part developed by the DOE-supported Alliances Center for Astrophysical Thermonuclear Flashes (ASCI) at the University of Chicago. This work was made possible by the facilities of the Shared Hierarchical Academic Research Computing Network (SHARCNET: www.sharcnet.ca ) and Compute/Calcul Canada. R.S.K. acknowledges support from the European Research Council under the European Communitys Seventh Framework Programme (FP7/2007-2013) via the ERC Advanced Grant “STARLIGHT: Formation of the First Stars” (project no. 339177). R.S.K. further acknowledges funding from the Deutsche Forschungsgemeinschaft (DFG) in the Collaborative Research Center SFB 881 The Milky Way System (subprojects B1, B2, and B8) and in the Priority Program SPP 1573 Physics of the Interstellar Medium (grant nos. KL 1358/18.1 and KL 1358/19.2).
Paper: 2015A&A...580L...9W (acknowledgments)
The research leading to these results has received funding from the European Community’s Seventh Framework Program (FP7/2007-2013) under grant agreement No. 269194 and also under the auspices of the US DoE by Los Alamos National Laboratory under Contract No. DE-AC52-06NA25396
Paper: 2018MNRAS.480.2535B (fulltext)
field is obtained using the cloud-in-cells particle assignment scheme (CIC; e.g. Hockney Eastwood 1981 ). We introduce some scatter before the mapping procedure in a way that is different from the original EZmock paper. The new scattering formula is where and are the ZA density field after and before the scattering, respectively, and G (λ) is a random number drawn from the Gaussian distribution with width λ. The exponential function, exp[ G (λ)], is used to avoid negative densities. The term including ρ a introduces a non-linear mapping, which converges to 1 when is large. It plays a similar role as the density saturation parameter in the original EZmock paper. Furthermore, we apply a density cut ρ c (called the density threshold in Chuang et al. 2015a ) on the ZA density field before applying the scatter formula to make sure that there is no object produced in a low-density region. The mock catalogue is then populated by randomly picking a fraction of the original ZA particles in each cell, which is equal to the number of haloes attributed to it by the PDF mapping procedure described above. Finally, we assign the velocity by multiplying the displacement field by a factor f , and combining it with a three-dimensional Gaussian random motion with width σ . The factor f is computed by where f () and H () are the growth rate and Hubble parameter, respectively, at the redshift of the simulation box. Thus, we have five effective bias parameters ( n d , A , λ, ρ c and σ ) to adjust EZmocks. In contrast to Chuang et al. ( 2015a ), we do not modify the input power spectrum for calibration because we want to observe the impact of different cosmological models, as explained in the next section. 2.2 Simulation set-up We use the same input power spectrum as the one used by Chuang et al. ( 2015a ), that is ΛCDM Planck cosmology with {Ω M = 0.307115, Ω b = 0.048206, σ 8 = 0.8288, n s = 0.96}, and a Hubble constant () given by h = 0.6777. The output galaxy catalogues are at redshift = 0.5618. Again, following Chuang et al. ( 2015a ), we calibrate the number density to 3.5 × 10 −4 , which is similar to that of the SDSS-III/Baryon Oscillation Spectroscopic Survey (BOSS) galaxy sample at ∼ 0.5 (Reid et al. 2016 ). The simulation boxes are 2.5 h −1 Gpc each side. The particle mesh used is 960 3 . We construct three sets of 3000 EZmock simulation boxes with three sets of parameters. These three sets of boxes share the same 3000 Gaussian random fields. Table 1 lists the values of these parameters. The first set is the reference, whose clustering statistics are similar to those in Chuang et al. ( 2015a ) but not the same, because the EZmock methodology we are using here is slightly different, as mentioned above. Table 1. The three sets of EZmock parameters used in this study. We construct 3000 EZmock simulation boxes for each set of parameters (i.e. 9000 boxes in total). The second set of 3000 EZmocks has a different amplitude in the input power spectrum (i.e.
Paper: 2017ApJ...836..218L (acknowledgments)
Thanks are given to the anonymous referee for the critical comments that motivated new calculations that reinforced the robustness of the analysis to be carried out. This work has been supported by the grant AYA2015-66506-P from the Spanish Ministry of Economy and Competitiveness (MINECO).