adsabs/WIESP2022-NER huggingface dataset:
Paper: 2021A&A...651A..41C (fulltext)
the shock to larger radii. This means that for a significant fraction of time between the passages through the primary and the secondary shocks, the electrons have lower Lorentz factors than just behind the primary shock, and the magnetic field is also lower. The radiative losses are therefore relatively small (except for the period right after the passage of the primary shock). The electrons then spend a long time in a “freezer,” until the gas passes through the secondary shock (mini-accretion shock), when its density increases back to the initial state (at least approximately). The electrons’ Lorentz factor and the strength of the magnetic field increase accordingly. As a result, the synchrotron emissivity is boosted by a factor (e.g., Markevitch et al. 2005 ), where p is the slope of the relativistic electrons energy spectrum and C is the volume compression factor. In terms of the spectral index α = ( p − 1)∕2 in the radio band, the boost factor is . This expression is based on the assumption that the magnetic field is enhanced by a factor C 2∕3 . For the shock with M ~ 1.5, the compression is C ≈ 1.7. For α = 2, the corresponding boost of the radio flux purely due to adiabatic compression is F ≈ 10. Unlike the “runway” merger shock, the mini-accretion shock does not feature a rarefaction region downstream and, therefore, the radio emission is controlled by radiative losses. Once again the question arises of whether the short radiative times pose a problem. The distance over which the secondary shock front can travel during t max is l max ~ c s t max ≲ 180 kpc (for ν = 1.4 GHz), assuming that the shock moves with the sound speed 5 . At ν = 150 MHz, this distance will be ~500 kpc. This is smaller than the size (radius) of the radio halo of some 700 kpc (not by a huge factor, though), which used to be an argument against the single shock acceleration scenario. However, in the scenario, where secondary shocks are responsible for the compression and, possibly, reacceleration of electrons, this problem can be alleviated. The electron reacceleration scenario implies that there is a pool of nonthermal relativistic electrons produced by MHD shocks and turbulence due to the cluster merging history and fast moving galaxies in the cluster. Then the diffusive shock acceleration (DSA) mechanism would reproduce the slope of the pool electron spectrum in a shock downstream if the pool distribution had a power-law spectrum of index . Otherwise, the spectrum in the shock downstream would have the standard test particle DSA index if the slope of the pool distribution has a steeper spectrum (see e.g., Blandford et al. 1987 ). Therefore, the shock with M ~ 1.5, and the compression ratio C ≈ 1.7 propagatingin the cluster plasma regions without the prominent preexisting nonthermal population have p = 5.2 and the synchrotron radio emission index α = 2.1. On the other hand, energetic particle acceleration by intensive MHD turbulence and multiple shocks may
Paper: 2018MNRAS.479.2328O (fulltext)
targets since the spectroscopic target selection was mostly done in a colour–colour space. The well-established morphology–density relation (Dressler 1980 ; Postman et al. 2005 ) can be translated to a morphology–clustercentric radius relation (e.g. Whitmore, Gilmore Jones 1993 ; Goto et al. 2003 ). That is, early-type galaxies are more frequent in the cluster core while late-type galaxies are more frequent in the outer regions of clusters. Moreover, the morphology of galaxies is related with other physical properties such as their stellar masses, colours and SF rates. In this sense, the morphology of galaxies can also be inferred from their colours, for example: early-type galaxies tend to be red, whereas late-type galaxies tend to be blue. In this context, the relation between the morphology of galaxies and the environment can be explained by a colour–environment relation (Blanton et al. 2005 ; Skibba et al. 2009 ; Grützbauch et al. 2011a ). In the case of MACS0416 and MACS1206, the spectroscopic colour fractions as a function of projected distance from the cluster centre obtained in Section 4.6.1 (see left-hand panel of Fig. 5 ) show that galaxies in clusters and substructures follow a colour–clustercentric radius relation. Galaxies within , independent of whether they are part of a cluster or substructure, tend to be redder than galaxies beyond . This suggests that this result is likely a consequence of the effect of the cluster environment over the properties of galaxies traced by their colours (e.g. Miller 1986 ; Byrd Valtonen 1990 ; Boselli et al. 2014 ). Moreover, studying the colour fraction of galaxies as a function of the distance from the cluster or substructure centre (see right-hand panel of Fig. 5 ), we note that the total colour–clustercentric radius relation in substructures follows similar trends observed in the main clusters. According to this, substructures may be considered as down-scaled versions of clusters in which galaxy properties, traced by their colours, have been sculpted by the gravitational potential and physical processes within the substructures (e.g. ram-pressure stripping and galaxy–galaxy interactions), which can stop SF and turn galaxiesred. Fig. 6 shows the spectroscopic colour fractions as a function of projected distance by separating galaxies in all environments according to their stellar masses in massive () and less massive (). We note that fraction of green galaxies is constant in all environments, independent of the stellar mass of the galaxies and that massive galaxies tend to be red independent of the environment in which they are located. Besides, the fraction of red galaxies ( f r ) in clusters and substructures at is higher than the f r in the field, independent of the stellar mass. This result is in agreement with the result presented in the left-hand panel of Fig. 5 , in which the cluster environment models galaxy properties traced by their colours at least within . Beyond f r in
Paper: 2020MNRAS.494.5603G (fulltext)
evolution is computed by solving the rate equations with one Jacobi iteration with implicit Eulerian time discretization, with a coupling between thermal and chemical states at subcylces in the hydrodynamical time-step (see Bryan et al. 2014 , and references therein for more details). Table 1. Main parameters of the three runs in the Chronos++suite used in the present work. From the left- to right-hand columns define the presence of radiative cooling or star-forming particles, the critical gas number density n * to trigger star formation in the Kravtsov ( 2003 ) model, the time-scale for star formation t * , the thermal feedback efficiency, and the magnetic feedback efficiency ( ε SF and ε SF, b ) from star-forming regions; the efficiency of Bondi accretion α Bondi in the Kim et al. ( 2011 ) model for SMBH; the thermal feedback efficiency and the magnetic feedback efficiency ( ε BH and ε BH, b ) from SMBH; the intensity of the initial magnetic field, B 0 ; the presence of sub-grid dynamo amplification at run time; the ID of the run and some additional descriptive notes. All simulations evolved a volume using 1024 3 cells and DM particles, starting at redshift z = 38. The name convention of all runs is consistent with Vazza et al. ( 2017 ). Table 2. List of observable properties and adopted detection threshold. Note : We associate to each observable a reference instrument, which loosely corresponds to the adopted observational cut. All the runs adopted the Lambda cold dark matter (ΛCDM) cosmology, with density parameters Ω BM = 0.0478 (BM representing the Baryonic Matter), Ω DM = 0.2602 (DM being the dark matter), Ω Λ = 0.692 (Λ, being the cosmological constant), and a Hubble constant H 0 = 67.8 km s −1 Mpc −1 and σ 8 = 0.815 (Planck Collaboration XIII 2016 ). The initial redshift is z = 38, the spatial resolution is (comoving) and the constant mass resolution of for DM particles. Additional details on our sample of simulations can be found in Vazza et al. ( 2017 ) and Gheller Vazza ( 2019 ). An RGB rendering of the projected distribution of different mass components (DM, ionised gas, and neutral Hydrogen) in our CSFBH2 model at z = 0.045 is shown in Fig. 1 . This example shows, at least in a qualitative way, the general difficulty of detecting the diffuse gas in the cosmic via cross-correlation: although on large scales all tracers are well correlated and part of the same web pattern, on scales smaller than a few they present different level of clustering and concentration, making their cross-correlation signal challenging to detect. Figure 1. RGB rendering of the matter distribution in our simulated volume for the CSFBH2 model at z = 0.045: DM density (blue), ionized gas (pink), and neutral hydrogen (green). 2.2 Multiwavelength synthetic observations and halo catalogues We generated emission maps of our simulated volume at different wavelengths, including a number of emission/absorption channels: X-ray emission: we assume for simplicity a
Paper: 2016ApJ...833..205H (fulltext)
the uncertainties of the PFI-PE peak energies. We find that the PFI-PE energy resolution achieved in the present PFI-PE measurement is within the FWHM range of 1.5–2.0 cm −1 for the PFI-PE bands, indicating that these PFI-PE bands have minor perturbations by near resonance autoionizing Rydberg states. Table 1 Comparison of Ionization Energies (IEs) in cm −1 Obtained from the Present VUV–PFI–PE and VUV–PIE Rydberg Series Measurements and Those Calculated Using Known Spectroscopic and IE Data Notes. a Obtained from the present PFI-PE measurement. b Obtained from Page Gudeman ( 1990 ). c Calculated using known spectroscopic data and the IE value from the literature (see the text). d Obtained based on the present PIE Rydberg series measurement. The observed PFI-PE bands are also depicted in Figure 1 as the lower stick spectra. However, since the relative intensities of these PFI-PE peaks have not been measured carefully, we have arbitrarily set all four PFI-PE bands of the Co atom to have the same intensity. The ionization energy (IE) of the Co atom was previously determined to be 7.8810 eV (63,564.5 cm −1 ) by Page Gudeman ( 1990 ) by employing the double-resonance fluorescence-dip technique. The latter IE value is found to be in excellent agreement with the lowest PFI-PE peak at 63,564.0 ± 1.5 cm −1 observed in the present study. According to the NIST atomic database (Kramida et al. 2016 ), the four lowest spin–orbit levels of neutral Co are 4 F 9/2 , 4 F 7/2 , 4 F 5/2 , and 4 F 3/2 (in ascending order), and the four lowest spin–orbit levels of the Co + ion are 3 F 4 , 3 F 3 , 3 F 2 , and 5 F 5 (in ascending order). The energies of the 4 F 7/2 , 4 F 5/2 , and 4 F 3/2 excited levels of neutral Co measured with respect to the ground 4 F 9/2 state of Co have been reported to be 816.00, 1406.84, and 1809.33 cm −1 , respectively. The energies of the 3 F 3 , 3 F 2 , and 5 F 5 excited spin–orbit levels of Co + measured with respect to the ground 3 F 4 state of Co + have also been determined to be 950.51, 1597.32, and 3350.58 cm −1 , respectively. Thus, the IE of Co observed at 63,564.5 cm −1 can be assigned as the photoionization transition Co(3d 7 4s 2 4 F 9/2 ) Co + (3d 8 3 F 4 ). This IE[Co( 4 F 9/2 ) Co + ( 3 F 4 )] value, along with the known spacings of the spin–orbit states for Co and Co + , allows the calculation of the photoionization transition energies from the 4 F 9/2 , 4 F 7/2 , 4 F 5/2 , and 4 F 3/2 states of the Co atom to excited spin–orbit levels 3 F 3 , 3 F 2 , and 5 F 5 of the Co + ion. We found that such IE calculations predict IE[Co( 4 F 9/2 ) Co + ( 3 F 3 )] = 64,515 cm −1 for Co(3d 7 4s 2 4 F 9/2 ) Co + (3d 8 3 F 3 ), IE[Co( 4 F 9/2 ) Co + ( 5 F 5 )] = 66,915.1 cm −1 for Co(3d 7 4s 2 4 F 9/2 ) Co + (3d 7 4s 1 5 F 5 ), and IE[Co( 4 F 7/2 ) Co + ( 3 F 3 )] =63,699.0 cm −1 for Co(3d 7 4s 2 4 F 7/2 ) Co + (3d 8 3 F 3 ). These calculated IE values for the photoionization transitions are included in Table 1 to compare with the
Paper: 2018MNRAS.474.3889R (acknowledgments)
Acknowledgements MR and CD acknowledge funding from the European Research Council Starting Consolidator Grant (no. 307209). CD acknowledges support from an STFC Consolidated Grant (ST/L000768/1). We thank Anthony Challinor for helpful discussions and comments on a draft of the paper. We also thank Martin Bucher for useful discussions in the early stages of this work. We acknowledge the use of the psm package (Delabrouille et al. 2013 ), developed by the Planck working group on component separation, for making the simulations used in this work. Some of the results in this paper have been derived using the healpix package (Górski et al. 2005 ).
Paper: 2020MNRAS.492.3294M (acknowledgments)
ACKNOWLEDGEMENTS AKM would like to thank Council of Scientific and Industrial Research (CSIR) for financial support through research fellowship No. 524007. This research has made use of NASA’s Astrophysics Data System Bibliographic Services. We acknowledge the HPC@IISERM, used for some of the computations presented here. Authors thank Professor D Narasimha for useful discussions and comments. JSB thanks Professor Varun Sahni and Professor Sergei Shandarin for insightful discussions on singularities and caustics, and also for useful comments on the manuscript. Authors thank Richard Ellis, Prasenjit Saha and Liliya Williams for detailed comments on the manuscript. Authors also thank Ms Soniya Sharma who worked on some aspects of this problem for her MS thesis.
Paper: 2019A&A...624A..68M (fulltext)
of individual absorption lines such as their width and asymmetries, but with a heightened signal to noise. The CCF is binned in 0.5 km s −1 increments, owing to the R = 55 000 resolving power of the spectrograph. Two different spectral type masks were used: G2 and K5. These were chosen based on the spectral type of the primary star, which in our sample ranges between K2 and F0. Dumusque et al. (2012) demonstrated that the closeness of the spectral type mask largely affects only the absolute radial velocity and not the radial velocity variations. Only having two spectral type masks therefore does not hinder our analysis. The CCF of each measurement was compared with a Thorium-Argon spectrum, which was used as a wavelength-calibration reference ( Lovis Pepe 2007 ). This accounted for variations in the instrument which would otherwise impose a drift on the measured radial velocity of the star. The main source of variation was the pressure of the spectrograph, which followed the ambient atmospheric pressure because CORALIE, unlike HARPS and HARPS-North, is not pressurised. In 2014 a Fabry-Pérot unit was added to provide even more precise calibrations. 5.2 Outlier removal For each CCF, which is approximately Gaussian, we measure the span of the bisector slope. The bisector is calculated by tracing vertically the midpoint of the CCF at each value of flux intensity. The span of the bisector slope is the difference between the bisector at the top and bottom of the CCF ( Queloz et al. 2001b ). The bisector therefore reflects any asymmetries in the absorption lines. We remove any observations with bisector positions more than three interquartile ranges below the first quartile or above the third quartile. Such outliers may be from the wrong star being observed accidentally, or an abnormally low signal to noise observation. A visual inspection was also done of the data to outliers in the CCF’s Full Width Half Maximum (FWHM). 5.3 Calculation of radial velocity uncertainties In Table A.1 three different σ radial velocity uncertainties are listed. The first value, σ 1800s , is mean the photon noise uncertainty for all observations of 1800 s, which was the typical observation length during the BEBOP programme. The value σ median is the median photon noise precision for all observations, that is both the 1800 s observations taken for BEBOP and earlier, shorter observations taken in the EBLM programme. Fig. 4 Time-series of 1519 radial velocity observations of the 47 eclipsing binaries in the BEBOP programme. Red diamonds are observations for 1700 s or longer. Blue squares are for shorter observations. It is seen that all binaries typically receive two long observations initially before a series of short observations as part of the EBLM programme. A series of long observations typically commenced near the end of 2013 as part of the BEBOP survey. After removing observations with significant outlier bisector values there may still remain some
Paper: 2016MNRAS.459.4038S (fulltext)
in 1997 during which it also stayed in the LHS during the entire outburst (Revnivtsev et al. 2000 ; Brocksopp et al. 2001 ). During the 1997 outburst, a similar photon index was observed (Γ = 1.4–1.5; Revnivtsev et al. 2000 ). There are three even earlier detections of X-ray activity of transient sources that can be spatially related to GS 1354–64. During two of these detections the source was in the HSS, while the remaining one caught a source in the LHS (see Tanaka Lewin 1995 , and references therein). In case all observations are related to the same source, this source shows ‘normal’ outbursts with LHS and HSS and so-called ‘failed’ outbursts where it stays in the LHS during the entire outburst. A BHB that is known to show both types of outbursts is H1743−322 (Stiele Yu 2016 , and references therein). Unlike GS 1354–64, H1743−322 shows outbursts quite frequently. Another possibility is that only the ‘failed’ outbursts are related with GS 1354–64 and that the HSS are from a nearby transient source. About 10 X-ray binaries (including neutron stars and black holes) are known that have only been observed during outbursts where they stayed in the LHS (Capitanio et al. 2009 , and references therein). To be certain that GS 1354–64 belongs to the type of BHBs that show ‘normal’ outbursts, we would need to observe an HSS with a modern X-ray satellite that allows us to confirm that the thermal X-ray emission is spatially consistent with the position of GS 1354–64 obtained during the observation of the Comptonized emission during the 2015 outburst. The covariance ratio obtained from the XMM–Newton observation decreases with decreasing energy below 1 keV, while the one obtained for LHS observations of GX 339–4 and Swift J1753.5−0127 increases with decreasing energy (Wilkinson Uttley 2009 ; Stiele Yu 2015 ). The increase of the covariance ratio towards lower energies has been interpreted as a sign of additional disc variability on longer time-scales. Thus, the decrease observed in GS 1354–64 can be either regarded as a sign of missing disc variability on longer time-scales or as a sign of additional variability on short time-scales. For two observations of H1743−322 taken during the 2008 and 2014 ‘failed’ outbursts, we also found covariance ratios that do not show an increase at lower energies. In case of H1743−322, the covariance ratios remained rather flat (Stiele Yu 2016 ). In Stiele Yu ( 2015 ), we investigated the energy dependence of the characteristic frequency of the BLN in PDS and found that for a noise component with a characteristic frequency above 1 Hz the characteristic frequency in the 1–2 keV band is lower than in the 4–8 keV. From the XMM–Newton data of GS 1354–64, we obtain a characteristic frequency of Hz in the 1–2 keV band which is lower than the characteristic frequency of Hz in the 4–8 keV band, although this result is not significant as the errors are big. The sources investigated in Stiele Yu ( 2015 ) showed either an increase of
Paper: 2018ApJ...853...79C (acknowledgments)
We are grateful to Georges Meynet, who refereed this paper, for many constructive comments that helped us improve the paper. This work was supported by the Basic Science Research program (NRF-2016R1D1A1A09918398) through the National Research Foundation of Korea (NRF) and by the Korea Astronomy and Space Science Institute under the RD program (Project No. 3348-20160002) supervised by the Ministry of Science and ICT. S.C.Y. acknowledges the support by the Monash Center for Astrophysics via the distinguished visitor program.
Paper: 2019ApJ...887..130H (fulltext)
of the sigmoid (Figure 6 ). Unfortunately, restricted by the projection effect, we cannot determine the real height of the erupting structure and its evolution with time, but can only derive its projection distance from the source region as shown in Figure 6 (b) and the velocity component in the plane of sky in Figure 6 (a). Assuming that the eruption is along the radial direction, the linear velocity is corrected to be around 60 km s −1 . Figure 5. Time-slice plots of HMI line-of-sight magnetograms showing the emergence phase (a) and cancellation phase (c) of the bipolar region. The directions used for making the time-slice plots are indicated by the blue lines in the two magnetograms at 19:35 UT on 2017 January 28 (b) and 06:36 UT on 2017 January 30 (d). The slopes of the oblique lines represent the moving velocities of the positive and negative polarities. Figure 6. (a) Time-slice plot of AIA 211 Å images showing the eruption process. (b) The slice is taken along the direction to the northwest (the line in blue) as indicated in the AIA 211 Å image at 14:05 UT on 2017 January 30. The slope of the oblique line in panel (a) represents the moving velocity of the erupting structure along the plane of sky. 2.3. Thermal Property of Mini-sigmoid The observed flux of passband i can be written as , where the R i ( T ) is the temperature response function and DEM( T ) is the plasma DEM in the corona. Knowing the observed flux F i and response function R i ( T ), we resolve the DEMs of each pixel in the mini-sigmoid source region following the method in Cheng et al. ( 2012 ), using the “xrt_dem_iterative2.pro” routine in SSW package. The emission measure maps at the four temperatures are shown in Figure 7 . One can see that the temperature of the sigmoidal structure is around 2.0 × 10 6 K (Figures 7 (b4) and (c4)). It is interesting that, before the appearance of the sigmoid, two J-shaped structures that constitute an apparent sigmoid have a higher temperature of 2.5 × 10 6 K (Figure 7 (d3)). Such a difference in temperature between the double J-shaped loops and the S-shaped structure is in agreement with the expectation that the sigmoidal field lines, are formed by the reconnection between two sheared arcades near the PIL. With the J-shaped arcades being closer to the reconnection site, they tend to be heated up to a higher temperature. Shortly afterwards, these J-shaped arcades transform into the sigmoidal structures, which then cool down probably due to the expansion. This is basically consistent with the observations by Tripathi et al. ( 2009 ). Figure 7. Temporal evolution of the EM distributions of the sigmoid source region at the four temperatures intervals ranging from 80 to 250 MK. 3. Nonlinear Force-free Field Structures of Mini-sigmoid 3.1. Flux-rope Insertion Method Through the flux-rope insertion method (van Ballegooijen 2004 ; Bobra et al. 2008 ; Su et al. 2009 ), we further reconstruct the nonlinear force-free field structures of