adsabs/WIESP2022-NER huggingface dataset:
Paper: 2020ApJ...900..159G (fulltext)
photons using 30′′ and 18 radius circular apertures, respectively. Table 1 Log of X-Ray Timing Observations of 1E 1207.4−5209 Notes. a Exposure times for XMM-Newton EPIC-pn does not reflect the 29% deadtime in the SmallWindow (sw) mode. b Newly reported observations. The NICER data sets are denoted by the ObsID and date of the first of the concatenated set of observations (see Section 2 for details). Table 2 Single Glitch Ephemerides for 1E 1207.4−5209 Notes. Derived parameters ( B s , , τ c ) are based on the pre-glitch timing solution. a Uncertainties in the last digits are given in parentheses. b Epoch of the glitch estimated by matching the zero phase of the two timing solutions; this assumes a constant post-glitch . The NICER (Gendreau Arzoumanian 2017 ) is an X-ray telescope attached to the International Space Station that provides submicrosecond time resolution in the 0.2–12 keV band. The NICER telescope consists of a set of 52 operational non-imaging silicon drift detectors (Prigozhin et al. 2016 ), each at the focus of an X-ray concentrator (Okajima et al. 2016 ) that subtends a 4′ radius field of view. The nominal effective area of the telescope is 1900 cm 2 at 1.5 keV. The NICER data sets were reduced and analyzed using the NICERDAD software suite distributed in the FTOOLS package, version 24Jun2019_V6.26.1, and the most up-to-date calibration files. We generated cleaned event files using the nicerl2 script that applied the standard filtering criteria. The data were further reduced by excluding detectors with anomalous count rates >5 σ above the mean rate, computed using all available detectors, in the energy range of interest. Similarly, we iteratively excluded time intervals with high background rates by comparing the event rate in 10 s steps to the mean rate. Since its launch in 2017, NICER has observed 1E 1207.4−5209 a total of 148 times to-date. Each observation is defined by a unique ObsID number and typically comprises short exposures (50% are less than 1.2 ks) spread over multiple satellite orbits, and often containing multi-day gaps within, and between. These exposures are generally too short to generate a precise pulse-phase measurement needed for our timing analysis. However, by concatenating adjacent observations we obtained eight sufficiently compact NICER data sets that contained the minimum number of events required to measure an independent pulse phase, as described below. 3. Timing Analysis For each reprocessed, cleaned event file, we folded the extracted photon arrival times on the pulsar frequency to compute the time-of-arrival (ToA) of phase zero of the pulse. To attempt a phase-connected timing solution, we fit the set of ToAs using the TEMPO software (Hobbs et al. 2006 ) to a model for the rotation phase of the pulsar including one or two of its frequency derivatives,Initially, we obtained the fold frequency from a periodogram search for the maximum power around the expected frequency, determined from the
Paper: 2021MNRAS.504.2360J (fulltext)
CO is determined from the CO (2 − 1) emission by assuming a luminosity ratio of and α CO . Using the and 3σ for non-detections from table 6 in Boogaard et al. ( 2020 ), we estimate the α [C i ](1 − 0) with both molecular gas masses, and present in Table 6 and Fig. 8 with the coloured diamonds. Figure 8. α [C i ](1 − 0) as a function of metallicity. The black and red symbols represent each detections and 0.1 bin values for our sample. The blue boxes represent samples of high-redshift ( z = 1.9−3.4) gamma-ray burst and quasar molecular gas absorbers from Heintz Watson ( 2020 ) with , and the black line shows their best-fitting linear relation of logα [C i ](1 − 0) = −1.13 × log(Z/Z ⊙ ) + 1.33. The orange and green diamonds are ASPECS galaxies from Boogaard et al. ( 2020 ) with molecular gas masses estimated based on CO luminosity and 1.2 mm dust-continuum emission on the Rayleigh–Jeans tail, respectively. Table 6. The adopted redshift, molecular gas mass, [C i ] (1 − 0) luminosity, metallicity, and derived α [C i ](1 − 0) for the ASPECS galaxy. Note . Columns (1)–(5) are adopted from Boogaard et al. ( 2020 ). (1) and (2) are ASPECS ID and redshift, respectively. Column (3) is molecular gas mass that estimates via the 1.2 mm dust-continuum emission on the Rayleigh–Jeans tail, and (4) is the molecular gas mass determined from the CO (2 − 1) emission assuming a luminosity ratio of and α CO (see table 5 in Boogaard et al. 2020 ). Both of the molecular gas masses from Boogaard et al. ( 2020 ) include a factor of 1.36 to account for heavy elements. Column (5) lists the with 3σ for the non-detections (see table 6 in Boogaard et al. 2020 ). The α [C i ](1 − 0) in columns (6) and (7) are estimated based on molecular gas masses of M mol, RJ and M mol, CO , respectively. The metallicity in column (8) is adopted from Boogaard et al. ( 2019 ). Though our derived α [C i ](1 − 0) shows almost flat with metallicity, they distribute next to the relation of Heintz Watson ( 2020 ) as seen in Fig. 8 , and similar with the α [C i ](1 − 0) result of ASPECS galaxies as well [the α [C i ](1 − 0) values in both Heintz Watson 2020 and Boogaard et al. 2020 include a factor of 1.36 to correct the helium and heavier elements]. The metallicity in our sample mainly focuses in the range of , whereas the metallicity of the sample in Heintz Watson ( 2020 ) covers two orders of magnitude in the ranges of , which is mostly smaller than our sample. Various studies suggest that α CO increases with decreasing metallicity, turning up sharply below metallicity of (Wolfire, Hollenbach McKee 2010 ; Bolatto, Wolfire Leroy 2013 ) where CO is easily photodissociated, whereas H 2 is self-shields or is shielded by dust from UV photodissociation, and becoming shallower near subsolar metallicity (Glover Mac 2011 ; Tacconi et al. 2018 ). The flat profile between α [C i ](1 − 0) with metallicity in our sample presents that α [C i ](1 − 0) might be similar to α CO and has a fairly shallow
Paper: 2017MNRAS.467.1067D (acknowledgments)
Acknowledgments This research was supported by the DFG cluster of excellence Origin and Structure of the Universe (JED).
Paper: 2017MNRAS.469.4437C (fulltext)
as [see equation ( 1 )], but at the same time the additional power would increase AGN feedback, which is proportional to the luminosity. If we instead increase the BH feedback efficiency, i.e. the constant of proportionality with luminosity, the gas surrounding the BH is less cold and dense, causing BH accretion to decrease. To quantify these effects on the dual-activity observability time-scales, we compare Runs 02, C3 and C4, which differ only by the initial BH mass or feedback efficiency. Increasing the BH mass (by a factor of 2.5) increases the dual-activity time, but only by a factor ≲2. Increasing the BH feedback efficiency (by a factor of 5) tends to decrease the normalized dual-activity time, although the factor widely depends on the filter one chooses (see Fig. B8 for more details). We note that different prescriptions for BH accretion (e.g. taking into account the angular momentum of the accreting gas; Debuhr et al. 2010 ; Hopkins Quataert 2011 ; Anglés-Alcázar, Özel Davé 2013 ; Anglés-Alcázar et al. 2015 , 2017 ) or AGN feedback (e.g. Newton Kay 2013 ; Wurster Thacker 2013 ) may also affect the results. 4.4 Comparison with other work In this section, we compare our dual-activity time-scales to a few select studies, both observational and theoretical, to validate our results. 4.4.1 Comparison with observations Most surveys provide the total number of AGN pairs out of the total number of AGN (e.g. Shen et al. 2011 ). These results are difficult to compare to ours since, by construction, we do not simulate isolated galaxies that could be harbouring a single AGN. Koss et al. ( 2012 ) study the fraction of dual AGN in the all-sky Swift Burst Alert Telescope (BAT) survey. For each of the 167 BAT AGN from the survey, they search for apparent companions, finding that 77 of them have at least a companion 8 within 1–100 kpc. Of these 77 companions, 15 have an AGN, making the fraction of dual AGN systems out of interacting systems (in which at least one system has an AGN) equal to 19.5 per cent (15/77). If we divide their sample in major and minor pairs (defined as pairs with mass ratios > and ≤0.25, respectively), the fraction changes to 37.1 per cent (13/35) for the major pairs and to 4.8 per cent (2/42) for the minor pairs. Since in this case only interacting systems are considered, we can compare the numbers from Koss et al. ( 2012 ) to our results. To do that, we simply consider, for each of our mergers, the dual-activity time when the BHs are at r > 1 kpc (our galaxies, by construction, are never above r ∼ 90 kpc) and divide it by the activity time at the same projected separations. 9 In Fig. 7 , we show the normalized dual-activity time above 1 kpc, 10 kpc and 150 km s −1 , for all our simulated mergers. We also show the results of Koss et al. ( 2012 ) for their full sample of BAT AGN and their subsamples of major and minor pairs. If we neglect the 1:2 merger with high BH feedback efficiency (Run C3), which obviously has a much lower
Paper: 2017MNRAS.464.1127R (acknowledgments)
This work was supported by the Research Projects of the Polish Ministry of Sciences and Higher Education: 04/45/DSPB/0148 (JR and JD) and 06/65/DSPB/0516 (ME).
Paper: 2019ApJ...875..132Z (acknowledgments)
We thank Marc Metchnik and Philip Pinto for their contributions to the A bacus simulation code. D.J.E., L.H.G., and D.W.F. have been supported by grant AST-1313285 from the National Science Foundation, and D.J.E. is additionally supported as a Simons Foundation Investigator.
Paper: 2017MNRAS.470..713M (fulltext)
70–600 keV). Therefore, the observation covers a wide energy band simultaneously and with high sensitivity making it possible to do detailed spectroscopic studies of the source. The data were reduced and processed with the standard procedures and using the latest caldb version ’20140825’. The XIS was operated in the standard data mode with the window mode that provided a timing resolution of 2 s. The nominal pointing was set to XIS. The XIS data was examined for the presence of pile-up. A central region corresponding to a pile-up fraction >4 per cent was discarded from all further analysis. 3 TIMING ANALYSIS: PULSATION SEARCH AND LIGHT CURVES We applied barycentric corrections to the event files for the timing analysis, using the FTOOLS task ‘aebarycen’. Orbital correction was not required as the observation duration is much less than the decoherence time-scale due to the orbital motion of the system (Chakrabarty et al. 1997 , decoherence time-scale is ∼54 d, equation A9). Light curves were extracted with a time resolution of 2 s and 1 s, respectively, from the XISs (0.2–12 keV) and HXD/PIN (10–70 keV). To search for pulsations in the data, pulse folding and χ 2 maximization technique was applied. Pulsations were found in the light curve at 835.29 ± 0.29 s, which was subsequently used to bin the light curves and also to create corresponding pulse profiles. Fig. 1 shows the light curves in the low (XIS: 0.2–12 keV) and high (PIN: 10–70 keV) energy bands along with the hardness ratio (HR) curve, all binned at the spin period of the source. The ‘HR’ is defined as the ratio of the count rate in the XIS band (with the three XISs added together) to the PIN band. It is clear from the figure that the count rates in both the energy bands vary by a factor up to 5 during the observation. Moreover the HR shows a variation by a similar factor with the PIN count rate (see right of Fig. 1 ) that indicates spectral variability in the source. In order to investigate the true energy dependence of the pulse profiles in this source and to construct an average model of the representative X-ray spectrum of the source, it is important to choose a time interval free from intensity or spectral variations. Therefore, in order to construct the pulse profiles and the energy spectrum of X Persei, we choose a stretch of the observation where 0.02 HR 0.03 and 0.8 PINc/s 1.4, as not much spectral variation is expected in this narrow stretch. Figure 1. Left figure shows the light curves in low- and high-energy bands with the lowest panel showing the HR. The light curves are binned at the spin period of 835.29 s. Right figure shows the HR plotted against the PIN count rate to highlight the variation in HR with the count rate in the high-energy band. 3.1 Energy dependence of the pulse profiles To investigate any possible energy dependence of the pulse profiles, we created the energy resolved pulse profiles by folding the data in different energy bands at the obtained pulse
Paper: 2019A&A...623A.105G (fulltext)
centred at , . Small-diameter (7′) WISE H II regions from Anderson et al. (2014) are marked by white squares and two extended WISE H II regions (diameter > 20′) are indicated by blue dashed circles. Three very extended radio sources in both λ 21 cm and λ 6 cm images are SNR G126.2+1.6, SNR G127.1+0.5 and H II region G127.9+1.7 (DU 65, Dubout-Crillon 1976 , red rectangle), which is missing in the WISE H II region catalogue. Lower left panel : its H α emission is shown overlaid by the λ 6 cm total-intensity emission. Lower middle and lower right panels : TT-plot results for DU 65 by using the Urumqi λ 6 cm against the Effelsberg λ 21 cm data and the Effelsberg λ 11 cm data. 4.1.1. New H II regions In addition to the missing known extended H II regions in the WISE H II region catalogue, a few new Galactic H II regions and H II region candidates are also discovered in the Urumqi λ 6 cm survey. They are G68.4+0.2, G76.7−1.2, G94.4+2.7, G139.2−3.0, G139.9−2.0, G172.3+1.9 (H II region candidate), G186.7−4.0 (H II region candidate), G210.8−2.6 and G212.9−3.7. We show them in Figs. 4 , 5 and 6 . For G68.4+0.2, G76.7−1.2 and G94.4+2.7 it is difficult to compare the λ 6 cm radio emission with the WISE 12 μ m infrared emission due to the large difference in angular resolution. We extracted the 1′ resolution CGPS λ 21 cm images and found that the associated infrared emission are not for the entire radio source but for partial shell- or ridge-like structures. The TT-plots confirmed their thermal origin. For the six remaining newly identified H II regions and H II region candidates, we found supporting evidence both in the TT-plot results and the associated H α emission, except for G172.3+1.9 and G186.7−4.0. For G172.3+1.9, we did not obtain a reliable TT-plot result and for G186.7−4.0, which is not fully covered by the Effelsberg λ 21 cm survey, the sensitivity of the Effelsberg λ 11 cm data is not enough for a clear determination. The H α image quality is not high in the south-east part of G172.3+1.9, but the data show a good correlation in the north-west part. Fig. 4. New H II regions G68.4+0.2, G76.7−1.2 and G94.4+2.7 identified in the Sino-German λ 6 cm survey. We show λ 6 cm images and WISE 12 μ m emission overlaid by CGPS λ 21 cm total intensity in the upper and middle panels . We present their TT-plot results in the lower panels . Fig. 5. Newly identified H II regions G139.2−3.0, G139.9−2.0 and G172.3+1.9. H α emission overlaid by Urumqi λ 6 cm total intensity contours are shown in the upper panel . The image quality of the south-east part of G172.3+1.9 is not good; however, correlation can be clearly recognised in the north-west part. TT-plot results are displayed in the lower panels . Fig. 6. Upper panels from left to right : λ 6 cm image, H α emission overlaid by Effelsberg λ 11 cm total intensity and the TT-plot result for the new H II region G212.9−3.7. Lower panels from left to middle : H α emission overlaid by Urumqi λ 6 cm total intensity
Paper: 2016MNRAS.459..880M (acknowledgments)
We thank the referee for the careful reading of the manuscript. This research is partially supported by the Spanish Ministerio de Ciencia e Innovación (MICINN) under grants AYA2012-39364-C02-02 and AYA2015-68012-C2-2-P, and by the Generalitat Valenciana (ACOMP/2014/129). AM acknowledges support from the Generalitat Valenciana through the grant BEST/2015/242 and from the Ministerio de Educación, Cultura y Deporte through the grant PRX15/00030. This work is based in part on the observations obtained with the Jacobus Kapteyn Telescope operated on the island of La Palma by the Isaac Newton Group, in the Spanish Observatorio Roque de los Muchachos of the Instituto de Astrofísica de Canarias. This work is based in part on the observations made with the Italian Telescopio Nazionale Galileo (TNG) operated on the island of La Palma by the Fundación Galileo Galilei of the INAF (Istituto Nazionale di Astrofisica) at the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias. This research is also based on the observations made with the Nordic Optical Telescope, operated on the island of La Palma jointly by Denmark, Finland, Iceland, Norway and Sweden, in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias. Some of the data presented here have been taken using ALFOSC, which is owned by the Instituto de Astrofisica de Andalucia (IAA) and operated at the Nordic Optical Telescope under agreement between IAA and the NBIfAFG of the Astronomical Observatory of Copenhagen. This work is based in part on the observations made at Observatoire de Haute Provence (CNRS), France. This research has made use of the SIMBAD data base, operated at CDS, Strasbourg (France) and of the WEBDA data base, operated at the Institute for Astronomy of the University of Vienna. This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation.
Paper: 2018A&A...609A..47P (acknowledgments)
We thank T. J. Haworth, J. Lesur and C. McNally for the useful discussions. This paper makes use of the following ALMA data: ADS/JAO.ALMA#2013.1.00798.S. ALMA is a partnership of ESO (representing its member states), NSF (USA), and NINS (Japan), together with NRC (Canada), NSC and ASIAA (Taiwan), and KASI (Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, AUI/NRAO, and NAOJ. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc. We acknowledge funding from ANR of France under contract number ANR-16-CE31-0013, from the Australian Research Council (ARC) under the Future Fellowship number FT170100040, from the National Centre for Competence in Research PlanetS supported by the Swiss National Science Foundation, and from the European Union Seventh Framework Programme FP7-2011 under grant agreement No. 284405.
Paper: 2019ApJ...884L..34P (fulltext)
so its disruption radius is closer to the BH (see Equation ( 5 )). The longer t acc in XT2 is likely due to a lower disk thickness ratio H / R because the latter carries the most sensitive parameter dependence in Equation ( 6 ). A lower H / R in turn might be caused by a lower Eddington-normalized accretion rate. This could suggest that XT2 was a tidal stripping event because the total bound mass Δ m can be much smaller than that of a full disruption event. The isotropic-equivalent peak luminosity of CDF-S XT2, ≈3 × 10 45 erg s −1 , is extremely high, which raises the possibility of a relativistically beamed emission. Three relativistic jetted TDE candidates have been discovered so far: Sw J1644+57 (Bloom et al. 2011 ; Burrows et al. 2011 ), Sw J2058+0516 (Cenko et al. 2012 ; Pasham et al. 2015 ), and Sw J1112−8238 (Brown et al. 2015 ). The 2D model of Dai et al. ( 2018 ) suggests that the X-ray emission of TDEs may be caused by jets through the Blandfold–Znajek process. Similarly, the WD–IMBH tidal disruption/stripping discussed here may produce a jet as well. Xue et al. ( 2019 ) estimated the CDF-S XT2–like event rate density to be Gpc −3 yr −1 . For CDF-S XT1, Bauer et al. ( 2017 ) estimated a large range of the event rate, ∼10 3 Gpc −3 yr −1 for z = 0.5 to ∼1 Gpc −3 yr −1 for z = 3. Theoretically, the rates of WD disruptions are very uncertain. For IMBHs in globular clusters (GCs), Baumgardt et al. ( 2004 ) estimated a total stellar TDE rate of ∼10 −7 yr −1 via N -body simulations of GCs with an initial central BH mass of 10 3 M ⊙ . Among the disrupted stars, ∼15% are WDs, giving a rate of ∼1.5 × 10 −8 yr −1 . Adopting a number density of 34 Mpc −3 of GCs, this gives a volumetric rate of R IMBH−WD ∼ 500 yr −1 Gpc −3 (Haas et al. 2012 ; Shcherbakov et al. 2013 ). Recently, Fragione et al. ( 2018 ) semianalytically calculated the evolution of a population of GCs in a galaxy and found a rate of WD TDE ∼10 −5 yr −1 per galaxy; combining this with GC population’s dependence on redshift and galaxy types, their results show a present-day volumetric rate of R IMBH−WD ∼ 10 yr −1 Gpc −3 . For IMBHs in dwarf galaxies, MacLeod et al. ( 2014 ) calculated a rate of ∼10 −6 yr −1 per IMBH for WD disruptions via the loss-cone dynamics for the BH mass range of 10 4 –10 5 M ⊙ . This rate is ∼30 times lower than that of main-sequence stellar TDEs by supermassive black holes (e.g., Stone Metzger 2016 ). Assuming a number density of dwarf galaxies ∼10 7 Gpc −3 (Shcherbakov et al. 2013 ; MacLeod et al. 2014 ) and an occupation fraction f IMBH of IMBHs in dwarf galaxies, then the volumetric rate is yr −1 Gpc −3 . Compared with WD–IMBH TDEs, a similar case that happens more commonly is the tidal disruption/stripping of MS stars by IMBHs. Indeed, as was shown in Fragione et al. ( 2018 ), the event rate of MS–IMBH TDEs is about 30 times higher than that of WD–IMBH TDEs in most galaxies. However, the timescale (∼years) of MS–IMBH TDEs is much longer than that of
Paper: 2016ApJ...826...65G (acknowledgments)
This research was supported by NASA grants NNX13AF99G, NNX10AE46G, and NNX12AH44G, and by NSF grant AGS-0955700. X.G. was also supported by the 973 program 2012CB825602, NNSFC grant 41231067, and in part by the Specialized Research Fund for State Key Laboratories of China. We are grateful for the use of the Neutron Monitor Database at http://www.nmdb.eu , the Wilcox Solar Observatory, and the OMNI data obtained through the GSFC/SPDF OMNIWeb interface at http://omniweb.gsfc.nasa.gov .
Paper: 2017ApJ...841...42X (acknowledgments)
We thank the anonymous referee very much for a careful reading of the manuscript and constructive comments. The authors thank Professor Ke-Jun Li for his constructive ideas and helpful suggestions on the manuscript. This work utilizes the radio flux data obtained through the Solar Radio Monitoring Programme, managed by the Dominion Radio Astrophysical Observatory, Penticton, British Columbia, Canada. The data used here were downloaded from the web site of NOAA and the authors express their deep thanks to the staff of the web site. The wavelet software was provided by C. Torrence and G. Compo. It is available at: http://paos.colorado.edu/research/wavelets/ . This work is funded by the National Natural Science Foundation of China (11573065, 11673061, and 11633008), the Applied Basic Research Foundation of Yunnan Province, China (Grant No. 2014FB190), the Collaborating Research Program of CAS Key Laboratory of Solar Activity (KLSA201613), the Specialized Research Fund for State Key Laboratories, Center for Astronomical Mega-Science, and the Chinese Academy of Sciences.