adsabs/WIESP2022-NER huggingface dataset:
Paper: 2019A&A...627A..23E (fulltext)
that the main limitation of this approach is the fact that simulations may not fully reproduce all the cluster properties, and the absolute performance derived may therefore be taken with caution. However, we found it the most operational way to compare the relative performance of the different algorithms on a common ground. The full methodology currently developed to determine the selection function and the related mass proxy will be addressed in future work. The performance of the cluster finder algorithms has been tested and compared in a series of four Cluster Finder Challenges (CFC) between 2013 and 2017. The codes were tested on Euclid survey-like mock catalogs based on semianalytic models ( Merson et al. 2013 ; Gonzalez-Perez et al. 2014 ) and halo occupation modeling ( Carretero et al. 2015 ). The positions of the mock clusters were unknown to the participants of the challenges. Through the years, the mock catalogs were refined to better represent the properties of galaxies within clusters. In particular, photometric redshifts were assigned to galaxies in order to run the codes as they would be run in the Euclid context. In the first challenges, photometric redshifts were assigned following a simplistic Gaussian distribution, while in the later ones, photometric redshift codes were used. At the end of the third cluster finder challenge, the methodology and analysis pipeline were sufficiently mature for a first assessment of the relative performance of the different codes. While eight cluster finder codes in total were tested in the three preliminary challenges, only six of them took part in the final challenge described in this paper. In this article, we present the methodology used to assess the performance of the codes and the results obtained from the final cluster finder challenge. The detection codes were applied blindly to a realistic galaxy mock, built using PhotReal ( Ascaso et al. 2015 ) on the Euclid wide light-cone ( Merson et al. 2013 ), which was considered to be the best compromise available in terms of angular size (300 deg 2 ), depth ( z > 2.5), and realistic modeling of galaxy properties. We present the main assumptions and methodology of each of the competing codes and discuss the main properties of the simulated mock in the context of cluster detection. The code detections were matched to the true mock clusters and this information was used to evaluate the performance of the algorithms. Special care was given to the matching procedure by using several methods, allowing us to estimate the associated systematic uncertainties. In light of the mock properties, the performance comparison of the different algorithms participating in the challenge guided our selection of those now being validated and implemented in the Euclid pipeline. At this stage, we stress that the goal of this paper is not yet to compute a robust selection function and robust mass proxies, but instead, to compare the relative performance of different
Paper: 2018ApJ...867...51M (acknowledgments)
We thank an anonymous referee for her/his useful comments and suggestions. S.-P.M. and O.C. were supported by NASA Living with a Star grant no. NNX16AC11G. J.J.D. was supported by NASA contract NAS8-03060 to the Chandra X-ray Center. J.D.A.-G. was supported by Chandra grants AR4-15000X and GO5-16021X. C.G. was supported by Chandra grants GO7-18017X and GO5-16021X. Simulation results were obtained using the Space Weather Modeling Framework, developed by the Center for Space Environment Modeling, at the University of Michigan with funding support from NASA ESS, NASA ESTO-CT, NSF KDI, and DoD MURI. Simulations were performed on NASA’s PLEIADES supercomputer under award HEC-SMD-17-1190.
Paper: 2020ApJS..251...21M (fulltext)
the limit of weak viscosity and/or magnetic diffusivity is accessible. 5. Naturally all the renormalized coefficients are proportional to D 1 , which is the magnitude of the nonreflectionally symmetric component of the stirring force. It follows that the α -effect is impossible if the turbulence is not helical: . 6. Finally, an interesting observation was made, that in the strong MHD turbulence the energy spectra are substantially influenced by the helical component of the stirring force, whereas the helicity spectrum is determined by both the helical and nonhelical components of the forcing. All the nonlinear corrections to turbulent energy and helicity spectra are at leading order proportional to the energy of the mean magnetic field, which emphasizes its role in the MHD turbulence. A significant limitation of the presented analysis is that the turbulence, i.e., the stirring force, was assumed isotropic. This is a great simplification; however, the natural astrophysical and geophysical flows, in the majority of cases, possess at least one distinguished axis associated with the background rotation, which introduces anisotropy. Application of the renormalization group technique to rapidly rotating MHD flows, in order to obtain a more astrophysically realistic form of the mean EMF (the -tensor), is a subject of current research (see Mizerski 2020 ). Appendix The details of the renormalization procedure applied in order to obtain the mean field equations are given here. First of all, we clarify how the ensemble averaging should be understood and explain the concept of a conditional average over a statistical subensemble for short-wavelength modes. We adopt the approach of McComb et al. ( 1992 ; see also McComb Watt 1990 , 1992 ). The essential idea of this approach is the introduction of a subensemble of flow realizations including near-chaotic statistical properties for the short-wavelength shell , but remaining quasi-deterministic for . The subensemble average can be precisely defined and then, utilizing the assumption that in the turbulent cascade the energy transfer in the Fourier space is local, the following crucial properties can be proved: For details see particularly Section IV and the beginning of Section V in McComb et al. ( 1992 ). We now substitute the expressions for short-wavelength modes from Equations ( 65a ) and ( 65b ) into the conditional averages in the equations for long-wavelength modes in Equations ( 64a ) and ( 64b ). Neglecting higher-order correlations of the type , etc. (which eliminates the rests in Equations ( 65a ) and ( 65b )), and using , , and , one obtains The order of accuracy kept above, i.e., up to terms of the order with neglect of terms 7 7 Recall that this allows for neglect of the terms proportional to and in the rest ( 67b ). in particular, allows us to keep in the two last terms in the Lorentz force ( 127b ); anticipating the results, we may say that these terms account for the Lorentz force effect
Paper: 2019MNRAS.487.5118M (fulltext)
to match the observed LFs at redshifts z = 6 − 10. Although not shown in the present paper, we find that a roughly constant (; best-fitting value) ε * is needed for all the flat and non-flat models considered here (see fig. 2 of Paper I ). We can then get limits for f esc at different redshifts from equation ( 12 ) using the MCMC constraints already obtained on the evolution of N ion ( z ). Note that we take the value of N γ as ≈3200 which is appropriate for the PopII Salpeter IMF assumed here. The redshift evolution of f esc for different models is shown in Fig. 4 . The corresponding 2-σ uncertainties, indicated by shaded regions in the plot, have been computed using the quadrature method (Mitra et al. 2013 ). We find that the best-fitting f esc remains almost constant at for the whole redshift range in all the flat models ( l eft panel). On the other hand, a strong redshift evolution of this quantity is required for the non-flat models (right panel) – it can increase by a factor of ∼7 from redshift 6 to 10. Moreover, if we consider their 2-σ ranges, these non-flat models can lead to an impractically high f esc (≳1) at redshifts z ≳ 8. The sole reason behind such trends is that the values of N ion for non-flat models can become as high as ∼1000 around z ≈ 8 − 9, considering their 2-σ limits (see panel (a) of Fig. 3 ), in order to produce very high optical depths required for those models. On the other hand, the upper limits (2-σ) of escape fraction for the flat models having relatively lower τ el can become at most for all the redshift ranges considered here. Such one-to-one correspondence between strong redshift evolution of f esc ( z ) and higher reionization optical depths has also been reported earlier in many studies (see e.g. Haardt Madau 2012 ; Kuhlen Faucher-Giguère 2012 ; Mitra et al. 2013 ). Figure 4. Redshift evolution of the escape fraction f esc ( z ) along with its 2-σ errors for all the flat (left panel) and non-flat (right panel) models considered in this work. The red solid lines in both panels correspond to an escape fraction of unity. 4 CONCLUDING REMARKS We have presented detailed statistical analysis of reionization in tilted flat and untilted non-flat ΛCDM, XCDM and φCDM inflation models. The cosmological parameters for these models are constrained by Planck 2015 TT + lowP + lensing CMB anisotropy and SNIa, BAO, H ( z ), and growth rate data, using physically motivated inflation power spectra for energy density inhomogeneities (Park Ratra 2018a , c ). For the non-flat models, these data prefer mildly closed models with Ω k ∼ −0.006 to −0.008. Although such models provide better fits to the observed low-l temperature anisotropy C l ’s and weak-lensing σ 8 estimates, they provide worse fits to the observed higher-l temperature anisotropy C l ’s and primordial deuterium abundances (Penton et al. 2018 ). These closed models also predict relatively higher reionization optical depth values (τ el ≈ 0.11–0.12) compared to
Paper: 2017ApJ...839..131C (fulltext)
contain groups of background QSOs. The narrowband filter has an FWHM of 40 Å, corresponding to the radial separation of 42 cMpc. The survey volume of the 2622 groups is cMpc cMpc cMpc cMpc 3 . Thus, BOSS1441 can be regarded as the most extreme system selected from a ≈1.0 × 10 8 cMpc 3 survey volume using our selection technique. 3. Deep Imaging and Spectroscopy in the BOSS1441 Field After selecting the BOSS1441 field, we conducted deep narrowband and broadband imaging and multiple-slit spectroscopy to search for LAEs in this field. 3.1. KPNO-4 m/MOSAIC Narrowband + Broadband Imaging We used the MOSAIC1.1 camera (Sawyer et al. 2010 ) at the f /3.1 prime focus of the 4 m Mayall Telescope at the Kitt Peak National Observatory to conduct deep narrowband and broadband imaging. We obtained deep narrowband images with the NB403 narrowband filter. As shown in Section 2.2 , NB403 is used for probing the Ly α -emitting galaxies at . The BOSS1441 overdensity was observed on 2013 March, and 2014 April and June. The total exposure time is 17.9 hr, which consists of individual 15 or 20 minute exposures with a standard dither pattern to fill in the gaps between the eight chips. The seeing ranges from 11 to 17, with a median combined seeing of 132. We observed with the broadband filter (Bw) for 3 hr to match our selection criteria. These observing conditions enable us to achieve a narrowband magnitude at 5 σ using a circle aperture of 25 and a Bw -band magnitude m B = 25.9 at 5 σ using the same aperture. The narrowband sensitivity limit corresponds to a Ly α surface brightness of erg s −1 cm −2 arcsec −2 . 3.2. LBT Multiple-wavelength Broadband Imaging Our multiband imaging was conducted with the Large Binocular Cameras (LBC; Giallongo et al. 2008 ) at the Large Binocular Telescope (LBT) on Mount Graham in Arizona. LBC is characterized by a unique optical system. Each of the two mirrors has a collecting area of 8.4 × 8.4 m 2 and a field of view of 23′ × 23′. For a complete selection of star-forming galaxies at , we used the LBT to conduct deep multiple broadband observations in the U , V , and i filters (Steidel et al. 2005 ). Multiple broadband imaging can also eliminate the low-redshift [O ii ] interlopers that are the main contaminants of LAEs at z = 2.3. We use the standard z = 2 star-forming galaxy selection (BX selection) technique (Adelberger et al. 2005 ) to eliminate the low- z interlopers. The one-night LBT/LBC deep multicolor imaging was carried out in 2014 March. The LBC binocular mode was used, and the LBC blue channel was used solely for deep U -band observations. On the red side, we observed the same field in the V and i filters. We conducted 6 hr deep imaging in U , 2.5 hr in V , and 3.5 hr in i . The individual exposure was six minutes with a standard five-point dither pattern to fill in the CCD gaps. The conditions were partially cloudy, with a median seeing of 06. Our observations reached at 5 σ , at 5 σ , and at 5 σ . These depths are
Paper: 2018A&A...620A.104S (fulltext)
for NOAA AR 11591. whereby t is in days and t ∈ N is at noon. X 0 is the value we are interested in and will be henceforth called offset. It is used instead of a time average ⟨ X ( t )⟩ t because it correctly accounts for missing data (most importantly the gap in the afternoon of Oct 17) and that t start and t end have a different time of day. Here we have |⟨ X ( t )⟩ t − X 0 | 0.5 G for all X ( t ) in G and 0.01° for . While X 1 and X 2 are used internally during the fitting process to guarantee numeric stability, the results are presented with parameters X 0 , X 3 , and X 4 in Table 2 . X 3 and X 4 are the amplitude and phase of the orbital artefacts. Also listed are the standard deviations of the residuals σ t = σ ( X ( t )− X fit ( t )) and the means of the standard deviations along the contours over the same range in time ⟨ σ ψ ⟩ t . Table 2. Results: fit parameters and time averages. Notes. ( a ) Excluding five snapshots due to faulty 180°-disambiguation: t = 10.22.{12 : 14, 12 : 36, 13 : 36, 14 : 00, 14 : 12}. Levels of magnetic contours. The offsets X 0 from the fits to , and for the 0.5(0.4) I qs contours are then used as contour level on the B ver , | B | and γ LRF maps, respectively. They are discussed in Sect. 3.2 and plotted in Figs. 3 and 5 and the videos. Distance between contours. To quantify how well two contours match we calculated the average distance between them ⟨ d ⟩ ψ , which we define as the area of symmetric difference divided by the length of the intensity contour, l( t ). The area of symmetric difference, Δ a ( t ), is the area surrounded by either of the contours but not both. When averaging in time we weighed by the contour length, giving These average distances between contours are listed in Table 2 in pixel. For ⟨ d ⟩ ψ ≪ 1pixel only the total ordering should be relied upon due to griding and other computational effects. Fit along each contour. For every point along a contour, a reference angle ψ = ∡(PCD) is calculated, whereby P is the point on the contour, C is the centroid of the I c = 0.5 I qs contour in the CCD frame and D is the centre of the solar disc as observed by SDO. The angles are calculated on the sphere. For every time step and every contour, is least square fitted against functions of the form Those fits are plotted in the right panels of the videos (cf. Sect. 3.2 and bottom panels of Figs. 3 and 5 ). Furthermore the time averages of the fit amplitudes are listed in Table 2 . Optimal height difference. Δ h = 465 km was chosen because it minimizes the average distance ⟨ d ⟩ ψ , t between the I c = 0.5 I qs contours after transformation with Eq. ( 1 ) and the B ver contours, whereby the contour level X 0 on the B ver map has been derived with the fit to ⟨ B ver ⟩ ψ ( t ) as described above (Eq. ( 2 )). An optimal height difference of Δ h = 465 km means that the intensity contour at the limb is shifted outwards by 465 km ⋅ r ⊙ / R ⊙ ≈ 0.65′′ ≈ 1.3 pixel. The difference of the formation heights for
Paper: 2017A&A...601A...3W (fulltext)
in the closure phases across these spectral channels at 200 cycles/arcsec (cf. Sect. 4.3 , Fig. 6). However, we cannot currently exclude an uncertainty of the position of the dominant spot of this order in the imaging process. 4.5. Fundamental parameters of R Scl Table 5 Fundamental properties of R Scl used in this work. Notes. 1: Discussion in Sect. 2.1 ; 2: Whitelock et al. (2008) ; 3: integrated photometry, see Sect. 2.1 ; 4: this work, average of our three epochs, see Sect. 4 ; 5: calculated from 2 and 4; 6: calculated from 3 and 4; 7: calculated from 2 and 3; 8: 7 and 8 with evolutionary tracks by Lagarde et al. (2012) ; 9: 6 and 9. Fig. 11 Position of R Scl in the HR diagram together with evolutionary tracks by Lagarde et al. (2012) . The tracks are those without rotation and reach up to the start of the TP-AGB. Masses are ZAMS masses; values in parenthesis are masses at the start of the TP-AGB, that is, at the end of the shown tracks. Table 5 summarizes the fundamental parameters of R Scl that we used in this work, including our adopted values for the bolometric flux and distance, the measured Rosseland angular diameter, and the derived effective temperature and luminosity. We note that the distance to R Scl is quite uncertain, as discussed in Sect. 2.1 , which is reflected in its large adopted error. Figure 11 shows the position of R Scl in the Hertzsprung-Russell (HR) diagram based on the effective temperature and luminosity. This figure includes stellar evolutionary tracks by Lagarde et al. (2012) for zero age main sequence (ZAMS; initial) masses between 1 and 2.5 . These tracks reach up to the start of the thermally pulsing (TP) AGB, at which point the mass range is 0.7 to 2.5 . The position of R Scl is consistent with an evolutionary phase shortly beyond the start of the TP-AGB and with an initial mass interval between 1 and 2 . We also compared the position of R Scl to the tracks of the TP-AGB by Marigo et al. (2013) as shown by Klotz et al. (2013) . Here, R Scl is also consistent with masses at the start of the TP-AGB between about 1 and 2 , that is, not significantly below 1 and not significantly above 2 . These are evolutionary tracks for single stars, while a binary companion has been detected for R Scl. However, based on the estimates for the binary companion mass and separation ( Maercker et al. 2016 ), it is unlikely that the companion has affected the evolution of R Scl to the AGB. As a result, we estimate the initial mass of R Scl to be 1.5 0.5 and the current mass to be 1.3 0.6 . Together with our estimate of the radius, these values correspond to a surface gravity of –0.6 0.4. The mass of R Scl can also be estimated by the pulsation properties. We used the formula from Wood (1990) , where is the pulsation constant, and and are the mass and radius in solar units. We estimated a value of 0.093 0.005 for the given ranges of masses and pulsation periods based on Fox Wood (1982) and assuming fundamental pulsation
Paper: 2016A&A...592A..11K (acknowledgments)
We would like to thank the anonymous referee for the useful comments and suggestions. XXL is an international project based around an XMM Very Large Programme surveying two 25 deg extragalactic fields at a depth of erg s cm in [0.5−2] keV at the 90% completeness level (see Paper I). The XXL website is http://irfu.cea.fr/xxl . Multiband information and spectroscopic follow-up of the X-ray sources are obtained through a number of survey programmes, summarised at http://xxlmultiwave.pbworks.com/ . The authors acknowledge L. Chiappetti for producing a format and catalog compliance report. EK acknowledges fellowship funding provided by the Greek General Secretariat of Research and Technology in the framework of the programme Support of Postdoctoral Researchers, PE-1145. E.K. acknowledges the Centre National d’Études Spatiales (CNES) and CNRS for support of post-doctoral research. Y.J. and the Marie Curie Actions of the European Commission (FP7-COFUND) acknowledges support by FONDECYT grant N. 3130476. O.M. is grateful for the financial support provided by the NEWFELPRO fellowship project in Croatia. F.P. acknowledges support from the BMBF/DLR grant 50 OR 1117, the DFG grant RE 1462-6 and the DFG Transregio Programme TR33. This work is based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/IRFU, at the Canada-France-Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l’Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is based in part on data products produced at Terapix available at the Canadian Astronomy Data Centre as part of the Canada-France-Hawaii Telescope Legacy Survey, a collaborative project of NRC and CNRS.
Paper: 2020MNRAS.491.1427S (acknowledgments)
ACKNOWLEDGEMENTS Based on data obtained at the W.M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and NASA, and was made possible by the generous financial support of the W.M. Keck Foundation. We acknowledge support from NSF AAG grants AST-1312780, 1312547, 1312764, and 1313171, archival grant AR-13907 provided by NASA through the Space Telescope Science Institute, and grant NNX16AF54G from the NASA ADAP program. We also acknowledge a NASA contract supporting the ‘WFIRST Extragalactic Potential Observations (EXPO) Science Investigation Team’ (15-WFIRST15-0004), administered by GSFC. We additionally acknowledge the 3D-HST collaboration for providing spectroscopic and photometric catalogues used in the MOSDEF survey. We wish to extend special thanks to those of Hawaiian ancestry on whose sacred mountain we are privileged to be guests. Without their generous hospitality, the work presented herein would not have been possible.