adsabs/AstroCLIMB huggingface dataset:
Paper: Implications from the Velocity Profile of the M87 Jet: A Possibility of a Slowly Rotating Black Hole Magnetosphere
Authors: Motoki Kino, Masaaki Takahashi, Tomohisa Kawashima, Jongho Park, Kazuhiro Hada, Hyunwook Ro, Yuzhu Cui, 玉竹 崔
Figure caption: Estimate of the magnetic field strength threading the event horizon. The horizontal axis shows the ratio Ω F /Ω H , where Ω F  is constrained as Equation (27). The estimate here is simply derived by equating L BZ (Appendix B) to the total jet power in M87 suggested as 1 × 1042 erg s−1 ≲ L j ≲ 1 × 1044 erg s−1. The color bar shows the corresponding L BZ.
Paper: X-Ray and GeV-γ-Ray Emission Property of TeV Compact Symmetric Object PKS 1413+135 and Implication for Episodic Jet Activity
Authors: Ying-Ying Gan, Jin Zhang, Su Yao, Hai-Ming Zhang, Yun-Feng Liang, En-Wei Liang
Figure caption: Correlation of the flux between γ-rays and X-rays of PKS 1413+135. The solid line represents F 2–10 keV = F 0.1−300 GeV/100. The data are taken from Figure 1.
Paper: New Identifications and Multiwavelength Properties of Extragalactic Fermi Gamma-Ray Sources in the SPT-SZ Survey Field
Authors: Lizhong Zhang, 力中 张, Joaquin D. Vieira, Marco Ajello, Matthew A. Malkan, Melanie A. Archipley, Joseph Capota, Allen Foster, Greg Madejski
Figure caption: The flux−flux plot showing the radio flux density at 843 MHz from the SUMSS survey vs. the SPT flux density at 2 mm (150 GHz) for all SPT-selected sources. The gray dots represent all the mm sources with radio counterparts. The blue/green dots represent those with previous known/unknown γ-ray detection. The orange diamonds represent faint mm sources with fluxes assigned by forced photometry using positional priors from the SUMSS radio catalog. Note that the steep-spectrum AGNs roughly lie within the yellow oval and run up the vertical axis clustered around S 150GHz = 10 mJy, while the flat-spectrum AGNs lie within the blue oval, which is nearly diagonal with slope = 1.239. 4FGL sources are selected if they have both SPT and SUMSS counterparts. These sources are shown in green and blue. Note that the total number of both blue and green dots in the plot is 265. This is because some 4FGL sources have multiple mm–radio counterparts as illustrated in Figure 3. Similar to Figure 1, the blue points are previously associated 4FGL sources, while the green points are previously unassociated 4FGL sources that have SPT counterparts. The majority of 4FGL sources are flat-spectrum AGNs.
Paper: New Identifications and Multiwavelength Properties of Extragalactic Fermi Gamma-Ray Sources in the SPT-SZ Survey Field
Authors: Lizhong Zhang, 力中 张, Joaquin D. Vieira, Marco Ajello, Matthew A. Malkan, Melanie A. Archipley, Joseph Capota, Allen Foster, Greg Madejski
Figure caption: Top panel: mm and γ-ray flux correlation with each source labeled. Source types are labeled by their identities (previously identified 4FGL source: blue dot; BL Lac: black diamond; FSRQ: red square; unassociated 4FGL source: green dot; faint mm sources: orange diamonds). The previously identified 4FGL sources without mm detections (ID-4FGL-NoSPT) and the remaining unidentified 4FGL sources (UID-4FGL) are indicated by blue and orange arrows, respectively, as 3σ upper limits from SPT-SZ. Note that three bright ID-4FGL-NoSPT sources (S 0.1−100GeV > 10−11 erg cm−2 s−1) in blue arrows are previously identified pulsars and therefore fail to be identified by SPT. Within associated 4FGL sources, FSRQs are more likely to be brighter than BL Lacs in mm wavelength. Most unassociated 4FGL sources are faint in both mm and γ-ray bands, which indicates that source identification might be limited by the sensitivity of the current generation of surveys. Bottom panel: the mm–radio spectral index (﹩{\alpha }_{150\,\mathrm{GHz}}^{843\,\mathrm{MHz}}﹩) as a function of γ-ray flux. Sources are labeled the same way as in the left panel. Cyan dots denote the median and standard deviations of the spectral index in each logarithmic bin of γ-ray flux. As shown in the plot, sources with brighter γ-ray fluxes are more likely to have flatter spectra except a few sources with γ-ray flux around 10−11 erg cm−2 s−1. These outliers have excess radio emission compared with normal flat-spectrum AGNs. Among these sources, some might have extra radio emission from nearby radio lobes, some are just ambiguous cross-matching that blends several radio counterparts, and some have valid multiband counterparts and need further investigation.
Paper: New Identifications and Multiwavelength Properties of Extragalactic Fermi Gamma-Ray Sources in the SPT-SZ Survey Field
Authors: Lizhong Zhang, 力中 张, Joaquin D. Vieira, Marco Ajello, Matthew A. Malkan, Melanie A. Archipley, Joseph Capota, Allen Foster, Greg Madejski
Figure caption: Flux correlations between 4FGL and other surveys (X-ray: blue; infrared: light blue; mm: green; radio: red), where black dots indicate previously unassociated 4FGL sources with mm counterparts. The Spearman’s rank correlation coefficient (r SC) of the flux correlation is shown in the upper right corner of each plot. Note that r SC,ID refers to previously associated 4FGL sources and r SC,UID+ID counts both previously associated and extra mm-identified 4FGL sources. (a) As most of the 4FGL-SPT blazars are flat-spectrum AGNs, the r SC in the radio band should be similar to that of the mm band. However, r SC in the radio band is significantly lower than the mm band because some 4FGL-SPT blazars have excess radio emission compared with most flat-spectrum sources (see Figure 7). (b) The mm and γ-ray bands are highly correlated, which is consistent with previous studies of multiwavelength associations of 4FGL sources. The dashed line represents least-squares fitting between the fluxes in the two bands. (c) The infrared band has comparable correlation to the γ-ray band as the mm band. However, the association between 4FGL and WISE has been refined by first matching to SPT because normal cross-matching would be heavily contaminated by the spurious associations due to the high source number density of WISE (∼104 deg−2). (d) Unlike any other wavelengths, the X-ray fluxes are uncorrelated with γ-ray fluxes. This may be because the γ-ray traces the jet while the X-ray traces the coronal region of the AGN (Ghisellini et al. 2017).
Paper: New Identifications and Multiwavelength Properties of Extragalactic Fermi Gamma-Ray Sources in the SPT-SZ Survey Field
Authors: Lizhong Zhang, 力中 张, Joaquin D. Vieira, Marco Ajello, Matthew A. Malkan, Melanie A. Archipley, Joseph Capota, Allen Foster, Greg Madejski
Figure caption: Potential associations of the sources from external catalogs with the 282 4FGL sources in the SPT-SZ survey field plotted with their probability of false association (p-value) vs. source separation in units of positional uncertainty. The gray dots represent all the point sources within 10σ 4FGL positional uncertainty. The vertical and horizontal dashed lines indicate our adopted r < 4σ 4FGL positional separation cut and p-value < 0.1 cut, respectively. The black dots represent the source with the lowest p-value associated with a 4FGL source. Orange diamonds represent faint mm sources with fluxes assigned by forced photometry using positional priors from the SUMSS radio catalog. Note that σ 4FGL refers to the standard deviation of the 4FGL position, which varies source by source. Left panel: the SUMSS radio associations are heavily contaminated owing to the excessively high source number density; thus, the region of spurious association extends from the upper right region to roughly 4σ 4FGL in separation and 0.1 in probability of false association. Middle panel: the SPT mm association shows more distinct separation between the two groups of the associations in p–r space, while for radio association the contamination of the spurious cross-matching causes the large overlap in the spurious region. With both the high completeness and high purity, mm provides the best combined performance in completeness and reliability. Right panel: the RASS X-ray association shows good purity according to the low probability of false association (most gray dots within 4σ 4FGL have p-value less than 0.1), but the completeness is the lowest compared with the others (see Table 1). Multiwavelength comparisons of sources within 4σ 4FGL in single parameter space are histogrammed in Figure 5. Note that the sources shown at low p-value and separation < 4σ 4FGL, which are shown in gray, are where there are multiple counterparts for a given 4FGL source, and we have adopted the counterpart with the lowest p-value as the association.
Paper: New Identifications and Multiwavelength Properties of Extragalactic Fermi Gamma-Ray Sources in the SPT-SZ Survey Field
Authors: Lizhong Zhang, 力中 张, Joaquin D. Vieira, Marco Ajello, Matthew A. Malkan, Melanie A. Archipley, Joseph Capota, Allen Foster, Greg Madejski
Figure caption: Multiwavelength comparison of the potential associations with 282 4FGL sources in the SPT-SZ survey field. Y-axes for both panels are number of sources. These histograms indicate that SPT+SUMSS is the most efficient identifier of γ-ray counterparts with high completeness and reliability. Left panel: histogram of angular separation of 4FGL sources from SUMSS (radio), SPT (mm), SPT+SUMSS (mm), and RASS (X-ray) positions. The mm and radio associations are highly complete, while X-ray only has around half of their completeness. Right panel: histogram of the probability of false associations of the 4FGL sources with SUMSS, SPT, SPT+SUMSS, and RASS sources. A low probability of false association corresponds to a high certainty of a real counterpart. Thus, the mm and X-ray counterparts are more secure because most of them have the probability of false association less than 0.1, while only around 2/3 radio potential counterparts are within 0.1.
Paper: New Identifications and Multiwavelength Properties of Extragalactic Fermi Gamma-Ray Sources in the SPT-SZ Survey Field
Authors: Lizhong Zhang, 力中 张, Joaquin D. Vieira, Marco Ajello, Matthew A. Malkan, Melanie A. Archipley, Joseph Capota, Allen Foster, Greg Madejski
Figure caption: Selected samples illustrating various kinds of 4FGL associations with mm and radio sources. 4FGL source name and thumbnail index (see Appendix A and B for all the sources studied in this work) are shown in the upper left corner of each panel. Each 0.°7 × 0.°7 thumbnail in the gray background is the high-pass-filtered SPT 150 GHz image. The blue ellipse at the center shows the 4FGL 95% uncertainty position, and the dashed blue ellipse represents the 4σ uncertainty. The green diamond marks the position of the SPT point source. The red circle shows the position of SUMSS point sources. The first two examples are of previously associated 4FGL sources, which already had known counterparts. In both cases, these known sources are also uniquely identified by SPT (the first is very bright in the mm wave band, while the second is fainter). The last two panels show previously unassociated 4FGL sources. The third panel shows a new unique association with an SPT source. The last panel shows an unusual case where two SPT sources fall within the 4FGL error circle, either or both of which could be producing the γ-ray emission.
Paper: New Identifications and Multiwavelength Properties of Extragalactic Fermi Gamma-Ray Sources in the SPT-SZ Survey Field
Authors: Lizhong Zhang, 力中 张, Joaquin D. Vieira, Marco Ajello, Matthew A. Malkan, Melanie A. Archipley, Joseph Capota, Allen Foster, Greg Madejski
Figure caption: Left panel: specific luminosity in 150 GHz as a function of redshift. We have assumed a ΛCDM cosmology with Ω M  = 0.27, ΩΛ = 0.73, and H 0 = 71 km s−1 Mpc−1. Gray dots represent all the SPT sources with redshift measurements. Those with 4FGL counterparts (4FGL-SPT) are covered by blue dots. We also label the blazar type for each 4FGL-SPT source if it is classified in the catalog. Given the same redshift, mm-identified 4FGL sources (flat-spectrum AGNs) are brightest, where the specific luminosity is above the threshold of mm detection by orders of magnitude. This is resulting from the mixing of two types of sources (flat-spectrum and steep-spectrum AGNs) and the selection bias of redshift data. Details are discussed in Section 4. We can roughly distinguish the population of FSRQs and BL Lacs by their mm specific luminosity. Right panel: histogram of redshift distribution. The label colors are consistent with the left panel, and redshifts are binned logarithmically. This histogram shows that the populations of FSRQs and BL Lacs can be distinguished by their redshift measurements as well. FSRQs are mostly observed with higher redshift than BL Lacs. This distinction should come from the detection bias of optical spectrum measurement. In general, FSRQs have strong emission lines in optical broadband, while the broadband spectra of BL Lacs have weak emission lines or are even featureless.
Paper: New Identifications and Multiwavelength Properties of Extragalactic Fermi Gamma-Ray Sources in the SPT-SZ Survey Field
Authors: Lizhong Zhang, 力中 张, Joaquin D. Vieira, Marco Ajello, Matthew A. Malkan, Melanie A. Archipley, Joseph Capota, Allen Foster, Greg Madejski
Figure caption: WISE color analysis. The background color map is based on the number source density in WISE color space. This color map contours the classes of WISE objects (see also Wright et al. 2010). On the background color map, each dot marks the SPT-selected source. These sources are also labeled by their identifications (previously associated 4FGL source: blue dot; previously unassociated 4FGL source with mm counterpart: green triangle; BL Lac: black diamond; FSRQ: red square). Red dashed lines outline the WGS (Massaro et al. 2012). Most of the mm associations lie inside the WGS, which indicates the consistency of mm correlation and WGS parameterization. Besides, the mm cross-matching provides more intrinsic associations and pinpoints the valid outliers outside WGS in WISE color space.
Paper: New Identifications and Multiwavelength Properties of Extragalactic Fermi Gamma-Ray Sources in the SPT-SZ Survey Field
Authors: Lizhong Zhang, 力中 张, Joaquin D. Vieira, Marco Ajello, Matthew A. Malkan, Melanie A. Archipley, Joseph Capota, Allen Foster, Greg Madejski
Figure caption: Multiwavelength flux density as a function of redshift. Most wavelengths (radio, mm, infrared, and γ-ray) show no apparent correlations between flux density and redshift, while in X-rays the upper bound of count rate declines for the fainter sources. Therefore, at most wavelengths, flat-spectrum AGNs are equally likely to be detected given the flux above the threshold of flux detection. In the X-rays, the extra flux dependence constraining the upper bound is due to the relative shallow depth of RASS. Either the bright X-ray sources at high redshift are less likely to be detected by RASS, or the origin of X-ray emission can be different from other wavelengths.
Paper: New Identifications and Multiwavelength Properties of Extragalactic Fermi Gamma-Ray Sources in the SPT-SZ Survey Field
Authors: Lizhong Zhang, 力中 张, Joaquin D. Vieira, Marco Ajello, Matthew A. Malkan, Melanie A. Archipley, Joseph Capota, Allen Foster, Greg Madejski
Figure caption: The logic sequence of multiwavelength cross-matching of 4FGL sources. We initially conduct the preliminary 4FGL cross-matching with SUMSS, SPT, and RASS to evaluate the most efficient wavelength for the γ-ray source identification, where the SPT+SUMSS association turns out to maximize the completeness while minimizing the impurity. The true counterparts are selected based on the statistics of the Poissonian probability from the preliminary results. We then take the advantage of mm–radio (SPT+SUMSS) counterparts to refine the position and enable a reliable cross-match with WISE.
Paper: On the Stability of Tidal Streams in Action Space
Authors: Arpit Arora, Robyn E. Sanderson, Nondh Panithanpaisal, Emily C. Cunningham, Andrew Wetzel, Nicolás Garavito-Camargo
Figure caption: The dynamically evolving COM in simulation coordinates for m12i (green), m12w (orange), and m12f (red). The re-centering is done with respect to the present-day positions. While m12i has smooth COM positions with time, accelerations in COM are prominent in m12f and m12w at t peri (black star). This is due to the infalling satellites displacing the barycenter position and velocity (reflex motion) during the merger. This effect is stronger in m12w with a more massive satellite and lower d peri.
Paper: On the Stability of Tidal Streams in Action Space
Authors: Arpit Arora, Robyn E. Sanderson, Nondh Panithanpaisal, Emily C. Cunningham, Andrew Wetzel, Nicolás Garavito-Camargo
Figure caption: The total magnitude of COM acceleration (green) along with the spline accelerations (black) calculated using the smooth cubic spline fits for each coordinate axis for m12i. The actual acceleration is jittery, highly oscillatory, and large while the spline values are significantly smooth and lower in comparison. The spline fit COM positions and velocities are overall better suited for potential modeling.
Paper: On the Stability of Tidal Streams in Action Space
Authors: Arpit Arora, Robyn E. Sanderson, Nondh Panithanpaisal, Emily C. Cunningham, Andrew Wetzel, Nicolás Garavito-Camargo
Figure caption: Amplitude in ∣Φ ℓ,0∣ r  averaged over radii for even poles of the multipole model with ℓ ≤ 4 described in Section 2.4.2 for all the halos computed independently at each time step. Due to the axisymmetry assumption, the odd poles vanish and the amplitude is stored only in m = 0 for even poles. The black stars on the plot mark the t peri for m12f and m12w. The increased amplitude near the merger demonstrates the ability of the higher poles in spherical harmonics in modeling a satellite infall.
Paper: On the Stability of Tidal Streams in Action Space
Authors: Arpit Arora, Robyn E. Sanderson, Nondh Panithanpaisal, Emily C. Cunningham, Andrew Wetzel, Nicolás Garavito-Camargo
Figure caption: Pericenter distance of the merging satellite with respect to the host galaxy for m12f and m12w. The mergers happen at 7.2 and 10.8 Gyr for m12f (two different satellites) and at 8 Gyr for m12w. The black stars illustrate the time at the first pericenter t peri.
Paper: On the Stability of Tidal Streams in Action Space
Authors: Arpit Arora, Robyn E. Sanderson, Nondh Panithanpaisal, Emily C. Cunningham, Andrew Wetzel, Nicolás Garavito-Camargo
Figure caption: Rotation velocity curve (left) computed using different potential models at the present day along with the true rotation curve (black). Note that both multipole (blue) and analytic (green) models produce rotation curves consistent with the true curves (accuracy of ±5% at all radii (right)) of the true rotation for m12i (top), m12f (middle), and m12w (bottom). This serves as a preliminary check for our models.
Paper: Solving the Multimessenger Puzzle of the AGN-starburst Composite Galaxy NGC 1068
Authors: Björn Eichmann, Foteini Oikonomou, Silvia Salvatore, Ralf-Jürgen Dettmar, Julia Becker Tjus
Figure caption: The different timescales of relativistic protons (upper panel) and electrons (lower panel) for the starburst zone (left) and the AGN corona zone (right). The assumed parameters are given in Table 1. The thin solid black line refers to the total energy-loss timescale (τ cool) and the thin dashed black line refers to the total escape timescale (τ esc). The abbreviated individual processes are as follows: ﹩{pp}\hat{\,=}﹩ hadronic pion production, ﹩p\gamma \hat{\,=}﹩ photopion production, BH ﹩\hat{=}﹩ Bethe–Heitler pair production, syn ﹩\hat{=}﹩ synchrotron radiation, diff ﹩\hat{=}﹩ diffusion, adv ﹩\hat{=}﹩ advection, acc ﹩\hat{=}﹩ acceleration (DSA for the starburst and SDA for the corona), Coul.﹩\hat{=}﹩ Coulomb losses, Brems.﹩\hat{=}﹩ Bremsstrahlung, IC ﹩\hat{=}﹩ inverse Compton scattering.
Paper: Solving the Multimessenger Puzzle of the AGN-starburst Composite Galaxy NGC 1068
Authors: Björn Eichmann, Foteini Oikonomou, Silvia Salvatore, Ralf-Jürgen Dettmar, Julia Becker Tjus
Figure caption: The model predictions of the photon and neutrino SED of NGC 1068 with respect to the data: red markers refer to a beam size of ∼0.01 arcsec, and black markers indicate a beam size of ≳1 arcsec. The dark gray area indicates the internal flux of the background (target) photon fields (disk- and torus emission as well as Comptonized X-rays of the AGN corona) of the central AGN and the light gray area indicates the thermal IR emission by dust grains of the starburst region. Note that the torus attenuation is not taken into account here.
Paper: Solving the Multimessenger Puzzle of the AGN-starburst Composite Galaxy NGC 1068
Authors: Björn Eichmann, Foteini Oikonomou, Silvia Salvatore, Ralf-Jürgen Dettmar, Julia Becker Tjus
Figure caption: Sketch of the two-zone AGN-starburst model. The sizes of the regions are not to scale as the (inner) coronal region typically extends out to about some hundreds of microparsecs, whereas the starburst ring is located at about 1 kpc distance from the nucleus.
Paper: Solving the Multimessenger Puzzle of the AGN-starburst Composite Galaxy NGC 1068
Authors: Björn Eichmann, Foteini Oikonomou, Silvia Salvatore, Ralf-Jürgen Dettmar, Julia Becker Tjus
Figure caption: The chi-squared distribution of the starburst zone (left) and the AGN corona zone (right) dependent on the fit parameters, where we display for two different parameters and marginalize over the others. The red cross marks the best-fit parameter values that are also used in Figures 2, 3 and 5.
Paper: Solving the Multimessenger Puzzle of the AGN-starburst Composite Galaxy NGC 1068
Authors: Björn Eichmann, Foteini Oikonomou, Silvia Salvatore, Ralf-Jürgen Dettmar, Julia Becker Tjus
Figure caption: The resulting CR spectra of the starburst zone (left) and the AGN corona zone (right) using the best-fit parameters as introduced in Section 3, hereby s = 2.2 for the starburst and s = 1.7 for the corona.
Paper: A Machine Learning Framework to Predict Images of Edge-on Protoplanetary Disks
Authors: Zoie Telkamp, Jorge Martínez-Palomera, Gaspard Duchêne, Aishabibi Ashimbekova, Edward Wolfe, Isabel Angelo, Christophe Pinte
Figure caption: Adopted architecture for the autoencoder neural network. The autoencoder takes the inputted images, breaks them down into a lower-dimensional latent space through a series of layers, and reconstructs them through a symmetric process. Brackets denote a block unit, while each element inside is a layer. In this study, we adopt n  c  = 1 (single wavelength image), but the architecture can be readily expanded to multiple images of a given disk. Metadata is the set of physical parameters that describes each disk.
Paper: A Machine Learning Framework to Predict Images of Edge-on Protoplanetary Disks
Authors: Zoie Telkamp, Jorge Martínez-Palomera, Gaspard Duchêne, Aishabibi Ashimbekova, Edward Wolfe, Isabel Angelo, Christophe Pinte
Figure caption: Comparison between machine learning (ML) and RT images during the testing phase. The first two rows represent the RT and AE-reconstructed images, respectively, while the third row shows the difference between the two. The fourth row provides a histogram plot of the residual map evaluated at all pixels with a brightness of at least 3% of the peak, in either the ML or RT image. For cosmetic purposes, all images are shown with the same orientation, corrected for the flips and rotations introduced during the training phase.
Paper: A Machine Learning Framework to Predict Images of Edge-on Protoplanetary Disks
Authors: Zoie Telkamp, Jorge Martínez-Palomera, Gaspard Duchêne, Aishabibi Ashimbekova, Edward Wolfe, Isabel Angelo, Christophe Pinte
Figure caption: Observed 0.6 μm images of two known EODs (left column; Wolff et al. 2017, 2021) and corresponding RT- and ML-predicted model images. All images are shown on the same angular scale and stretch. The two faint point sources seen in the image of STSC2D J163131.2–242627 are unrelated background stars. Note that the ESO Hα 569 hosts a jet that is visible in the HST 0.6 μm and increases the disk’s peak brightness toward its center. The image normalization applied here thus artificially reduces the contrast in the observed image compared to the RT and ML images.