adsabs/AstroCLIMB huggingface dataset:
Paper: The X-Ray Luminous Type Ibn SN 2022ablq: Estimates of Preexplosion Mass Loss and Constraints on Precursor Emission
Authors: C. Pellegrino, M. Modjaz, Y. Takei, D. Tsuna, M. Newsome, T. Pritchard, R. Baer-Way, K. A. Bostroem, P. Chandra, P. Charalampopoulos, Y. Dong, J. Farah, D. A. Howell, C. McCully, S. Mohamed, E. Padilla Gonzalez, G. Terreran
Figure caption: The pseudobolometric light curve of SN 2022ablq (black points) compared to the CHIPS numerical light-curve model. The full CSM interaction and 56Ni decay light curve is shown (blue dashed line) alongside the separate CSM (orange dashed–dotted line) and 56Ni decay (green dotted line) components. The model parameters are shown in the text. The first observation is a lower limit given the lack of multiwavelength observations at this phase. There is remarkable agreement between the model light curve and our observations throughout the SN evolution, and the model parameters are in good agreement with the progenitor and mass-loss properties we infer from the X-ray detections.
Paper: Tracking an Eruptive Prominence Using Multiwavelength and Multiview Observations on 2023 March 7
Authors: Qingmin Zhang, Yudi Ou, Zhenghua Huang, Yongliang Song, Suli Ma
Figure caption: Time–distance diagram of S1 in 171 Å. s = 0 and s = 312″ stand for the southwest and northeast endpoints of S1 in Figure 2(d), respectively. The magenta dashed line denotes the time (20:25:09 UT) when the coronal loops are pushed farthest by the eruptive prominence.
Paper: Tracking an Eruptive Prominence Using Multiwavelength and Multiview Observations on 2023 March 7
Authors: Qingmin Zhang, Yudi Ou, Zhenghua Huang, Yongliang Song, Suli Ma
Figure caption: Top panels: the prominence observed in 304 Å by SDO/AIA (a1), GOES-16/SUVI (b1), SolO/EUI (c1), and STA/EUVI (d1) around 20:45 UT. The white arrows point to the legs and leading edge of the prominence. Bottom panels: the same EUV images superposed by projections of the reconstructed cone (cyan dots).
Paper: Tracking an Eruptive Prominence Using Multiwavelength and Multiview Observations on 2023 March 7
Authors: Qingmin Zhang, Yudi Ou, Zhenghua Huang, Yongliang Song, Suli Ma
Figure caption: The Solar-MACH plot at 20:30 UT on 2023 March 7, showing the locations and connectivity to the Sun of STA (red box), SolO (blue box), and Earth (green box).
Paper: Tracking an Eruptive Prominence Using Multiwavelength and Multiview Observations on 2023 March 7
Authors: Qingmin Zhang, Yudi Ou, Zhenghua Huang, Yongliang Song, Suli Ma
Figure caption: The prominence observed by AIA (top panels) and EUI (bottom panels) at 20:30 UT (a1)–(b1) and 20:37 UT (c1)–(d1), respectively. Projections of the reconstructed cones are superposed with cyan dots (a2)–(d2).
Paper: Tracking an Eruptive Prominence Using Multiwavelength and Multiview Observations on 2023 March 7
Authors: Qingmin Zhang, Yudi Ou, Zhenghua Huang, Yongliang Song, Suli Ma
Figure caption: The prominence observed by AIA (top panels) and EUVI (bottom panels) at 20:25 UT (a1)–(b1) and 20:35 UT (c1)–(d1), respectively. Projections of the reconstructed cones are superposed with cyan dots (a2)–(d2).
Paper: Tracking an Eruptive Prominence Using Multiwavelength and Multiview Observations on 2023 March 7
Authors: Qingmin Zhang, Yudi Ou, Zhenghua Huang, Yongliang Song, Suli Ma
Figure caption: Light curves of the C2.3 flare in 1−8 Å (pink line) and 94 Å (dark blue line).
Paper: GOALS-JWST: The Warm Molecular Outflows of the Merging Starburst Galaxy NGC 3256
Authors: Thomas Bohn, Hanae Inami, Aditya Togi, Lee Armus, Thomas S.-Y. Lai, Loreto Barcos-Munoz, Yiqing Song, S. T. Linden, Jason Surace, Marina Bianchin, Vivian U, Aaron S. Evans, Torsten Böker, Matthew A. Malkan, Kirsten L. Larson, Sabrina Stierwalt, Victorine A. Buiten, Vassilis Charmandaris, Tanio Diaz-Santos, Justin H. Howell, George C. Privon, Claudio Ricci, Paul P. van der Werf, Susanne Aalto, Christopher C. Hayward, Justin A. Kader, Joseph M. Mazzarella, Francisco Muller-Sanchez, David B. Sanders
Figure caption: Left: PAH 6.2 μm flux map, plotted over the full MIRI channel 1 FOV. Blue and red contours mark the regions where we detect the molecular outflows, as traced by H2 S(1) 17.0 μm emission. The PAH emission is strongest in the nuclear region of each galaxy, with prominent emission also seen in the disks and spiral arms. Upper right: PAH 6.2 μm flux histogram. Regions within each outflow (red and blue) and the nuclei (green) have been separately identified from those outside them (gray). The outflow regions are based on the contours in Figure 8, and the nuclear regions are defined as the central region within a radius of 5σ of the point-spread function (PSF). The dashed lines indicate the median value for each region and are accordingly labeled. Lower right: PAH6.2/PAH7.7 and PAH11.3/PAH7.7 flux ratios from Continuum And Feature Extraction (CAFE) Region Extraction Tool Automaton (CRETA) grid extractions of the disk, nuclear, and outflow regions of the northern and southern galaxy (see the Appendix). Model tracks from B. T. Draine et al. (2021) show the theoretical values for neutral and ionized PAHs. The ratios of the outflow regions are within the scatter of the disk ratios, suggesting that the outflows have no significant effect on the grain size and ionization state of the PAHs.
Paper: Neural Network Constraints on the Cosmic-Ray Ionization Rate and Other Physical Conditions in NGC 253 with ALCHEMI Measurements of HCN and HNC
Authors: Erica Behrens, Jeffrey G. Mangum, Serena Viti, Jonathan Holdship, Ko-Yun Huang, Mathilde Bouvier, Joshua Butterworth, Cosima Eibensteiner, Nanase Harada, Sergio Martín, Kazushi Sakamoto, Sebastien Muller, Kunihiko Tanaka, Laura Colzi, Christian Henkel, David S. Meier, Víctor M. Rivilla, Paul P. van der Werf
Figure caption: Top: map of NGC 253 HCN 1–0 integrated emission with S/N > 3 overlaid with the regions analyzed in this article. Purple circles indicate locations of GMCs studied in J. Holdship et al. (2022) and E. Behrens et al. (2022; note J. Holdship et al. 2022 only investigated GMCs 3–7). The circle in the bottom-left corner indicates the size of the 1.″6 (∼28 pc) ALCHEMI beam. Orange crosses in both panels indicate the location of the galaxy’s kinematic center (J. L. Turner & P. T. P. Ho 1985). Bottom: map of the hexagonal regions used in this analysis with hatching to indicate how many total HCN and HNC transitions have been detected with S/N > 3.
Paper: Neural Network Constraints on the Cosmic-Ray Ionization Rate and Other Physical Conditions in NGC 253 with ALCHEMI Measurements of HCN and HNC
Authors: Erica Behrens, Jeffrey G. Mangum, Serena Viti, Jonathan Holdship, Ko-Yun Huang, Mathilde Bouvier, Joshua Butterworth, Cosima Eibensteiner, Nanase Harada, Sergio Martín, Kazushi Sakamoto, Sebastien Muller, Kunihiko Tanaka, Laura Colzi, Christian Henkel, David S. Meier, Víctor M. Rivilla, Paul P. van der Werf
Figure caption: Parameter-inference results from our Bayesian nested sampling plus neural network algorithm for kinetic temperature (upper left), H2 volume density (upper right), CRIR (middle left), H2 column density (middle right), and beam-filling factor (bottom). Gray contours correspond the the integrated HCN 1–0 emission at levels of 1, 3, and 5 Jy km s−1 beam−1. White and black crosses indicate the galaxy’s kinematic center (J. L. Turner & P. T. P. Ho 1985). Green circle in the bottom-right corner of each map represents ALCHEMI’s 1.″6 (∼28 pc) beam.
Paper: Neural Network Constraints on the Cosmic-Ray Ionization Rate and Other Physical Conditions in NGC 253 with ALCHEMI Measurements of HCN and HNC
Authors: Erica Behrens, Jeffrey G. Mangum, Serena Viti, Jonathan Holdship, Ko-Yun Huang, Mathilde Bouvier, Joshua Butterworth, Cosima Eibensteiner, Nanase Harada, Sergio Martín, Kazushi Sakamoto, Sebastien Muller, Kunihiko Tanaka, Laura Colzi, Christian Henkel, David S. Meier, Víctor M. Rivilla, Paul P. van der Werf
Figure caption: (a) Neural network predictions of test set parameter combinations where the model was trained using the original parameter ranges in Table 2 without buffer points. Predictions for parameter combinations that used maximum or minimum values for column or volume density are indicated with X’s. (b) Same as (a), but neural network training set included additional buffer points for volume and column density.(c) Neural network predictions using the same model as in (b), but buffer points are not plotted.
Paper: Neural Network Constraints on the Cosmic-Ray Ionization Rate and Other Physical Conditions in NGC 253 with ALCHEMI Measurements of HCN and HNC
Authors: Erica Behrens, Jeffrey G. Mangum, Serena Viti, Jonathan Holdship, Ko-Yun Huang, Mathilde Bouvier, Joshua Butterworth, Cosima Eibensteiner, Nanase Harada, Sergio Martín, Kazushi Sakamoto, Sebastien Muller, Kunihiko Tanaka, Laura Colzi, Christian Henkel, David S. Meier, Víctor M. Rivilla, Paul P. van der Werf
Figure caption: Flow chart describing our Bayesian nested sampling algorithm, where the highlighted purple rectangle indicates the neural network’s position in our modeling process.
Paper: Neural Network Constraints on the Cosmic-Ray Ionization Rate and Other Physical Conditions in NGC 253 with ALCHEMI Measurements of HCN and HNC
Authors: Erica Behrens, Jeffrey G. Mangum, Serena Viti, Jonathan Holdship, Ko-Yun Huang, Mathilde Bouvier, Joshua Butterworth, Cosima Eibensteiner, Nanase Harada, Sergio Martín, Kazushi Sakamoto, Sebastien Muller, Kunihiko Tanaka, Laura Colzi, Christian Henkel, David S. Meier, Víctor M. Rivilla, Paul P. van der Werf
Figure caption: (a) Corner plot for region 26 using UCLCHEM. (b) Corner plot for region 26 using the HCN/HNC neural network. (c) Corner plot for region 53 using UCLCHEM. (d) Corner plot for region 53 using the HCN/HNC neural network.
Paper: Neural Network Constraints on the Cosmic-Ray Ionization Rate and Other Physical Conditions in NGC 253 with ALCHEMI Measurements of HCN and HNC
Authors: Erica Behrens, Jeffrey G. Mangum, Serena Viti, Jonathan Holdship, Ko-Yun Huang, Mathilde Bouvier, Joshua Butterworth, Cosima Eibensteiner, Nanase Harada, Sergio Martín, Kazushi Sakamoto, Sebastien Muller, Kunihiko Tanaka, Laura Colzi, Christian Henkel, David S. Meier, Víctor M. Rivilla, Paul P. van der Werf
Figure caption: Uncertainties on our five inferred parameters. For the parameters over which we consider a log-uniform distribution (﹩{n}_{{{\rm{H}}}_{2}}﹩, ζ, and ﹩{N}_{{{\rm{H}}}_{2}}﹩), we show their uncertainties as orders of magnitude from the inferred value, as shown above the corner plot 1D distributions in Figure 4.
Paper: GOALS-JWST: The Warm Molecular Outflows of the Merging Starburst Galaxy NGC 3256
Authors: Thomas Bohn, Hanae Inami, Aditya Togi, Lee Armus, Thomas S.-Y. Lai, Loreto Barcos-Munoz, Yiqing Song, S. T. Linden, Jason Surace, Marina Bianchin, Vivian U, Aaron S. Evans, Torsten Böker, Matthew A. Malkan, Kirsten L. Larson, Sabrina Stierwalt, Victorine A. Buiten, Vassilis Charmandaris, Tanio Diaz-Santos, Justin H. Howell, George C. Privon, Claudio Ricci, Paul P. van der Werf, Susanne Aalto, Christopher C. Hayward, Justin A. Kader, Joseph M. Mazzarella, Francisco Muller-Sanchez, David B. Sanders
Figure caption: PAH6.2/PAH7.7 and PAH11.3/PAH7.7 ratio maps. Each grid is 1.″0 × 1.″0 in size. The locations of the nuclei are shown as white crosses and the red and blue contours show the locations of the outflows based on the H2 S(1) 17.0 μm outflow emission.
Paper: Neutrino Detection Rates from Lepto-hadronic Model Simulations of Bright Blazar Flares
Authors: Joshua Robinson, Markus Böttcher
Figure caption: Neutrino count expectations for OneHaLe simulations of the sample of blazar flares. Expected counts for the IceCube Neutrino Observatory are shown in green, and those for KM3NeT are shown in purple. The expected neutrino counts using the calorimetric method are shown in red. The orange and blue dots represent the results from the grid scans of flare 34 and flare 21, respectively.
Paper: Neutrino Detection Rates from Lepto-hadronic Model Simulations of Bright Blazar Flares
Authors: Joshua Robinson, Markus Böttcher
Figure caption: An example of a fit SED and light curve for a flaring event (flare 7) of PKS 1510-089. In the top panel, the quiescent SED fit is shown in orange and the SED fit at the peak of the flare is shown in red. The photon-flux light curve from Fermi-LAT is shown in the bottom panel in blue, along with the simulated light curve in red.
Paper: Neutrino Detection Rates from Lepto-hadronic Model Simulations of Bright Blazar Flares
Authors: Joshua Robinson, Markus Böttcher
Figure caption: Lepto-hadronic fits for each source in our sample in their quiescent state. See Table 1 for parameters.
Paper: Absolute Dimensions of the Interferometric Binary HD 174881: A Test of Stellar Evolution Models for Evolved Stars
Authors: Guillermo Torres, Andrew F. Boden, John D. Monnier, Gerard T. van Belle
Figure caption: Similar to Figure 10, for the triple product amplitudes.
Paper: Absolute Dimensions of the Interferometric Binary HD 174881: A Test of Stellar Evolution Models for Evolved Stars
Authors: Guillermo Torres, Andrew F. Boden, John D. Monnier, Gerard T. van Belle
Figure caption: Similar to Figure 10, for the closure phases.
Paper: Simulations of the Collision between a Debris Stream and an Outer Dusty Torus: A Possible Channel for Forming a Fast-rise and Long-delay Radio Outburst in Tidal Disruption Events
Authors: Xiangli Lei, Qingwen Wu, Hui Li, Ya-Ping Li, Wei-Hua Lei, Xiao Fan, Jiancheng Wu, Mengye Wang, Weibo Yang
Figure caption: The top panel presents the radio light curves at 6 GHz for different model parameters, where the dotted lines present the typical radio emission from radio-quiet AGNs at different bolometric Eddington ratios with an SMBH mass of M BH = 106  M ⊙. The top-left panel presents the different torus densities and the injection angle for the debris stream with respect to the equatorial plane. The top-right panel shows the different penetration factors of TDEs. The bottom panel shows the results for the different SMBH masses and different Eddington ratios, which regulate the size of the dusty torus. The same color is used to represent the same dusty torus size.
Paper: Simulations of the Collision between a Debris Stream and an Outer Dusty Torus: A Possible Channel for Forming a Fast-rise and Long-delay Radio Outburst in Tidal Disruption Events
Authors: Xiangli Lei, Qingwen Wu, Hui Li, Ya-Ping Li, Wei-Hua Lei, Xiao Fan, Jiancheng Wu, Mengye Wang, Weibo Yang
Figure caption: The top-left panel shows the radio light curves at different frequencies (solid lines), where the dashed line represents the light curve of ﹩{\nu }_{{\rm{p}}}{L}_{{\nu }_{{\rm{p}}}}﹩. The evolution of the peak frequencies ν p is shown in the bottom-left panel. The right panel shows the same results but with the starting time set to the beginning of the interaction.
Paper: Simulations of the Collision between a Debris Stream and an Outer Dusty Torus: A Possible Channel for Forming a Fast-rise and Long-delay Radio Outburst in Tidal Disruption Events
Authors: Xiangli Lei, Qingwen Wu, Hui Li, Ya-Ping Li, Wei-Hua Lei, Xiao Fan, Jiancheng Wu, Mengye Wang, Weibo Yang
Figure caption: The distributions of the number density and entropy for the material at the azimuth of the debris stream in our simulation at several typical snapshots. In the left panels, the solid lines represent optical depth τ = 1 at different frequencies: 1 GHz (yellow), 3 GHz (red), and 4.5 GHz (black), where a face-on observer is assumed. In the right panels, the white and green solid lines correspond to ﹩S={10}^{-3}\,{S}_{\max }﹩ and ﹩S={10}^{-4}\,{S}_{\max }﹩, respectively.
Paper: Simulations of the Collision between a Debris Stream and an Outer Dusty Torus: A Possible Channel for Forming a Fast-rise and Long-delay Radio Outburst in Tidal Disruption Events
Authors: Xiangli Lei, Qingwen Wu, Hui Li, Ya-Ping Li, Wei-Hua Lei, Xiao Fan, Jiancheng Wu, Mengye Wang, Weibo Yang
Figure caption: The distributions of the scaled entropy at fixed θ = 0.8 and ϕ = 0 (along the debris) at several typical snapshots, and the red and orange dashed lines represent ﹩S={10}^{-3}\,{S}_{\max }﹩ and ﹩S={10}^{-4}\,{S}_{\max }﹩, respectively.
Paper: Simulations of the Collision between a Debris Stream and an Outer Dusty Torus: A Possible Channel for Forming a Fast-rise and Long-delay Radio Outburst in Tidal Disruption Events
Authors: Xiangli Lei, Qingwen Wu, Hui Li, Ya-Ping Li, Wei-Hua Lei, Xiao Fan, Jiancheng Wu, Mengye Wang, Weibo Yang
Figure caption: The radio spectrum at different epochs, where triangles correspond to the peak luminosity.
Paper: Simulations of the Collision between a Debris Stream and an Outer Dusty Torus: A Possible Channel for Forming a Fast-rise and Long-delay Radio Outburst in Tidal Disruption Events
Authors: Xiangli Lei, Qingwen Wu, Hui Li, Ya-Ping Li, Wei-Hua Lei, Xiao Fan, Jiancheng Wu, Mengye Wang, Weibo Yang
Figure caption: The left panel shows the spectral fits for PS16dtm on days 1767 and 2291 after detection. The right panel shows the radio light curves at 3 GHz and 6 GHz (the data are selected from Y. Cendes et al. 2023), where the solid lines are model predictions.
Paper: Simulations of the Collision between a Debris Stream and an Outer Dusty Torus: A Possible Channel for Forming a Fast-rise and Long-delay Radio Outburst in Tidal Disruption Events
Authors: Xiangli Lei, Qingwen Wu, Hui Li, Ya-Ping Li, Wei-Hua Lei, Xiao Fan, Jiancheng Wu, Mengye Wang, Weibo Yang
Figure caption: Schematic diagram of the interaction between the unbound debris and the outer dusty torus.
Paper: Rotational Velocities and Radii Estimates of Low-mass Pre-main-sequence Stars in NGC 2264
Authors: Laurin M. Gray, Katherine L. Rhode, Catrina M. Hamilton-Drager, Tiffany Picard, Luisa M. Rebull
Figure caption: Example probability density distribution of r sin i, for ρ = 1. The black histogram is for the idealized case, with no measurement uncertainties in v sin i or the rotation period. The blue histogram is the probability distribution for a star with a relative uncertainty of 0.1 in the v sin i measurement, with the red line showing the curve fit to the distribution. The probability of measuring a specific value of r sin i given the rotation period, v sin i, and radius predicted by the stellar evolutionary model can then be obtained from the fitted function.
Paper: Rotational Velocities and Radii Estimates of Low-mass Pre-main-sequence Stars in NGC 2264
Authors: Laurin M. Gray, Katherine L. Rhode, Catrina M. Hamilton-Drager, Tiffany Picard, Luisa M. Rebull
Figure caption: Plot of our measured v sin i values vs. values for the same stars from J. C. Mermilliod et al. (2009), to demonstrate the effectiveness of our measurement methods. The magenta dashed line depicts a perfect one-to-one correlation.
Paper: JWST Validates HST Distance Measurements: Selection of Supernova Subsample Explains Differences in JWST Estimates of Local H 0 
Authors: Adam G. Riess, Dan Scolnic, Gagandeep S. Anand, Louise Breuval, Stefano Casertano, Lucas M. Macri, Siyang Li, Wenlong Yuan, Caroline D. Huang, Saurabh Jha, Yukei S. Murakami, Rachael Beaton, Dillon Brout, Tianrui Wu, Graeme E. Addison, Charles Bennett, Richard I. Anderson, Alexei V. Filippenko, Anthony Carr
Figure caption: Distribution of H 0 values for each calibrator SN Ia as calibrated by HST Cepheids (left panel). The mean of the complete set of 42, in blue, results in H 0 = 73 km s−1 Mpc−1, and the standard deviation is a result of SN Ia dispersion with σ of 6% in distance. We show the subsample selected by the CCHP (10 hosts of 11 SNe Ia) and after their exclusion of three hosts for JAGB measurements (top-left panel). The remaining set of eight SNe Ia used for JAGB, in red, are biased low with respect to the mean, with HST Cepheids expecting H 0 = 70.5 km s−1 Mpc−1 for this set. Selecting a every unique combination of eight SNe Ia from the original 42 shows the selected JAGB sample to be unusual, both low in H 0 (top-middle panel, only 5% are lower) and with little variation in H 0 (right panel, only 5% are lower), with <0.1% of samples both lower and tighter. This selection is the primary reason for the low value of H 0 from CCHP JAGB, not from a difference in measured distances.
Paper: JWST Validates HST Distance Measurements: Selection of Supernova Subsample Explains Differences in JWST Estimates of Local H 0 
Authors: Adam G. Riess, Dan Scolnic, Gagandeep S. Anand, Louise Breuval, Stefano Casertano, Lucas M. Macri, Siyang Li, Wenlong Yuan, Caroline D. Huang, Saurabh Jha, Yukei S. Murakami, Rachael Beaton, Dillon Brout, Tianrui Wu, Graeme E. Addison, Charles Bennett, Richard I. Anderson, Alexei V. Filippenko, Anthony Carr
Figure caption: Anchors and SN Ia hosts selected to cross-check HST and JWST distances from the full HST sample of four anchors and 42 SNe Ia. We show the value of H 0 indicated by HST alone for each SN Ia. Small samples will produce large fluctuations in the value of H 0. (HST also indicates the selection by both teams of the anchor NGC 4258 will produce a lower value of H 0 by −0.7 km s−1 Mpc−1.) The JWST subsample selected by each team may be directly compared to the same from HST (i.e., “apples to apples”) without bias, but if used alone to determine H 0, the subsample value is seen to be biased with respect to the full HST sample mean with the values calculated from HST Cepheids indicated on the right. A larger sample, both teams combined (red and blue, N = 15 SNe Ia), is found to be minimally biased and nearly complete in distance to D < 25 Mpc.
Paper: JWST Validates HST Distance Measurements: Selection of Supernova Subsample Explains Differences in JWST Estimates of Local H 0 
Authors: Adam G. Riess, Dan Scolnic, Gagandeep S. Anand, Louise Breuval, Stefano Casertano, Lucas M. Macri, Siyang Li, Wenlong Yuan, Caroline D. Huang, Saurabh Jha, Yukei S. Murakami, Rachael Beaton, Dillon Brout, Tianrui Wu, Graeme E. Addison, Charles Bennett, Richard I. Anderson, Alexei V. Filippenko, Anthony Carr
Figure caption: A graphic explaining two issues that may be addressed using new JWST observations, overlaid on top of the three-rung distance ladder presented by R22. The first (see Section 2) compares relative distances measured between NGC 4258 and SN Ia hosts by HST Cepheids with other indicators. This can be done at the 0.03–0.06 mag level depending on the quality of the measurements. This test is independent of SN magnitudes, anchor distances, and the Hubble flow. The second (see Section 3) refers to the measurement of H 0 that can be expected from the selected SN subsamples and chosen anchor. This is strongly affected by the subsample selection owing to sampling noise and is most meaningfully compared to the same selections made from the full HST sample as indicated.
Paper: JWST Validates HST Distance Measurements: Selection of Supernova Subsample Explains Differences in JWST Estimates of Local H 0 
Authors: Adam G. Riess, Dan Scolnic, Gagandeep S. Anand, Louise Breuval, Stefano Casertano, Lucas M. Macri, Siyang Li, Wenlong Yuan, Caroline D. Huang, Saurabh Jha, Yukei S. Murakami, Rachael Beaton, Dillon Brout, Tianrui Wu, Graeme E. Addison, Charles Bennett, Richard I. Anderson, Alexei V. Filippenko, Anthony Carr
Figure caption: HST Cepheid distance linearity assessed by comparing to all other indicators. The comparison is a linear fit μ HST = slope × μ other − offset between each method (non-SN) and HST Cepheids (relative to the distance of NGC 4258, 29.4 mag) with one additional offset term for including SNe (                            ﹩{M}_{B}^{0}﹩                         ), a total of one linearity term and two offsets. The HST Cepheid linearity is measured to be 0.994 ± 0.010, in good agreement with unity. There is also no evidence of an offset (non-SN) relative to all other indicators, with HST Cepheids in good accord with the mean. In the inset, we show the combined constraint out to 5σ confidence and compared to the region that would be necessary to produce an 0.18 mag mean bias between NGC 4258 and the mean HST SN Ia host, a range of 2.5 mag.