adsabs/AstroCLIMB huggingface dataset:
Paper: Mass, Luminosity, and Stellar Age of Early-type Stars from the LAMOST Survey
Authors: Qida Li, Jianping Xiong, Jiao Li, Yanjun Guo, Zhanwen Han, Xuefei Chen, Chao Liu
Figure caption: Comparison of L and M with that of W. Sun et al. (2021). The x-axis represents the values from W. Sun et al. (2021), and the y-axis represents our predicted values for the sample selected from M. Xiang et al. (2022). The median relative error is indicated at the top left of each panel.
Paper: Mass, Luminosity, and Stellar Age of Early-type Stars from the LAMOST Survey
Authors: Qida Li, Jianping Xiong, Jiao Li, Yanjun Guo, Zhanwen Han, Xuefei Chen, Chao Liu
Figure caption: The distribution on T eff–﹩\mathrm{log}\ L﹩ for our sample (left) and mock data (right). In the left panel, the two black lines show the boundary range of the mock data. The other colored lines represent the different degrees of evolution of stars with solar metallicity in the main sequence. In the right panel, the color represents the M i.
Paper: Mass, Luminosity, and Stellar Age of Early-type Stars from the LAMOST Survey
Authors: Qida Li, Jianping Xiong, Jiao Li, Yanjun Guo, Zhanwen Han, Xuefei Chen, Chao Liu
Figure caption: The differences in our predicted values of L, M, t, and M i between the two prediction samples. The x-axis represents the predicted values for Y. Guo et al. (2021), and the y-axis is those from M. Xiang et al. (2022). The median relative error has been marked at the top left of each panel.
Paper: Mass, Luminosity, and Stellar Age of Early-type Stars from the LAMOST Survey
Authors: Qida Li, Jianping Xiong, Jiao Li, Yanjun Guo, Zhanwen Han, Xuefei Chen, Chao Liu
Figure caption: The M–L relations of the stars from our sample. The red crosses represent the median values of the predicted L in each mass bin, and the orange curve represents the M–L relation from PARSEC 1.2S, fitted by the least-squares method. The curves in other styles represent the work of others from Table 4. The color indicates the value of [M/H].
Paper: Mass, Luminosity, and Stellar Age of Early-type Stars from the LAMOST Survey
Authors: Qida Li, Jianping Xiong, Jiao Li, Yanjun Guo, Zhanwen Han, Xuefei Chen, Chao Liu
Figure caption: The distribution of the ratio of the lifetime for stars of different masses for our sample. The x-axis represents the predicted M, and the y-axis represents the predicted t divided by the main-sequence lifetime. The color indicates the count in log of each bin.
Paper: Mass, Luminosity, and Stellar Age of Early-type Stars from the LAMOST Survey
Authors: Qida Li, Jianping Xiong, Jiao Li, Yanjun Guo, Zhanwen Han, Xuefei Chen, Chao Liu
Figure caption: The distribution of predicted L, M, t, and M i for our sample in the Milky Way. Different panels represent different predicted parameters, and the color indicates the value of each parameter.
Paper: Mass, Luminosity, and Stellar Age of Early-type Stars from the LAMOST Survey
Authors: Qida Li, Jianping Xiong, Jiao Li, Yanjun Guo, Zhanwen Han, Xuefei Chen, Chao Liu
Figure caption: The distribution of samples filtered out by the convex hull algorithm on the T eff–﹩\mathrm{log}\ g﹩ panel, with colors representing the values of [M/H].
Paper: Mass, Luminosity, and Stellar Age of Early-type Stars from the LAMOST Survey
Authors: Qida Li, Jianping Xiong, Jiao Li, Yanjun Guo, Zhanwen Han, Xuefei Chen, Chao Liu
Figure caption: The atmospheric parameters between the two samples we used. The x-axis represents the atmospheric parameters from Y. Guo et al. (2021), and the y-axis is those from M. Xiang et al. (2022).
Paper: Mass, Luminosity, and Stellar Age of Early-type Stars from the LAMOST Survey
Authors: Qida Li, Jianping Xiong, Jiao Li, Yanjun Guo, Zhanwen Han, Xuefei Chen, Chao Liu
Figure caption: Comparison of prediction results between Bayesian isochrone fitting and RF on the testing set. The x-axis represents the true values from the testing set, while the y-axis shows the predicted results from Bayesian isochrone fitting (first row) and the RF model (second row).
Paper: Time-averaging Polarimetric and Spectral Properties of Gamma-Ray Bursts
Authors: Liang Li, Soroush Shakeri
Figure caption: The lightcurve, polarization, and spectral properties for the HD-type bursts. Left panels: the prompt emission lightcurve (overlaid in gray) and polarization observations in γ-ray/hard X-ray energy bands (cyan shaded area). Right panels: the spectral data and their best-fit model (Band+BB) during the time epoch (see Table 1) of the matching polarization observations.
Paper: Time-averaging Polarimetric and Spectral Properties of Gamma-Ray Bursts
Authors: Liang Li, Soroush Shakeri
Figure caption:                         Same as Figure 1 but for bursts classified as PFD-type with Band-like spectra.
Paper: Time-averaging Polarimetric and Spectral Properties of Gamma-Ray Bursts
Authors: Liang Li, Soroush Shakeri
Figure caption: Left: the maximum degree of the linear polarization applying a synchrotron emission model (﹩{{\rm{\Pi }}}_{{\rm{\max }}}^{{\rm{lin}}}﹩; Equation (8)) with observed data using α indices based on a time-integrated spectral analysis. Here, we have plotted the polarization of 16 GRBs out of 27 sources, and we ignored 11 GRBs with only limiting reported values of polarization. Right: time-integrated polarization degree in the presence of an ordered magnetic field Bord within the plane of ejecta (Equation (8)) measured by an on-axis observer (θobs = 0); the evolution of the polarization is plotted in terms of α for different values of ﹩{y}_{{\rm{\max }}}={({\rm{\Gamma }}{\theta }_{{\rm{\max }}})}^{2}﹩.
Paper: Time-averaging Polarimetric and Spectral Properties of Gamma-Ray Bursts
Authors: Liang Li, Soroush Shakeri
Figure caption: The time-integrated polarization for a random magnetic field B⊥ that lies entirely in the plane of the shock (Equation (18)) as a function of the off-axis parameter ζ = θobs/θj for different values of spectral index α (left) and ﹩{y}_{j}={({\rm{\Gamma }}{\theta }_{j})}^{2}﹩ (right) as labeled.
Paper: Time-averaging Polarimetric and Spectral Properties of Gamma-Ray Bursts
Authors: Liang Li, Soroush Shakeri
Figure caption: Scatter plots of polarization degree π vs. several other observed quantities: (a) the peak energy (Ep) of the νFν prompt emission spectrum, (b) the BB temperature kT, (c) the corresponding energy fluence Sγ, (d) the magnetization parameter σ0, and (e) the redshift z. Data points with gray and red colors indicate the PFD and HD bursts, respectively.
Paper: Time-averaging Polarimetric and Spectral Properties of Gamma-Ray Bursts
Authors: Liang Li, Soroush Shakeri
Figure caption: Distribution of polarization degree π, comparing the PFD-type bursts (gray color) with the HD-type bursts (red color). The best Gaussian fits give π = log10(65.9 ± 1.7)% for the HD-type bursts (dashed red line) and π = log10(50.0 ± 1.5)% (the higher-peak G1) and π = log10(11.9 ± 1.2)% (the lower-peak G2) for the PFD-type bursts (dashed gray line).
Paper: Time-averaging Polarimetric and Spectral Properties of Gamma-Ray Bursts
Authors: Liang Li, Soroush Shakeri
Figure caption:                         Same as Figure 2 but for bursts classified as PFD-type with CPL-like spectra.
Paper: Identification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection
Authors: Baoqiang Lao, Heinz Andernach, Xiaolong Yang, Xiang Zhang, Rushuang Zhao, Zhen Zhao, Yun Yu, Xiaohui Sun, Sheng-Li Qin
Figure caption: Left: the distribution of logarithmic 1.4 GHz luminosity (﹩{{\rm{log}}}_{10}({L}_{1.4{\rm{GHz}}})﹩) for all BTRGs with redshift (z) is depicted, where the color of each circle corresponds to the BTRG number, reflecting their respective redshift and 1.4 GHz luminosity values. Right: the distribution of logarithmic 1.4 GHz luminosity (﹩{{\rm{log}}}_{10}({L}_{1.4{\rm{GHz}}})﹩) for FR-I and FR-II sources in our BTRG catalog. The red dashed line represents the classical luminosity break value ﹩{{\rm{log}}}_{10}({L}_{1.4{\rm{GHz}}}/{\rm{W}}\,{{\rm{Hz}}}^{-1})=25﹩. The blue and black dashed lines denote luminosities at peaks of the distribution for FR-I and FR-II, respectively.
Paper: Identification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection
Authors: Baoqiang Lao, Heinz Andernach, Xiaolong Yang, Xiang Zhang, Rushuang Zhao, Zhen Zhao, Yun Yu, Xiaohui Sun, Sheng-Li Qin
Figure caption: An example demonstrating the identification of a host galaxy through visual inspection of a FIRST image (magenta contours) overlaid on a DESI LS r-band image (background image). Contour levels begin at 3 times the local rms noise (1σ = 0.14 mJy/beam) and increase by a factor of ﹩\sqrt{2}﹩. The peak flux density and centroid coordinates are marked with a yellow “+.” Potential host candidates are indicated with an “ × ,” where a green “ × ” represents the true host galaxy identified by visual inspection, and two blue “ × ” signs indicate the nearest host candidates to the peak flux density and centroid coordinates, respectively.
Paper: Identification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection
Authors: Baoqiang Lao, Heinz Andernach, Xiaolong Yang, Xiang Zhang, Rushuang Zhao, Zhen Zhao, Yun Yu, Xiaohui Sun, Sheng-Li Qin
Figure caption: Definition example of opening angle (OA) for a BTRG. The magenta dotted line represents the predicted polygon points of the BTRG, derived from the transformation of its prediction mask. The green dotted line indicates the center-line of the predicted polygon points. The core position (C) of the BTRG is denoted by a blue “ × .” The tail end positions (T1 and T2) are indicated by blue filled circles. The gray dashed line illustrates the circle of curvature of the radio jets. The black point Pc is the center of the fitted circle, and the gray solid line represents the radius of curvature.
Paper: Identification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection
Authors: Baoqiang Lao, Heinz Andernach, Xiaolong Yang, Xiang Zhang, Rushuang Zhao, Zhen Zhao, Yun Yu, Xiaohui Sun, Sheng-Li Qin
Figure caption: Examples of five classes (CS, sFR-I, sFR-II, BT, and OSE) in this work. The BT class is a combination of WAT and NAT. The red dotted line represents the straight or bent jets of a radio source.
Paper: Identification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection
Authors: Baoqiang Lao, Heinz Andernach, Xiaolong Yang, Xiang Zhang, Rushuang Zhao, Zhen Zhao, Yun Yu, Xiaohui Sun, Sheng-Li Qin
Figure caption: FIRST image (contours) overlaid on the DESI LS r-band image (gray scale) for a sample of 12 BTRGs. Contour levels begin at 3 times the local rms noise and increase by a factor of ﹩\sqrt{2}﹩. The green “ × ” represents the host galaxy.
Paper: Identification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection
Authors: Baoqiang Lao, Heinz Andernach, Xiaolong Yang, Xiang Zhang, Rushuang Zhao, Zhen Zhao, Yun Yu, Xiaohui Sun, Sheng-Li Qin
Figure caption: A histogram depicting the distribution of the spectral index (﹩{\alpha }_{1.4\,{\rm{GHz}}}^{3\,{\rm{GHz}}}﹩) for all BTRGs is presented. The black dotted curve represents a Gaussian fit to the histogram, characterized by a mean of 0.83 ± 0.01 and a standard deviation of 0.32. The red dashed line indicates the mean spectral index value.
Paper: Identification of 4876 Bent-tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection
Authors: Baoqiang Lao, Heinz Andernach, Xiaolong Yang, Xiang Zhang, Rushuang Zhao, Zhen Zhao, Yun Yu, Xiaohui Sun, Sheng-Li Qin
Figure caption: A simple schematic of the RGCMT network for BTRG detection, modified from L. Ke et al. (2022). For a given image, Mask R-CNN first generates an initial coarse mask prediction. Then, the ambiguity areas detector identifies ambiguity areas using three levels of region of interest (RoI) align features. Finally, the transformer block is used to correct the ambiguity areas and produce the final refined mask prediction.
Paper: Kinematics of Young Stellar Objects under Various Stellar Feedback
Authors: Longhui Yang, Dejian Liu, Chaojie Hao, Zehao Lin, YingJie Li, Yiwei Dong, Zu-Jia Lu, En-Wei Liang, Y. Xu
Figure caption: This figure shows the kinematic characteristics of the star-forming regions affected by feedback from massive stars. (a) YSO distribution in OMC. The green circle represents the H II region the same as in Figure 1. The blue circles represent regions with radii of three-fourths and five-fourths of H II region radii, respectively. The red dots represent YSOs inside the H II region and the blue dots represent YSOs near the edge of the H II region. (b) YSO distribution in NGC 2024. The green circle represents the H II region the same as in Figure 4. The blue circles represent regions with radii of three-fourths and five-fourths of H II region radii, respectively. The red dots represent YSOs inside the H II region and the blue dots represent YSOs near the edge of the H II region.
Paper: Kinematics of Young Stellar Objects under Various Stellar Feedback
Authors: Longhui Yang, Dejian Liu, Chaojie Hao, Zehao Lin, YingJie Li, Yiwei Dong, Zu-Jia Lu, En-Wei Liang, Y. Xu
Figure caption: Projected distribution of YSOs in λ Orionis. The background is a false-color image of λ Orionis (red: Planck 353 GHz; green: IRAS 100 μm; and blue: Hα). The contours represent the velocity channel of [−2.6, 15.6] km s−1. The other features are the same as in Figure 1.
Paper: Kinematics of Young Stellar Objects under Various Stellar Feedback
Authors: Longhui Yang, Dejian Liu, Chaojie Hao, Zehao Lin, YingJie Li, Yiwei Dong, Zu-Jia Lu, En-Wei Liang, Y. Xu
Figure caption: Kinematics characteristics of the studied star-forming regions. (a) Difference in the LSR velocity between different classes of YSOs and molecular gas, i.e., ∣ΔV LSR,rad∣. (b) Difference in 3D velocity between the Class II and III YSOs, i.e., ∣ΔV 3D∣. From left to right the feedback environment consists of outflows, massive stars, and supernovae. The points in different colors represent the investigated subregions.
Paper: Kinematics of Young Stellar Objects under Various Stellar Feedback
Authors: Longhui Yang, Dejian Liu, Chaojie Hao, Zehao Lin, YingJie Li, Yiwei Dong, Zu-Jia Lu, En-Wei Liang, Y. Xu
Figure caption: Parallax distributions and criteria applied to the YSOs in the Orion A, shown for (a) the OMC, (b) L1641N, (c) L1641C, (d) L1641S1, and (e) L1641S2. The green solid circles represent the Class I YSOs, the red crosses represent the Class II YSOs, and the blue open circles represent the Class III YSOs.
Paper: Kinematics of Young Stellar Objects under Various Stellar Feedback
Authors: Longhui Yang, Dejian Liu, Chaojie Hao, Zehao Lin, YingJie Li, Yiwei Dong, Zu-Jia Lu, En-Wei Liang, Y. Xu
Figure caption: Proper-motion distribution of YSOs in Taurus, where the crosses represent Class II YSOs and the circles represent Class III YSOs.
Paper: Kinematics of Young Stellar Objects under Various Stellar Feedback
Authors: Longhui Yang, Dejian Liu, Chaojie Hao, Zehao Lin, YingJie Li, Yiwei Dong, Zu-Jia Lu, En-Wei Liang, Y. Xu
Figure caption: Proper-motion distribution of YSOs in B30. The crosses represent Class II YSOs and the circles represent Class III YSOs.
Paper: Kinematics of Young Stellar Objects under Various Stellar Feedback
Authors: Longhui Yang, Dejian Liu, Chaojie Hao, Zehao Lin, YingJie Li, Yiwei Dong, Zu-Jia Lu, En-Wei Liang, Y. Xu
Figure caption: Parallax distributions and criteria applied to the YSOs in Taurus, shown for (a) Heiles’ Cloud 2, (b) L1536, (c) B18, (d) L1495, and (e) B213. The other features are the same as in Figure B1.
Paper: Kinematics of Young Stellar Objects under Various Stellar Feedback
Authors: Longhui Yang, Dejian Liu, Chaojie Hao, Zehao Lin, YingJie Li, Yiwei Dong, Zu-Jia Lu, En-Wei Liang, Y. Xu
Figure caption: Parallax distributions and criteria applied to the YSOs in Perseus, shown for (a) IC 348 and (b) NGC 1333. The other features are the same as in Figure B1.
Paper: Kinematics of Young Stellar Objects under Various Stellar Feedback
Authors: Longhui Yang, Dejian Liu, Chaojie Hao, Zehao Lin, YingJie Li, Yiwei Dong, Zu-Jia Lu, En-Wei Liang, Y. Xu
Figure caption: Parallax distributions and criteria applied to the YSOs in Orion B, shown for (a) L1630N and (b) NGC 2024. The other features are the same as in Figure B1.
Paper: Simons Observatory: Predeployment Performance of a Large Aperture Telescope Optics Tube in the 90 and 150 GHz Spectral Bands
Authors: Carlos E. Sierra, Kathleen Harrington, Shreya Sutariya, Thomas Alford, Anna M. Kofman, Grace E. Chesmore, Jason E. Austermann, Andrew Bazarko, James A. Beall, Tanay Bhandarkar, Mark J. Devlin, Simon R. Dicker, Peter N. Dow, Shannon M. Duff, Daniel Dutcher, Nicholas Galitzki, Joseph E. Golec, John C. Groh, Jon E. Gudmundsson, Saianeesh K. Haridas, Erin Healy, Johannes Hubmayr, Jeffrey Iuliano, Bradley R. Johnson, Claire S. Lessler, Richard A. Lew, Michael J. Link, Tammy J. Lucas, Jeffrey J. McMahon, Jenna E. Moore, Federico Nati, Michael D. Niemack, Benjamin L. Schmitt, Max Silva-Feaver, Robinjeet Singh, Rita F. Sonka, Alex Thomas, Robert J. Thornton, Tran Tsan, Joel N. Ullom, Jeffrey L. Van Lanen, Eve M. Vavagiakis, Michael R. Vissers, Yuhan Wang, Kaiwen Zheng
Figure caption: The comparison between different detector responsivity calibration methods and the observed optical response to a chopped source as a function of commanded bias voltage, where the bias line resistance is 16.4 kΩ. In both panels, the responsivity curves are shown for 39 detector channels at 90 GHz. These detectors were chosen such that they were all close to 50% R  n  at V bias = 6 V. The lines indicate the S  I  (V bias) values calculated using either the IV curves or bias steps method. In the left panel, bias step calibrations are used to determine the range of bias voltages “on transition” between 20 and 80% R  n , and this range is fit to the S  I  function. The same operation is performed in the right panel for the IV “Method A” calibration. The black curve regions correspond to ranges where the detector is “off transition,” i.e., R  n  < 20% or R  n  > 80%. The bias step calibration method correctly reproduces the optical response pattern when the detectors are on transition, while the IV calibration does not follow the observed optical response. This is believed to be due to nontrivial wafer heating that occurs during an IV curve measurement.
Paper: Simons Observatory: Predeployment Performance of a Large Aperture Telescope Optics Tube in the 90 and 150 GHz Spectral Bands
Authors: Carlos E. Sierra, Kathleen Harrington, Shreya Sutariya, Thomas Alford, Anna M. Kofman, Grace E. Chesmore, Jason E. Austermann, Andrew Bazarko, James A. Beall, Tanay Bhandarkar, Mark J. Devlin, Simon R. Dicker, Peter N. Dow, Shannon M. Duff, Daniel Dutcher, Nicholas Galitzki, Joseph E. Golec, John C. Groh, Jon E. Gudmundsson, Saianeesh K. Haridas, Erin Healy, Johannes Hubmayr, Jeffrey Iuliano, Bradley R. Johnson, Claire S. Lessler, Richard A. Lew, Michael J. Link, Tammy J. Lucas, Jeffrey J. McMahon, Jenna E. Moore, Federico Nati, Michael D. Niemack, Benjamin L. Schmitt, Max Silva-Feaver, Robinjeet Singh, Rita F. Sonka, Alex Thomas, Robert J. Thornton, Tran Tsan, Joel N. Ullom, Jeffrey L. Van Lanen, Eve M. Vavagiakis, Michael R. Vissers, Yuhan Wang, Kaiwen Zheng
Figure caption: The measured optical responses for the 90 and 150 GHz spectral bands found using the two different measurement methods, “warm chops” and “IV/P bias,” as explained in the text. The measured optical responses of the 150 GHz detectors are smaller than those of the 90 GHz detectors because of the lower NDF transmission in the 150 GHz band. The colored dashed lines mark the median values measured for each method. The black dashed lines mark the response expected from the end-to-end optics model for the installed optics and detectors. The gray-shaded region indicates the effect of the band-averaged NDF transmission uncertainty on the expected optical response. Both measurement methods are in good agreement with the optical model, indicating the integrated optical efficiency is sufficiently close to the designed values.
Paper: Simons Observatory: Predeployment Performance of a Large Aperture Telescope Optics Tube in the 90 and 150 GHz Spectral Bands
Authors: Carlos E. Sierra, Kathleen Harrington, Shreya Sutariya, Thomas Alford, Anna M. Kofman, Grace E. Chesmore, Jason E. Austermann, Andrew Bazarko, James A. Beall, Tanay Bhandarkar, Mark J. Devlin, Simon R. Dicker, Peter N. Dow, Shannon M. Duff, Daniel Dutcher, Nicholas Galitzki, Joseph E. Golec, John C. Groh, Jon E. Gudmundsson, Saianeesh K. Haridas, Erin Healy, Johannes Hubmayr, Jeffrey Iuliano, Bradley R. Johnson, Claire S. Lessler, Richard A. Lew, Michael J. Link, Tammy J. Lucas, Jeffrey J. McMahon, Jenna E. Moore, Federico Nati, Michael D. Niemack, Benjamin L. Schmitt, Max Silva-Feaver, Robinjeet Singh, Rita F. Sonka, Alex Thomas, Robert J. Thornton, Tran Tsan, Joel N. Ullom, Jeffrey L. Van Lanen, Eve M. Vavagiakis, Michael R. Vissers, Yuhan Wang, Kaiwen Zheng
Figure caption: Top: readout crosstalk on the detector array is constrained by measuring the signal power within correlation beams of frequency-adjacent resonator pairs. This measurement is limited by a scattering noise floor at the 20–25 dB level; therefore, the majority of these correlation beam measurements should be interpreted as an upper bound constraint on readout crosstalk to below 1%. Channels labeled “noise-dominated beam” represent an upper limit for nearest-neighbor crosstalk, while channels labeled “visible beam crosstalk” indicate a true crosstalk signal that is measurable above this noise floor. Bottom: example of a neighboring pair of detector channels with relatively high electrical readout crosstalk of about 1%. A ghost beam is observed in each beam map directly near the center of the beam of the nearest-neighbor resonator, with dots indicating the center of the detector beams for reference. The amplitudes of the correlation beams are used to estimate crosstalk for these channels.
Paper: Simons Observatory: Predeployment Performance of a Large Aperture Telescope Optics Tube in the 90 and 150 GHz Spectral Bands
Authors: Carlos E. Sierra, Kathleen Harrington, Shreya Sutariya, Thomas Alford, Anna M. Kofman, Grace E. Chesmore, Jason E. Austermann, Andrew Bazarko, James A. Beall, Tanay Bhandarkar, Mark J. Devlin, Simon R. Dicker, Peter N. Dow, Shannon M. Duff, Daniel Dutcher, Nicholas Galitzki, Joseph E. Golec, John C. Groh, Jon E. Gudmundsson, Saianeesh K. Haridas, Erin Healy, Johannes Hubmayr, Jeffrey Iuliano, Bradley R. Johnson, Claire S. Lessler, Richard A. Lew, Michael J. Link, Tammy J. Lucas, Jeffrey J. McMahon, Jenna E. Moore, Federico Nati, Michael D. Niemack, Benjamin L. Schmitt, Max Silva-Feaver, Robinjeet Singh, Rita F. Sonka, Alex Thomas, Robert J. Thornton, Tran Tsan, Joel N. Ullom, Jeffrey L. Van Lanen, Eve M. Vavagiakis, Michael R. Vissers, Yuhan Wang, Kaiwen Zheng
Figure caption: Detector optical efficiencies measured using a cold load in the LATR-Tester’s dark configuration. These values assume a transmission model for all optics between 4 K and 100 mK. The median efficiency values of the distribution are 95% and 59% for 90 and 150 GHz detectors, respectively. Detectors with measured efficiencies above unity point to a systematic error in this measurement, likely from uncertainty in the optics model or excessive wafer heating.
Paper: Calibrating the Color–Magnitude Relation of M Giants by Using Open Clusters
Authors: X. Y. Tang, C. J. Hao, J. Li, Z. Z. Yan, Y. Xu, J. Zhong, Z. H. Lin, Y. J. Li, D. J. Liu, L. F. Ding, X. F. Long
Figure caption: Examples of OCs (blue dots) harboring M giants (red stars). The columns of each panel represent the distributions of the member stars of OCs and M giants for positions (α and δ), proper motions (﹩{\mu }_{{\alpha }^{* }}﹩ and μδ), and the CMD, as well as the mean parallax and total proper-motion dispersion of OCs. Here, the listed OCs are NGC 1798, Collinder 110, NGC 1817, UBC 435, FSR 0167, and NGC 1245. The identification numbers of M giants and the ages of OCs are displayed in the upper right of the CMD.