adsabs/AstroCLIMB huggingface dataset:
Paper: Spectroscopic Study of Heating Distributions and Mechanisms Using Hinode/EIS
Authors: Shun Ishigami, Hirohisa Hara, Takayoshi Oba
Figure caption: Comparison of β and λ in Equation (2). The red diamond shows the β = 1.04, and λ = −0.99, which minimize r. The blue and gray filled areas show the ±1σ and ±2σ errors where r ≤ 1 and r ≤ 2 for β and λ. The diamonds with numbers show the β, λ for 17 of the 22 heating models listed in C. H. Mandrini et al. (2000) in the range of β = [−0.1, 2.3] and λ = [−1.6, 1.0]. The crosses with alphabets show the β, λ obtained by the previous observational studies. The numbers and the alphabet are listed in Table 4. The upper right panel shows an enlarged view of the β = [0.6, 1.5], λ = [−1.2, −0.7] range.
Paper: Spectroscopic Study of Heating Distributions and Mechanisms Using Hinode/EIS
Authors: Shun Ishigami, Hirohisa Hara, Takayoshi Oba
Figure caption: The colored 2D histograms show the probability distributions of electron temperature and density of Loop 3 derived by a Bayesian analysis. Darker is a higher probability than bright. The green lines show T  e (s) and n  e (s) obtained by E 0 and s  H  that best explain the observations. The error bars of T  e (s) and n  e (s) indicate the ±1σ errors resulting from the photon noise. The horizontal bar shows the length of the segment. The loop end height h end is 5 Mm from the photosphere.
Paper: Spectroscopic Study of Heating Distributions and Mechanisms Using Hinode/EIS
Authors: Shun Ishigami, Hirohisa Hara, Takayoshi Oba
Figure caption: The relation of s  H , E 0 and L half. The red crosses indicate the best-fit values. The red vertical bars indicate the 95% credible intervals of s  H  and E 0 probability distributions for 18 loops indicated with the numbers. The black crosses show s  H  from M. J. Aschwanden et al. (2000) with the 1σ errors. The diamonds show s  H  and E 0 from M. J. Aschwanden (2001).
Paper: Spectroscopic Study of Heating Distributions and Mechanisms Using Hinode/EIS
Authors: Shun Ishigami, Hirohisa Hara, Takayoshi Oba
Figure caption: The electron temperature and density distributions by Hinode/EIS (black bars) and SDO/AIA (red bars) for Loop 3. The error bars on T  e , n  e  indicate uncertainties resulting from the photon noise derived by the aia_bp_estimate_error routine in SolarSoft. The horizontal bar shows the length of the segment. The diamonds are derived by Equation (5), assuming that the filling factor is unity.
Paper: Spectroscopic Study of Heating Distributions and Mechanisms Using Hinode/EIS
Authors: Shun Ishigami, Hirohisa Hara, Takayoshi Oba
Figure caption: The histograms show probability distributions of s  H  and E 0 from T  e (s) and n  e (s) of Loop 3 through Bayesian analysis. The red solid lines show the best-fit values. The ranges between the dashed blue and red lines indicate the 68% and 95% credible intervals.
Paper: Spectroscopic Study of Heating Distributions and Mechanisms Using Hinode/EIS
Authors: Shun Ishigami, Hirohisa Hara, Takayoshi Oba
Figure caption: Estimation of s  H , E 0 from the limited points of T  e (s) for ﹩{s}_{H}^{\mathrm{mod}}=10\ \mathrm{Mm},{E}_{0}^{\mathrm{mod}}=1.0\times {10}^{-2}\ \mathrm{erg}\ {\mathrm{cm}}^{-3}\ {{\rm{s}}}^{-1}﹩, and ﹩{L}_{\mathrm{half}}^{\mathrm{mod}}=55\ \mathrm{Mm}﹩.
Paper: Spectroscopic Study of Heating Distributions and Mechanisms Using Hinode/EIS
Authors: Shun Ishigami, Hirohisa Hara, Takayoshi Oba
Figure caption: The relation of s  H , E 0 and L half by spectroscopic data (black crosses) with these derived by imaging data (red crosses). The bars indicate the 95% credible intervals of s  H , E 0 probability distributions for 18 loops.
Paper: The Peculiar Disk Evolution of 4U 1630-472 Observed by Insight-HXMT During its 2022 and 2023 Outbursts
Authors: Jing-Qiang Peng, Shu Zhang, Qing-Cang Shui, Yu-Peng Chen, Shuang-Nan Zhang, Ling-Da Kong, A. Santangelo, Zhuo-Li Yu, Long Ji, Peng-Ju Wang, Zhi Chang, Jian Li, Zhao-sheng Li
Figure caption: Luminosity ratio of the nonthermal to the total luminosity obtained with model M1, plotted against the total luminosity. The green rectangle and red dashed triangle represent the anomalous and apparently standard regimes defined in Y. Abe et al. (2005), respectively. The RXTE data shown with blue triangles and diamonds are relevant to the standard regime (Y. Abe et al. 2005). The blue arrows represent the evolution with luminosity found in Y. Abe et al. (2005). The gray color represents the data from our article, with the star symbol representing the outburst in 2022 and the dot symbol the outburst in 2023. The black arrow indicates the direction of luminosity evolution, while the gray arrow shows the possible evolution direction at higher luminosities.
Paper: The Peculiar Disk Evolution of 4U 1630-472 Observed by Insight-HXMT During its 2022 and 2023 Outbursts
Authors: Jing-Qiang Peng, Shu Zhang, Qing-Cang Shui, Yu-Peng Chen, Shuang-Nan Zhang, Ling-Da Kong, A. Santangelo, Zhuo-Li Yu, Long Ji, Peng-Ju Wang, Zhi Chang, Jian Li, Zhao-sheng Li
Figure caption: Evolution of the spectral parameters of 4U 1630–472 in 2022 and 2023 determined with model M3: Γ is the low-energy power-law photon index, T in is the temperature of the inner disk, Cov_frac is the coverage factor, R in is the inner radius of the disk, p is the exponent of the radial dependence of the disk temperature, and F disk and F nonthermal are the disk flux and nonthermal flux, respectively. The colors are the same as those in Figure 3.
Paper: The Peculiar Disk Evolution of 4U 1630-472 Observed by Insight-HXMT During its 2022 and 2023 Outbursts
Authors: Jing-Qiang Peng, Shu Zhang, Qing-Cang Shui, Yu-Peng Chen, Shuang-Nan Zhang, Ling-Da Kong, A. Santangelo, Zhuo-Li Yu, Long Ji, Peng-Ju Wang, Zhi Chang, Jian Li, Zhao-sheng Li
Figure caption: Evolution of p against inner disk temperature T in. The colors have the same meaning as in Figure 3. The red and black lines are fits with linear slopes of −1.53 and −0.22, respectively. The shaded areas are 95% confidence intervals.
Paper: The Peculiar Disk Evolution of 4U 1630-472 Observed by Insight-HXMT During its 2022 and 2023 Outbursts
Authors: Jing-Qiang Peng, Shu Zhang, Qing-Cang Shui, Yu-Peng Chen, Shuang-Nan Zhang, Ling-Da Kong, A. Santangelo, Zhuo-Li Yu, Long Ji, Peng-Ju Wang, Zhi Chang, Jian Li, Zhao-sheng Li
Figure caption: Spectral fit using model M3 for 4U 1630–472, for Obs P040426302301. The black, red, and green symbols correspond to the LE, ME, and HE data from Insight-HXMT, respectively.
Paper: The Peculiar Disk Evolution of 4U 1630-472 Observed by Insight-HXMT During its 2022 and 2023 Outbursts
Authors: Jing-Qiang Peng, Shu Zhang, Qing-Cang Shui, Yu-Peng Chen, Shuang-Nan Zhang, Ling-Da Kong, A. Santangelo, Zhuo-Li Yu, Long Ji, Peng-Ju Wang, Zhi Chang, Jian Li, Zhao-sheng Li
Figure caption: Evolution of the hardening factor with luminosity. The pink stars are the mean values calculated by combining the four neighboring data points.
Paper: The Peculiar Disk Evolution of 4U 1630-472 Observed by Insight-HXMT During its 2022 and 2023 Outbursts
Authors: Jing-Qiang Peng, Shu Zhang, Qing-Cang Shui, Yu-Peng Chen, Shuang-Nan Zhang, Ling-Da Kong, A. Santangelo, Zhuo-Li Yu, Long Ji, Peng-Ju Wang, Zhi Chang, Jian Li, Zhao-sheng Li
Figure caption: Evolution of the spectral parameters of 4U 1630–472 in 2022 and 2023 from model M1: Γ is the low-energy power-law photon index, T in is the temperature of the inner disk, Cov_frac is the coverage factor, and r in is the inner radius of the disk. F disk and F nonthermal are the disk flux and nonthermal flux, respectively. The red dots represent data points with relatively low fluxes, including the 2022 outburst and three low-flux data points from the 2023 outburst, while the black dots correspond to high flux data from 2023.
Paper: The Peculiar Disk Evolution of 4U 1630-472 Observed by Insight-HXMT During its 2022 and 2023 Outbursts
Authors: Jing-Qiang Peng, Shu Zhang, Qing-Cang Shui, Yu-Peng Chen, Shuang-Nan Zhang, Ling-Da Kong, A. Santangelo, Zhuo-Li Yu, Long Ji, Peng-Ju Wang, Zhi Chang, Jian Li, Zhao-sheng Li
Figure caption: The relationship between inner disk temperature and flux. The red and black points have the same meanings as in Figure 3. The green and blue lines represent the relationship ﹩{F}_{\mathrm{disk}}\propto {T}_{\mathrm{in}}^{\alpha }﹩ , where α 1 = 1.20 ± 0.01 and α 2 = 1.61 ± 0.06. The two subfigures below are one- and two-dimensional projections of the posterior probability distributions, and the 0.16, 0.5, and 0.84 quantile contours derived from the MCMC analysis for the two parameters.
Paper: The Peculiar Disk Evolution of 4U 1630-472 Observed by Insight-HXMT During its 2022 and 2023 Outbursts
Authors: Jing-Qiang Peng, Shu Zhang, Qing-Cang Shui, Yu-Peng Chen, Shuang-Nan Zhang, Ling-Da Kong, A. Santangelo, Zhuo-Li Yu, Long Ji, Peng-Ju Wang, Zhi Chang, Jian Li, Zhao-sheng Li
Figure caption: Evolution of the spectral parameters of 4U 1630–472 in 2022 and 2023 determined using model M2: Γ is the low-energy power-law photon index, Cov_frac is the coverage factor, M dd is the effective mass accretion rate of the disk in units of 1018 g s−1, f col is the spectral hardening factor, T eff is the effective temperature of the inner zone of the disk, obtained by T in/f col, and R in is the inner radius of the disk. The colors are the same as those in Figure 3.
Paper: The Peculiar Disk Evolution of 4U 1630-472 Observed by Insight-HXMT During its 2022 and 2023 Outbursts
Authors: Jing-Qiang Peng, Shu Zhang, Qing-Cang Shui, Yu-Peng Chen, Shuang-Nan Zhang, Ling-Da Kong, A. Santangelo, Zhuo-Li Yu, Long Ji, Peng-Ju Wang, Zhi Chang, Jian Li, Zhao-sheng Li
Figure caption: The unabsorbed disk flux (1–100 keV) vs. the disk inner temperature (T eff). The flux correlates with temperature as ﹩{T}_{\mathrm{eff}}^{3.92\pm 0.13}﹩ and ﹩{T}_{\mathrm{eff}}^{4.91\pm 1.00}﹩ during the 2022 (left) and 2023 (right) outbursts, respectively. The two subfigures below are one- and two-dimensional projections of the posterior probability distributions, and the 0.16, 0.5, and 0.84 quantile contours derived from the MCMC analysis for the two parameters.
Paper: The Peculiar Disk Evolution of 4U 1630-472 Observed by Insight-HXMT During its 2022 and 2023 Outbursts
Authors: Jing-Qiang Peng, Shu Zhang, Qing-Cang Shui, Yu-Peng Chen, Shuang-Nan Zhang, Ling-Da Kong, A. Santangelo, Zhuo-Li Yu, Long Ji, Peng-Ju Wang, Zhi Chang, Jian Li, Zhao-sheng Li
Figure caption: HID of 4U 1630–472, where the hardness is defined as the ratio of F disk to F nonthermal. The colors are the same as those in Figure 3. The three data points with the lowest flux values from the 2023 outburst are plotted with triangles.
Paper: The Peculiar Disk Evolution of 4U 1630-472 Observed by Insight-HXMT During its 2022 and 2023 Outbursts
Authors: Jing-Qiang Peng, Shu Zhang, Qing-Cang Shui, Yu-Peng Chen, Shuang-Nan Zhang, Ling-Da Kong, A. Santangelo, Zhuo-Li Yu, Long Ji, Peng-Ju Wang, Zhi Chang, Jian Li, Zhao-sheng Li
Figure caption: Spectral fit of model M2 for 4U 1630–472, for Obs P040426302301. The black, red, and green symbols correspond to the LE, ME, and HE data from Insight-HXMT, respectively.
Paper: The Peculiar Disk Evolution of 4U 1630-472 Observed by Insight-HXMT During its 2022 and 2023 Outbursts
Authors: Jing-Qiang Peng, Shu Zhang, Qing-Cang Shui, Yu-Peng Chen, Shuang-Nan Zhang, Ling-Da Kong, A. Santangelo, Zhuo-Li Yu, Long Ji, Peng-Ju Wang, Zhi Chang, Jian Li, Zhao-sheng Li
Figure caption: Spectral fit of M1 for 4U 1630–472, for Obs P040426302301. The black, red, and green symbols correspond to the LE, ME, and HE data from Insight-HXMT, respectively.
Paper: The Peculiar Disk Evolution of 4U 1630-472 Observed by Insight-HXMT During its 2022 and 2023 Outbursts
Authors: Jing-Qiang Peng, Shu Zhang, Qing-Cang Shui, Yu-Peng Chen, Shuang-Nan Zhang, Ling-Da Kong, A. Santangelo, Zhuo-Li Yu, Long Ji, Peng-Ju Wang, Zhi Chang, Jian Li, Zhao-sheng Li
Figure caption: The light curves of 4U 1630–472 observed by Insight-HXMT during its 2022 and 2023 outbursts. Top panel: light curve of the Insight-HXMT LE instrument in 2–8 keV. Middle panel: light curve of the Insight-HXMT ME instrument in 10–28 keV. Bottom panel: light curve of the Insight-HXMT HE instrument in 28–100 keV.
Paper: The Peculiar Disk Evolution of 4U 1630-472 Observed by Insight-HXMT During its 2022 and 2023 Outbursts
Authors: Jing-Qiang Peng, Shu Zhang, Qing-Cang Shui, Yu-Peng Chen, Shuang-Nan Zhang, Ling-Da Kong, A. Santangelo, Zhuo-Li Yu, Long Ji, Peng-Ju Wang, Zhi Chang, Jian Li, Zhao-sheng Li
Figure caption: HID of 4U 1630–472, where the hardness is defined as the ratio of the 6–8 keV to 2–6 keV count rates. The red and black dots represent the 2022 and 2023 outbursts of 4U 1630–472 observed by Insight-HXMT.
Paper: Windy or Not: Radio Parsec-scale Evidence for a Broad-line Region Wind in Radio-quiet Quasars
Authors: Sina Chen, Ari Laor, Ehud Behar, Ranieri D. Baldi, Joseph D. Gelfand, Amy E. Kimball, Ian M. McHardy, Gabor Orosz, Zsolt Paragi
Figure caption: The C IV emission line profile compared to the Hβ line profile of the objects observed with the EVN, adapted from Figure 1 in A. Baskin & A. Laor (2005). Both line profiles are of the net BLR emission. The objects in the first column are selected to show C IV blue excess, and the objects in the second column do not show C IV blue excess. The six objects in the first, second, and third rows are detected in the EVN observations, and the four objects in the fourth and fifth rows are not detected in the EVN observations. The name of the object is indicated in the top left corner of each panel. The thick line is the C IV profile, and the thin line is the Hβ profile. Both profiles are normalized by their peak flux density. The peak flux density of the C IV/Hβ lines is listed in the top right corner of each panel in units of 10−14 erg cm−2 s−1 Å−1. The filled circles are data points used in the fitting procedure, and the open circles are data points excluded due to possible intrinsic or Galactic absorption.
Paper: Windy or Not: Radio Parsec-scale Evidence for a Broad-line Region Wind in Radio-quiet Quasars
Authors: Sina Chen, Ari Laor, Ehud Behar, Ranieri D. Baldi, Joseph D. Gelfand, Amy E. Kimball, Ian M. McHardy, Gabor Orosz, Zsolt Paragi
Figure caption: The C IV emission line profile compared to the Hβ line profile of the objects detected with the VLBA, adapted from Figure 1 in A. Baskin & A. Laor (2005). The first column shows the three objects with C IV blue excess, and the second and third columns show the 10 objects without C IV blue excess. The labels are the same as Figure 1.
Paper: Windy or Not: Radio Parsec-scale Evidence for a Broad-line Region Wind in Radio-quiet Quasars
Authors: Sina Chen, Ari Laor, Ehud Behar, Ranieri D. Baldi, Joseph D. Gelfand, Amy E. Kimball, Ian M. McHardy, Gabor Orosz, Zsolt Paragi
Figure caption: Radio maps of the six objects detected in the EVN observations at 1.7 and 4.9 GHz. The synthesized beam is shown in the lower left corner, and the size and orientation are reported in Table 1. The uv-range and the background noise rms are reported in Table 2. The images are centered at the Gaia position, which is marked as a red plus. The name of the object and the central frequency are indicated in the top left and top right corners of each panel, respectively.
Paper: Windy or Not: Radio Parsec-scale Evidence for a Broad-line Region Wind in Radio-quiet Quasars
Authors: Sina Chen, Ari Laor, Ehud Behar, Ranieri D. Baldi, Joseph D. Gelfand, Amy E. Kimball, Ian M. McHardy, Gabor Orosz, Zsolt Paragi
Figure caption: The distribution of the BH mass and the Eddington ratio of the combined EVN and VLBA sample. The black crosses represent the 71 z < 0.5 RQ PG quasars. The red squares and blue circles mark the objects observed with the EVN and VLBA, respectively. The undetected objects are in fainter colors.
Paper: Inferring Cosmological Parameters on SDSS via Domain-generalized Neural Networks and Light-cone Simulations
Authors: Jun-Young Lee, Ji-hoon Kim, Minyong Jung, Boon Kiat Oh, Yongseok Jo, Songyoun Park, Jaehyun Lee, Yuan-Sen Ting, Ho Seong Hwang
Figure caption: Diagram that exhibits the overall structure of this study with simulation and deep learning pipelines. We aim to infer cosmological parameters from the observation-driven catalog, SDSS BOSS LOWZ NGC. We produce two light-cone mock suites, L-PICOLA and GADGET mocks, combining N-body simulations (Sections 2.2 and 2.3) and galaxy-halo connection models (Section 2.5) while fully accounting for observational effects (Section 2.6). We then utilize a point-cloud-based network, Minkowski-PointNet, which takes individual galaxies as inputs to predict Ωm and σ 8, and their errors (Section 3). The L-PICOLA mocks (source domain) are trained together with the GADGET mocks (target domain) using the training strategy for the domain adaptation and generalization techniques (see Section 4.3). In this process, we use training strategies to align the representation of each mock (Section 4). The adapted machines are then applied to unseen domains, including the fine-tuned MD-PATCHY mocks and the SDSS BOSS LOWZ NGC sample. The main results, including the predictions for the actual observation are shown in Section 2.
Paper: Inferring Cosmological Parameters on SDSS via Domain-generalized Neural Networks and Light-cone Simulations
Authors: Jun-Young Lee, Ji-hoon Kim, Minyong Jung, Boon Kiat Oh, Yongseok Jo, Songyoun Park, Jaehyun Lee, Yuan-Sen Ting, Ho Seong Hwang
Figure caption: Count of galaxies per radial bins for SDSS BOSS LOWZ NGC (red solid line), L-PICOLA fiducial (orange dashed line), GADGET  fiducial (green dashed line), and averaged count for all 2048 MD-PATCHY (blue dashed line). The radial bins from redshift 0.15–0.4 are defined to evenly divide the redshift space volume. All light-cone mocks with fiducial cosmological parameters exhibit a consistent number of galaxies across different radial bins compared to the SDSS BOSS LOWZ NGC catalog. See Section 2.6 for more information.
Paper: Windy or Not: Radio Parsec-scale Evidence for a Broad-line Region Wind in Radio-quiet Quasars
Authors: Sina Chen, Ari Laor, Ehud Behar, Ranieri D. Baldi, Joseph D. Gelfand, Amy E. Kimball, Ian M. McHardy, Gabor Orosz, Zsolt Paragi
Figure caption: The Eddington ratio as a function of the radio slope at 1.7–4.9 GHz. The symbols are the same as in Figure 5. The names of the objects discussed in Section 7 are labeled. PG 1404+226 is likely affected by free–free absorption, and its intrinsic slope could be steep (see Section 7.1). The five objects with both radio and BLR winds (black) reside at ﹩\mathrm{log}L/{L}_{\mathrm{Edd}}\gt -0.5﹩, while eight of the nine objects without a wind (green) reside at ﹩\mathrm{log}L/{L}_{\mathrm{Edd}}\lt -0.5﹩.
Paper: Windy or Not: Radio Parsec-scale Evidence for a Broad-line Region Wind in Radio-quiet Quasars
Authors: Sina Chen, Ari Laor, Ehud Behar, Ranieri D. Baldi, Joseph D. Gelfand, Amy E. Kimball, Ian M. McHardy, Gabor Orosz, Zsolt Paragi
Figure caption: The radio 5 GHz to X-ray 0.2–12 keV luminosity ratio as a function of the BH mass. The objects are divided into four groups based on showing both radio and BLR winds (black), either BLR wind (blue) or radio wind (red) only, or neither BLR nor radio winds (green; including the corona and jet in radio). The classification can be seen in Table 4. The squares and circles represent the objects observed with EVN and VLBA, respectively.
Paper: Windy or Not: Radio Parsec-scale Evidence for a Broad-line Region Wind in Radio-quiet Quasars
Authors: Sina Chen, Ari Laor, Ehud Behar, Ranieri D. Baldi, Joseph D. Gelfand, Amy E. Kimball, Ian M. McHardy, Gabor Orosz, Zsolt Paragi
Figure caption: The radio slope at 1.7–4.9 GHz as a function of the C IV velocity shift divided by its FWHM. The symbols are the same as in Figure 5. The names of the objects discussed in Section 7 are labeled. PG 1404+226 is likely affected by free–free absorption, and its intrinsic slope could be steep (see Section 7.1). The five objects with both radio and BLR winds (black) show a strong C IV blue excess, while the nine objects without a wind (green) do not show it.
Paper: Inferring Cosmological Parameters on SDSS via Domain-generalized Neural Networks and Light-cone Simulations
Authors: Jun-Young Lee, Ji-hoon Kim, Minyong Jung, Boon Kiat Oh, Yongseok Jo, Songyoun Park, Jaehyun Lee, Yuan-Sen Ting, Ho Seong Hwang
Figure caption: The footprints of a single realization from L-PICOLA fiducial (top left), GADGET fiducial (top right), MD-PATCHY (bottom left), and SDSS BOSS LOWZ NGC catalog (bottom right). The same acceptance and veto masks are employed to reproduce the overall topology. We further cut the region into R.A. = 150°–240° and decl. > 0°. See Section 2.6 for more information.
Paper: Windy or Not: Radio Parsec-scale Evidence for a Broad-line Region Wind in Radio-quiet Quasars
Authors: Sina Chen, Ari Laor, Ehud Behar, Ranieri D. Baldi, Joseph D. Gelfand, Amy E. Kimball, Ian M. McHardy, Gabor Orosz, Zsolt Paragi
Figure caption: The Eddington ratio as a function of the C IV velocity shift divided by its FWHM. The symbols are the same as in Figure 5. The names of the objects discussed in Section 7 are labeled.
Paper: Inferring Cosmological Parameters on SDSS via Domain-generalized Neural Networks and Light-cone Simulations
Authors: Jun-Young Lee, Ji-hoon Kim, Minyong Jung, Boon Kiat Oh, Yongseok Jo, Songyoun Park, Jaehyun Lee, Yuan-Sen Ting, Ho Seong Hwang
Figure caption: Light-cone slices of Figure 3 from 0° < decl. < 6°. See Section 2.6 for more information.
Paper: Inferring Cosmological Parameters on SDSS via Domain-generalized Neural Networks and Light-cone Simulations
Authors: Jun-Young Lee, Ji-hoon Kim, Minyong Jung, Boon Kiat Oh, Yongseok Jo, Songyoun Park, Jaehyun Lee, Yuan-Sen Ting, Ho Seong Hwang
Figure caption: Comparison of the ground truth and the predicted values of Ωm and σ 8 on the test set. Predictions are made by Minkowski-PointNet machines with L-PICOLA (red) and GADGET (blue) mocks, trained with the semantic alignment strategy. The top two panels display the results from the SHAM model and the bottom two panels display the results from the fixed-SHMR model. The left two columns show the results of a single arbitrarily selected machine, while the right two show the results for the 25 independently trained machines, with the normalized count expressed in logarithmic color bars. R 2, relative error (ϵ) and rms error metrics calculated altogether are shown. Residuals Δy = y true − y pred are depicted in the bottom panels. The machine is trained, validated, and tested on the two suites of mocks: L-PICOLA mocks and GADGET mocks. Error bars of the two left columns indicate the 1σ values derived from the implicit likelihood inference. Black dotted lines depict the complete match with null residual. The results from the ensemble of 25 machines for Ωm and σ 8 show a relative error of 3.20% and 1.28% for the SHAM model. The fixed-SHMR model yields 2.65% and 1.34%. See Section 5.1 for more information.
Paper: Inferring Cosmological Parameters on SDSS via Domain-generalized Neural Networks and Light-cone Simulations
Authors: Jun-Young Lee, Ji-hoon Kim, Minyong Jung, Boon Kiat Oh, Yongseok Jo, Songyoun Park, Jaehyun Lee, Yuan-Sen Ting, Ho Seong Hwang
Figure caption: Prediction on the actual SDSS BOSS LOWZ NGC catalog from the ensemble of 25 independently trained Minkowski-PointNet machines. The left figure displays our results when using the SHAM model, and the right figure displays the results when using the fixed-SHMR model. The machines are trained with L-PICOLA and GADGET mocks with the semantic alignment (SA) strategy, a domain adaptation and generalization technique that enables the machines to extract consistent features regardless of their simulation domains (see Section 4.3). Predictions are shown with error bars. A red star shows the result from the Planck 2018 (Planck Collaboration et al. 2020) measurements and a blue star from M. M. Ivanov et al. (2020). Elliptic contours show the bounds of 1σ, 2σ, and 3σ bounds, calculated from the Gaussian mixture model (GMM) to incorporate the individual errors. Our results yield Ωm = 0.339 ± 0.056, σ 8 = 0.801 ± 0.061 (left, SHAM), and Ωm = 0.227 ± 0.035, σ 8 = 0.743 ± 0.039 (right, fixed SHMR). See Section 5.2 for more information.