adsabs/AstroCLIMB huggingface dataset:
Paper: A Precursor to Solar Prominence Eruptions: Detection and Analysis of EUV Prominence Oscillations
Authors: William Beckwith-Chandler, Claire Foullon, Erwin Verwichte
Figure caption: Lomb–Scargle periodogram (blue) and Fourier power spectrum (red) for the 193 Å time series, δ I(t), in Interval 2. The Fourier spectrum is shown using a histogram mode. The spectra are normalized with respect to the variance of a global wavelet power spectrum, and the global significance level is shown as a dashed line.
Paper: Detection of the Temperature Dependence of the White Dwarf Mass–Radius Relation with Gravitational Redshifts
Authors: Nicole R. Crumpler, Vedant Chandra, Nadia L. Zakamska, Gautham Adamane Pallathadka, Stefan Arseneau, Nicola Gentile Fusillo, J. J. Hermes, Carles Badenes, Priyanka Chakraborty, Boris T. Gänsicke, Stephen P. Schmidt
Figure caption: The agreement between the La Plata theoretical models of WD structure and our measurements. The core composition and hydrogen layer thickness of the La Plata models varies as a function of WD mass. The model for a very cold 4000 K WD is shown in red and for a hot 40,000 K WD is shown in blue. The gravitational redshifts (top) are binned in photometric radius (left) and in spectroscopic surface gravity (right). In the bottom row, we plot the corresponding mass–radius or mass–surface gravity relations for the theoretical models and our data. We show our measurements using only the SDSS-V catalog in cyan, only the previous SDSS catalog in magenta, and the combined catalog in black. The error bars on the data come from the error on the weighted mean radial velocity plus the systematic error due to the sharp-peak bias correction, added in quadrature. The region in which most WDs must be in binary systems is shaded in gray. We find that our empirical mass–radius relation is consistent with the La Plata models.
Paper: Detection of the Temperature Dependence of the White Dwarf Mass–Radius Relation with Gravitational Redshifts
Authors: Nicole R. Crumpler, Vedant Chandra, Nadia L. Zakamska, Gautham Adamane Pallathadka, Stefan Arseneau, Nicola Gentile Fusillo, J. J. Hermes, Carles Badenes, Priyanka Chakraborty, Boris T. Gänsicke, Stephen P. Schmidt
Figure caption: The agreement between our measured gravitational redshifts and the theoretical redshifts from La Plata models at the peak of the radius (top) and surface gravity (bottom) distributions with no temperature cuts. Our measured gravitational redshift, including bias corrections, is shown in black, with the gray shaded region showing the error on this measurement. The theoretical gravitational redshift at the peak radius or peak surface gravity and the mean photometric effective temperature of the WDs in the peak is shown in green. The uncertainty on this theoretical gravitational redshift is the green shaded region. The mean measured and theoretical gravitational redshifts for the peak radius bin are 28.1 ± 0.6 and ﹩29.5{\,}_{-\,1.2}^{+\,1.0}﹩ km s−1, respectively. The mean measured and theoretical gravitational redshifts for the peak surface gravity bin are 27.3 ± 0.8 and ﹩27.5{\,}_{-\,0.3}^{+\,0.3}﹩ km s−1, respectively. The LSR and asymmetric drift-corrected radial velocities in the peak bin are shown in the blue histogram. We cannot bias-correct individual radial velocities, so the maximum of this histogram does not correspond precisely to the measured gravitational redshift.
Paper: Detection of the Temperature Dependence of the White Dwarf Mass–Radius Relation with Gravitational Redshifts
Authors: Nicole R. Crumpler, Vedant Chandra, Nadia L. Zakamska, Gautham Adamane Pallathadka, Stefan Arseneau, Nicola Gentile Fusillo, J. J. Hermes, Carles Badenes, Priyanka Chakraborty, Boris T. Gänsicke, Stephen P. Schmidt
Figure caption: Example run of the sharply peaked distribution bias simulation. The top plots show the true (blue) and noisy (orange) radius (left) and surface gravity (right) distributions. Adding noise to the true distributions flattens them. The bottom plots show the effect of this flattening on measuring gravitational redshifts. The relation between the true radius or surface gravity and the gravitational redshift is shown in black, and the noisy relation is shown in red.
Paper: Detection of the Temperature Dependence of the White Dwarf Mass–Radius Relation with Gravitational Redshifts
Authors: Nicole R. Crumpler, Vedant Chandra, Nadia L. Zakamska, Gautham Adamane Pallathadka, Stefan Arseneau, Nicola Gentile Fusillo, J. J. Hermes, Carles Badenes, Priyanka Chakraborty, Boris T. Gänsicke, Stephen P. Schmidt
Figure caption: The distribution of WD photometric effective temperatures for the cool (red) and warm (blue) subsamples. The mean photometric temperatures of the cool (red line) and warm (blue line) subsamples are 8500 and 21,500 K, respectively.
Paper: Filament Accretion and Fragmentation in the Perseus Molecular Cloud
Authors: Michael Chun-Yuan Chen, James Di Francesco, Rachel K. Friesen, Jaime E. Pineda, Paola Caselli, Adam Ginsburg, Helen Kirk, Anna Punanova
Figure caption: The median σ  v  of each filament plotted against the filament’s M lin, with the same markers as in Figure 5. The gray dashed line marks the best-fit linear regression model. The light and dark blue shaded regions show where 0.5M line,vir ≤ M line ≤ 2M line,vir, and M line ≥ 2M line,vir, respectively. The dotted line marks where M line,vir = M line. The observed σ v contains both a thermal and a nonthermal component, and the horizontal dotted line shows the σ v value of a 10 K gas with a nonthermal component that is sonic.
Paper: Filament Accretion and Fragmentation in the Perseus Molecular Cloud
Authors: Michael Chun-Yuan Chen, James Di Francesco, Rachel K. Friesen, Jaime E. Pineda, Paola Caselli, Adam Ginsburg, Helen Kirk, Anna Punanova
Figure caption: The median v LSR of each filament plotted against the filament’s M lin. The filaments belonging to each star-forming clump are marked with the symbols labeled in the legend. The value of M lin,crit at 10 K is marked by the vertical dotted line, with the shaded region representing the transcritical values of 0.5M lin,crit ≤ M lin ≤ 2M lin,crit.
Paper: Filament Accretion and Fragmentation in the Perseus Molecular Cloud
Authors: Michael Chun-Yuan Chen, James Di Francesco, Rachel K. Friesen, Jaime E. Pineda, Paola Caselli, Adam Ginsburg, Helen Kirk, Anna Punanova
Figure caption: The filament spines identified from the fits-derived NH3 spectral models in PPV space, overlaid on top of the integrated intensity maps of the NH3 (1, 1) observations, which are in units of Kelvin kilometers per second. Spines with lengths ≥10.5 pixels (three beam widths) are shown in yellow, while the rest are shown in red. The positions of the cores identified by Pattle et al. (submitted) and the Class 0/I YSOs identified by M. M. Dunham et al. (2015) are marked by the circles and pluses, respectively, selected only for those located on our filaments. The remaining labels are the same as those in Figure 1.
Paper: Filament Accretion and Fragmentation in the Perseus Molecular Cloud
Authors: Michael Chun-Yuan Chen, James Di Francesco, Rachel K. Friesen, Jaime E. Pineda, Paola Caselli, Adam Ginsburg, Helen Kirk, Anna Punanova
Figure caption: The median M lin of filaments within each star-forming clump plotted against the N(H2) PDF power-law slope of the clump measured by S. Pezzuto et al. (2021), using the same method as S. I. Sadavoy et al. (2014). The symbols are the same as those in Figure 5. The gray dashed line marks the best-fit linear regression model.
Paper: Filament Accretion and Fragmentation in the Perseus Molecular Cloud
Authors: Michael Chun-Yuan Chen, James Di Francesco, Rachel K. Friesen, Jaime E. Pineda, Paola Caselli, Adam Ginsburg, Helen Kirk, Anna Punanova
Figure caption: The interfilament standard deviation of each filament’s median v LSR within a star-forming clump plotted against the mass of the clump above N(H2) = 1 × 1022 cm−1, as measured by S. I. Sadavoy et al. (2014). The symbols are the same as those in Figure 5. The horizontal dotted line marks the isothermal sound speed of a 10 K gas.
Paper: Filament Accretion and Fragmentation in the Perseus Molecular Cloud
Authors: Michael Chun-Yuan Chen, James Di Francesco, Rachel K. Friesen, Jaime E. Pineda, Paola Caselli, Adam Ginsburg, Helen Kirk, Anna Punanova
Figure caption: The Herschel-derived H2 column density map of Perseus East (top) and West (bottom), overlaid with filled contours showing where the GBT-observed NH3 spectra are best fitted by one-component and two-component models in orange and blue, respectively. The footprints of the GAS observations are shown with the orange dashed contours. The scale bars are shown in the top right corners of each panel.
Paper: Filament Accretion and Fragmentation in the Perseus Molecular Cloud
Authors: Michael Chun-Yuan Chen, James Di Francesco, Rachel K. Friesen, Jaime E. Pineda, Paola Caselli, Adam Ginsburg, Helen Kirk, Anna Punanova
Figure caption: The top left and right panels show example vector fields that are perpendicular or parallel to a filament spine, respectively, taken from a B1 filament. The filament spine and the distance between each pixel and the spine, from which the vector fields are derived, are shown in the background. The bottom left and right panels show the ∇v LSR,⊥ and ∇v LSR,∥ maps of the same filament, respectively.
Paper: Filament Accretion and Fragmentation in the Perseus Molecular Cloud
Authors: Michael Chun-Yuan Chen, James Di Francesco, Rachel K. Friesen, Jaime E. Pineda, Paola Caselli, Adam Ginsburg, Helen Kirk, Anna Punanova
Figure caption: The NH3 (1, 1) integrated intensity maps of the six Perseus clumps in units Kelvin kilometers per second. The scale bar and beam size of each map are shown in the top left and top right corners of their panels, respectively.
Paper: Filament Accretion and Fragmentation in the Perseus Molecular Cloud
Authors: Michael Chun-Yuan Chen, James Di Francesco, Rachel K. Friesen, Jaime E. Pineda, Paola Caselli, Adam Ginsburg, Helen Kirk, Anna Punanova
Figure caption: The median ∣∇v LSR,⊥∣ of the Perseus filaments plotted against their ∣∇v LSR,∥∣ counterparts. The markers are the same as in Figure 5. The best-fitting linear regression models are represented by the gray dashed line.
Paper: SCExAO/CHARIS Near-infrared Scattered-light Imaging and Integral Field Spectropolarimetry of the AB Aurigae Protoplanetary System
Authors: Erica Dykes, Thayne Currie, Kellen Lawson, Miles Lucas, Tomoyuki Kudo, Minghan Chen, Olivier Guyon, Tyler D. Groff, Julien Lozi, Jeffrey Chilcote, Timothy D. Brandt, Sebastien Vievard, Nour Skaf, Vincent Deo, Mona El Morsy, Danielle Bovie, Taichi Uyama, Carol Grady, Michael Sitko, Jun Hashimoto, Frantz Martinache, Nemanja Jovanovic, Motohide Tamura, N. Jeremy Kasdin
Figure caption: Model azimuthal dependent values for total intensity, PI, and PF compared to measured values at 0.″25–0.″5 and 0.″5–0.″75 for a model of high porosity (p = 0.7) and low porosity (p = 0.3). All other parameters for these models are the same (see main text).
Paper: SCExAO/CHARIS Near-infrared Scattered-light Imaging and Integral Field Spectropolarimetry of the AB Aurigae Protoplanetary System
Authors: Erica Dykes, Thayne Currie, Kellen Lawson, Miles Lucas, Tomoyuki Kudo, Minghan Chen, Olivier Guyon, Tyler D. Groff, Julien Lozi, Jeffrey Chilcote, Timothy D. Brandt, Sebastien Vievard, Nour Skaf, Vincent Deo, Mona El Morsy, Danielle Bovie, Taichi Uyama, Carol Grady, Michael Sitko, Jun Hashimoto, Frantz Martinache, Nemanja Jovanovic, Motohide Tamura, N. Jeremy Kasdin
Figure caption: Mean PF vs. angle from the disk minor axis for CHARIS broadband, J, H, and K. The error bars correspond to the standard deviation of the polarization at each angle. Measurements missing from the right-hand panel (near 90° and 270°) correspond to regions with a limited field of view on the CHARIS detector.
Paper: SCExAO/CHARIS Near-infrared Scattered-light Imaging and Integral Field Spectropolarimetry of the AB Aurigae Protoplanetary System
Authors: Erica Dykes, Thayne Currie, Kellen Lawson, Miles Lucas, Tomoyuki Kudo, Minghan Chen, Olivier Guyon, Tyler D. Groff, Julien Lozi, Jeffrey Chilcote, Timothy D. Brandt, Sebastien Vievard, Nour Skaf, Vincent Deo, Mona El Morsy, Danielle Bovie, Taichi Uyama, Carol Grady, Michael Sitko, Jun Hashimoto, Frantz Martinache, Nemanja Jovanovic, Motohide Tamura, N. Jeremy Kasdin
Figure caption: Measured polarization spectra (top) and normalized (by the median surface brightness for each spectrum; middle) polarization spectra for various locations in the disk, as listed in Table 2. Comparison of measured polarization spectra and total intensity spectra at the location of AB Aur b (bottom).
Paper: SCExAO/CHARIS Near-infrared Scattered-light Imaging and Integral Field Spectropolarimetry of the AB Aurigae Protoplanetary System
Authors: Erica Dykes, Thayne Currie, Kellen Lawson, Miles Lucas, Tomoyuki Kudo, Minghan Chen, Olivier Guyon, Tyler D. Groff, Julien Lozi, Jeffrey Chilcote, Timothy D. Brandt, Sebastien Vievard, Nour Skaf, Vincent Deo, Mona El Morsy, Danielle Bovie, Taichi Uyama, Carol Grady, Michael Sitko, Jun Hashimoto, Frantz Martinache, Nemanja Jovanovic, Motohide Tamura, N. Jeremy Kasdin
Figure caption: The χ 2 distributions for models of varying dust grain porosities for total intensity, PI, and PF (top left, top right, and lower left, respectively). The cumulative χ 2 across all three data types is shown in the lower right panel. All χ 2 values are plotted in logarithmic scale due to the large range in values.
Paper: SCExAO/CHARIS Near-infrared Scattered-light Imaging and Integral Field Spectropolarimetry of the AB Aurigae Protoplanetary System
Authors: Erica Dykes, Thayne Currie, Kellen Lawson, Miles Lucas, Tomoyuki Kudo, Minghan Chen, Olivier Guyon, Tyler D. Groff, Julien Lozi, Jeffrey Chilcote, Timothy D. Brandt, Sebastien Vievard, Nour Skaf, Vincent Deo, Mona El Morsy, Danielle Bovie, Taichi Uyama, Carol Grady, Michael Sitko, Jun Hashimoto, Frantz Martinache, Nemanja Jovanovic, Motohide Tamura, N. Jeremy Kasdin
Figure caption: Synthetic PF maps at H band for the high and low porosity models (left and middle) compared to the measured polarization map (right).
Paper: SCExAO/CHARIS Near-infrared Scattered-light Imaging and Integral Field Spectropolarimetry of the AB Aurigae Protoplanetary System
Authors: Erica Dykes, Thayne Currie, Kellen Lawson, Miles Lucas, Tomoyuki Kudo, Minghan Chen, Olivier Guyon, Tyler D. Groff, Julien Lozi, Jeffrey Chilcote, Timothy D. Brandt, Sebastien Vievard, Nour Skaf, Vincent Deo, Mona El Morsy, Danielle Bovie, Taichi Uyama, Carol Grady, Michael Sitko, Jun Hashimoto, Frantz Martinache, Nemanja Jovanovic, Motohide Tamura, N. Jeremy Kasdin
Figure caption: The radius-squared broadband image of the AB Aur disk with locations at which we extract polarization spectra denoted by different symbols.
Paper: SCExAO/CHARIS Near-infrared Scattered-light Imaging and Integral Field Spectropolarimetry of the AB Aurigae Protoplanetary System
Authors: Erica Dykes, Thayne Currie, Kellen Lawson, Miles Lucas, Tomoyuki Kudo, Minghan Chen, Olivier Guyon, Tyler D. Groff, Julien Lozi, Jeffrey Chilcote, Timothy D. Brandt, Sebastien Vievard, Nour Skaf, Vincent Deo, Mona El Morsy, Danielle Bovie, Taichi Uyama, Carol Grady, Michael Sitko, Jun Hashimoto, Frantz Martinache, Nemanja Jovanovic, Motohide Tamura, N. Jeremy Kasdin
Figure caption: Gallery of synthetic PF maps for different models at inclinations of 15°–45°, showing the effect of varying the dust porosity from p = 0.3 to p = 0.8.
Paper: SCExAO/CHARIS Near-infrared Scattered-light Imaging and Integral Field Spectropolarimetry of the AB Aurigae Protoplanetary System
Authors: Erica Dykes, Thayne Currie, Kellen Lawson, Miles Lucas, Tomoyuki Kudo, Minghan Chen, Olivier Guyon, Tyler D. Groff, Julien Lozi, Jeffrey Chilcote, Timothy D. Brandt, Sebastien Vievard, Nour Skaf, Vincent Deo, Mona El Morsy, Danielle Bovie, Taichi Uyama, Carol Grady, Michael Sitko, Jun Hashimoto, Frantz Martinache, Nemanja Jovanovic, Motohide Tamura, N. Jeremy Kasdin
Figure caption: Gallery of synthetic PF maps for different models at inclinations of 15°–45°, showing the effect of varying the reference scale height from 0.0125 to 0.05.
Paper: SCExAO/CHARIS Near-infrared Scattered-light Imaging and Integral Field Spectropolarimetry of the AB Aurigae Protoplanetary System
Authors: Erica Dykes, Thayne Currie, Kellen Lawson, Miles Lucas, Tomoyuki Kudo, Minghan Chen, Olivier Guyon, Tyler D. Groff, Julien Lozi, Jeffrey Chilcote, Timothy D. Brandt, Sebastien Vievard, Nour Skaf, Vincent Deo, Mona El Morsy, Danielle Bovie, Taichi Uyama, Carol Grady, Michael Sitko, Jun Hashimoto, Frantz Martinache, Nemanja Jovanovic, Motohide Tamura, N. Jeremy Kasdin
Figure caption: Wavelength-collapsed, median-combined PF across AB Aur’s disk in broadband, and the J, H, and K bands.
Paper: Semisupervised Learning for Detecting Inverse Compton Emission in Galaxy Clusters
Authors: Sheng-Chieh Lin, Yuanyuan Su, Fabio Gastaldello, Nathan Jacobs
Figure caption: An example of synthetic NuSTAR spectrum consists of thermal emission and four background models. The synthetic spectrum shown as black points is generated using FAKEIT for a (source plus background) model shown as the black curve. The cluster emission model is adopted from the thermal parameters of the Coma cluster, determined from the best fit of an absorbed two-temperature model of tbabs*(apec+apec) (F. Gastaldello et al. 2015). The red spectrum (APEC) is the hotter component at 9.03 keV, and the blue spectrum is the cooler one at 1.02 keV. Several background components (brown) are taken into account including instrumental continuum background (labeled as instr. continuum, dotted), focused cosmic X-ray background (labeled as focused CXB, dashed), aperture background (labeled as aperture, solid), and instrumental lines and solar reflected component (labeled as instr. line, dashed–dotted).
Paper: Semisupervised Learning for Detecting Inverse Compton Emission in Galaxy Clusters
Authors: Sheng-Chieh Lin, Yuanyuan Su, Fabio Gastaldello, Nathan Jacobs
Figure caption: Schematic diagram of the algorithm. (a) Demonstration of the training and testing processes. The dashed arrows show the training work flow that ends in the rounded block of L  r  + L  c , which represents the sum of the reconstruction loss and the constraining loss. The constraining loss, as shown in Equation (1), is obtained by calculating the MAE between the predicted values and the input values of the apec parameters (shown as the middle block labeled APEC). The solid arrows indicate the testing procedure in which we compare the input spectra with the reconstructed spectra using the mean squared error (MSE). (b) Detailed layouts of the encoder and decoder. Note that the skip mechanism is applied to both the convolutional and deconvolutional blocks.
Paper: Semisupervised Learning for Detecting Inverse Compton Emission in Galaxy Clusters
Authors: Sheng-Chieh Lin, Yuanyuan Su, Fabio Gastaldello, Nathan Jacobs
Figure caption: The spectrum number count as a function of anomaly score R  a . The vertical dashed line shows the threshold of R  a  = 0.00042 for classification decision making, above which spectra are classified as containing the IC signal, while those below it are classified as pure thermal spectra. True 2T and true 1T+IC data are marked in blue and red, respectively. Two panels show the results from two different AEs: upper—CAE; lower—ordinary AE.
Paper: SCExAO/CHARIS Near-infrared Scattered-light Imaging and Integral Field Spectropolarimetry of the AB Aurigae Protoplanetary System
Authors: Erica Dykes, Thayne Currie, Kellen Lawson, Miles Lucas, Tomoyuki Kudo, Minghan Chen, Olivier Guyon, Tyler D. Groff, Julien Lozi, Jeffrey Chilcote, Timothy D. Brandt, Sebastien Vievard, Nour Skaf, Vincent Deo, Mona El Morsy, Danielle Bovie, Taichi Uyama, Carol Grady, Michael Sitko, Jun Hashimoto, Frantz Martinache, Nemanja Jovanovic, Motohide Tamura, N. Jeremy Kasdin
Figure caption: Gallery of χ 2 distributions comparing the azimuthal profiles of our MCFOST models to our total intensity data (first row), PI data (second row), and PF (third row) for each of the free parameters. The cumulative χ 2 distribution of all three data types is shown in the fourth row. The χ 2 values are plotted on a logarithmic scale due to the large range.
Paper: Semisupervised Learning for Detecting Inverse Compton Emission in Galaxy Clusters
Authors: Sheng-Chieh Lin, Yuanyuan Su, Fabio Gastaldello, Nathan Jacobs
Figure caption: Distributions of the MSE (anomaly score R  a ) of the spectra reconstruction for true 1T+IC (red) and true 2T (blue) spectra, returned by CAE.
Paper: SCExAO/CHARIS Near-infrared Scattered-light Imaging and Integral Field Spectropolarimetry of the AB Aurigae Protoplanetary System
Authors: Erica Dykes, Thayne Currie, Kellen Lawson, Miles Lucas, Tomoyuki Kudo, Minghan Chen, Olivier Guyon, Tyler D. Groff, Julien Lozi, Jeffrey Chilcote, Timothy D. Brandt, Sebastien Vievard, Nour Skaf, Vincent Deo, Mona El Morsy, Danielle Bovie, Taichi Uyama, Carol Grady, Michael Sitko, Jun Hashimoto, Frantz Martinache, Nemanja Jovanovic, Motohide Tamura, N. Jeremy Kasdin
Figure caption: Gallery of synthetic PF maps for different models at inclinations of 15°–45°, showing the effect of varying the disk mass from 10−5 M ⊙ to 10−4 M ⊙.
Paper: Cosmic-Ray North–South Anisotropy: Rigidity Spectrum and Solar Cycle Variations Observed by Ground-based Muon Detectors
Authors: M. Kozai, Y. Hayashi, K. Fujii, K. Munakata, C. Kato, N. Miyashita, A. Kadokura, R. Kataoka, S. Miyake, M. L. Duldig, J. E. Humble, K. Iwai
Figure caption: Temporal variations of the solar activity, interplanetary, and GCR modulation parameters. (a) Yearly averages of the magnitude B [nT] and spiral angle ψ of the IMF. (b) Solar wind (SW) speed V [km s−1] for each year and X-class flare occurrence rate every week. (c) Radial density gradients [%/au (astronomical units)] and (d) diffusion coefficients [1022 cm2 s−1] of (open circles) ∼30 GV and (filled circles) ∼130 GV GCRs derived from the yearly NS anisotropy.
Paper: Cosmic-Ray North–South Anisotropy: Rigidity Spectrum and Solar Cycle Variations Observed by Ground-based Muon Detectors
Authors: M. Kozai, Y. Hayashi, K. Fujii, K. Munakata, C. Kato, N. Miyashita, A. Kadokura, R. Kataoka, S. Miyake, M. L. Duldig, J. E. Humble, K. Iwai
Figure caption: Each panel shows yearly mean rigidity spectra of the NS anisotropy [%] in the solar activity’s ascending (Asc.) or descending (Desc.) phases in solar cycle 23 or 24, respectively.
Paper: Cosmic-Ray North–South Anisotropy: Rigidity Spectrum and Solar Cycle Variations Observed by Ground-based Muon Detectors
Authors: M. Kozai, Y. Hayashi, K. Fujii, K. Munakata, C. Kato, N. Miyashita, A. Kadokura, R. Kataoka, S. Miyake, M. L. Duldig, J. E. Humble, K. Iwai
Figure caption: Probability density distribution projected onto the θ 3 − θ 4 parameter space (upper panel) and 10 random spectra (lower panel) for the Gaussian process with a hyperparameter (a) b = 0.4 or (b) b = 1.0 ﹩[{\mathrm{log}}_{10}(\mathrm{GV})﹩], respectively. Other hyperparameters are set at common values, θ  c  = 0.15% and σ  G  = 0.1%, for both cases (a) and (b).
Paper: Cosmic-Ray North–South Anisotropy: Rigidity Spectrum and Solar Cycle Variations Observed by Ground-based Muon Detectors
Authors: M. Kozai, Y. Hayashi, K. Fujii, K. Munakata, C. Kato, N. Miyashita, A. Kadokura, R. Kataoka, S. Miyake, M. L. Duldig, J. E. Humble, K. Iwai
Figure caption: Conditional distributions of the (a) likelihood of observed data and (b) posterior probability of Bayesian estimation, each in θ 3 − θ 4 space for the sample year 2015. Other parameters, θ  k  for k ≠ 3 or 4, are fixed at those in the mean vector Θ of the posterior distribution. Each distribution is normalized so that its integration in the θ 3 − θ 4 space is equal to 1.