adsabs/AstroCLIMB huggingface dataset:
Paper: An Unsupervised Machine Learning-based Algorithm for Detecting Weak Impulsive Narrowband Quiet Sun Emissions and Characterizing Their Morphology
Authors: Shabbir Bawaji, Ujjaini Alam, Surajit Mondal, Divya Oberoi, Ayan Biswas
Figure caption: Distribution of the WINQSEs detected in a region of diameter 40′ centered on the Sun for the 20200620 data set at 120.52 MHz.
Paper: An Unsupervised Machine Learning-based Algorithm for Detecting Weak Impulsive Narrowband Quiet Sun Emissions and Characterizing Their Morphology
Authors: Shabbir Bawaji, Ujjaini Alam, Surajit Mondal, Divya Oberoi, Ayan Biswas
Figure caption: The top panel shows the contours around the features detected at a particular time for the median subtracted 120.52 MHz quiet Sun data set. The bottom panel shows four of these features in detail. We can see that the first feature (left-hand panel) is quite isolated, the second feature (middle panel) is semi-isolated, with some distortion in contours due to the proximity of nearby features, and the third and fourth features (right-hand panel), are so close together that the contours around them are joined.
Paper: An Unsupervised Machine Learning-based Algorithm for Detecting Weak Impulsive Narrowband Quiet Sun Emissions and Characterizing Their Morphology
Authors: Shabbir Bawaji, Ujjaini Alam, Surajit Mondal, Divya Oberoi, Ayan Biswas
Figure caption: The left-hand panel show the median image for the 20171127 data set, with the active region marked by a green dot. The right-hand panel shows the median image for the 20200620 data set at 120.52 MHz frequency, with the three persistent peak positions marked with green dots.
Paper: An Unsupervised Machine Learning-based Algorithm for Detecting Weak Impulsive Narrowband Quiet Sun Emissions and Characterizing Their Morphology
Authors: Shabbir Bawaji, Ujjaini Alam, Surajit Mondal, Divya Oberoi, Ayan Biswas
Figure caption: The distance of the centroid of solar emission from a reference pixel for each of the time slices used for 20200620. The red-dashed lines represent the boundaries of the adjacent scans. As expected, sudden jumps in the solar centroid location lie at scan boundaries, and the variations inside a scan are smoother and much smaller.
Paper: An Unsupervised Machine Learning-based Algorithm for Detecting Weak Impulsive Narrowband Quiet Sun Emissions and Characterizing Their Morphology
Authors: Shabbir Bawaji, Ujjaini Alam, Surajit Mondal, Divya Oberoi, Ayan Biswas
Figure caption: The left-hand panel shows the solar image at a particular time for the 20200620 data set at 120.52 MHz, the middle panel shows the median image over time for the entire data set, while the right panel shows the median subtracted image for the same time slice as shown in the left-hand panel.
Paper: An Unsupervised Machine Learning-based Algorithm for Detecting Weak Impulsive Narrowband Quiet Sun Emissions and Characterizing Their Morphology
Authors: Shabbir Bawaji, Ujjaini Alam, Surajit Mondal, Divya Oberoi, Ayan Biswas
Figure caption: Overall flowchart to identify and characterize the low level peaks seen in solar radio images.
Paper: Early Planet Formation in Embedded Disks (eDisk). IX. High-resolution ALMA Observations of the Class 0 Protostar R CrA IRS5N and Its Surroundings
Authors: Rajeeb Sharma, Jes K. Jørgensen, Sacha Gavino, Nagayoshi Ohashi, John J. Tobin, Zhe-Yu Daniel Lin, Zhi-Yun Li, Shigehisa Takakuwa, Chang Won Lee, Jinshi Sai (Insa Choi), Woojin Kwon, Itziar de Gregorio-Monsalvo, Alejandro Santamaría-Miranda, Hsi-Wei Yen, Yuri Aikawa, Yusuke Aso, Shih-Ping Lai, Jeong-Eun Lee, Leslie W. Looney, Nguyen Thi Phuong, Travis J. Thieme, Jonathan P. Williams
Figure caption: (a) 1.3 mm continuum images of R CrA IRS5N and IRS5 sources with a robust paramater of 0.5. (b) Zoomed-in view of the IRS5N disk. (c) Zoomed-in view of IRS5a and its companion IRS5b. (d) and (e) show further zoomed-in views of the individual sources of the IRS5 binary. The contour levels are 5σ, 10σ, 20σ, 40σ, and 80σ with σ = 0.016 mJy beam−1. The synthesized beam is shown in white in the bottom right corner with a beam size of 0.″052 × 0.″035 and a position angle of 75.°4. The color stretch used for the images is arcsinh to cover the dynamic range between the sources.
Paper: Early Planet Formation in Embedded Disks (eDisk). IX. High-resolution ALMA Observations of the Class 0 Protostar R CrA IRS5N and Its Surroundings
Authors: Rajeeb Sharma, Jes K. Jørgensen, Sacha Gavino, Nagayoshi Ohashi, John J. Tobin, Zhe-Yu Daniel Lin, Zhi-Yun Li, Shigehisa Takakuwa, Chang Won Lee, Jinshi Sai (Insa Choi), Woojin Kwon, Itziar de Gregorio-Monsalvo, Alejandro Santamaría-Miranda, Hsi-Wei Yen, Yuri Aikawa, Yusuke Aso, Shih-Ping Lai, Jeong-Eun Lee, Leslie W. Looney, Nguyen Thi Phuong, Travis J. Thieme, Jonathan P. Williams
Figure caption: Overview of all the molecular lines detected toward IRS5N and IRS5. For each molecule, the moment-0 map is shown on the left and the moment-1 map is shown on the right. The cross marks show the peak of the continuum emission of IRS5N and the binary IRS5. The maps are created by integrating over the velocity ranges of 3.68–9.53 km s−1, −5.38–20.65 km s−1, 0.51–12.03 km s−1, 2.06–8.76 km s−1, 3.68–7.36 km s−1, and 3.40–7.42 km s−1 for C18O, 12CO, 13CO, H2CO (30,3–20,2), H2CO (32,1–22,0), and H2CO (32,2–22,1), respectively. The synthesized beam is shown in black in the bottom right corner of each image, enclosed by a square.
Paper: Early Planet Formation in Embedded Disks (eDisk). IX. High-resolution ALMA Observations of the Class 0 Protostar R CrA IRS5N and Its Surroundings
Authors: Rajeeb Sharma, Jes K. Jørgensen, Sacha Gavino, Nagayoshi Ohashi, John J. Tobin, Zhe-Yu Daniel Lin, Zhi-Yun Li, Shigehisa Takakuwa, Chang Won Lee, Jinshi Sai (Insa Choi), Woojin Kwon, Itziar de Gregorio-Monsalvo, Alejandro Santamaría-Miranda, Hsi-Wei Yen, Yuri Aikawa, Yusuke Aso, Shih-Ping Lai, Jeong-Eun Lee, Leslie W. Looney, Nguyen Thi Phuong, Travis J. Thieme, Jonathan P. Williams
Figure caption: Zoomed-in moment-0 map (left) and moment-1 map (right) of the C18O (J = 2–1) emission toward IRS5N created with the robust value of 0.5. The overlaid contours show continuum emission from 3σ to 192σ, and each contour doubles the previous σ level. The maps are created by integrating over the velocity ranges of 3.68–9.53 km s−1. The synthesized beam size for the C18O emission is 0.″11 × 0.″ 08.
Paper: Early Planet Formation in Embedded Disks (eDisk). IX. High-resolution ALMA Observations of the Class 0 Protostar R CrA IRS5N and Its Surroundings
Authors: Rajeeb Sharma, Jes K. Jørgensen, Sacha Gavino, Nagayoshi Ohashi, John J. Tobin, Zhe-Yu Daniel Lin, Zhi-Yun Li, Shigehisa Takakuwa, Chang Won Lee, Jinshi Sai (Insa Choi), Woojin Kwon, Itziar de Gregorio-Monsalvo, Alejandro Santamaría-Miranda, Hsi-Wei Yen, Yuri Aikawa, Yusuke Aso, Shih-Ping Lai, Jeong-Eun Lee, Leslie W. Looney, Nguyen Thi Phuong, Travis J. Thieme, Jonathan P. Williams
Figure caption: Fitting of the SED of IRS5N with a 1D radiative transfer model. The filled red circles represent SED values over 60 μm that are fit by the model. The open red circles represent the remaining SED values we used as input. The solid blue line represents the fit given by the model. The dashed blue line shows that the model does not fit this part of the SED.
Paper: As Simple as Possible but No Simpler: Optimizing the Performance of Neural Net Emulators for Galaxy SED Fitting
Authors: Elijah P. Mathews, Joel Leja, Joshua S. Speagle, 佳士 沈, Benjamin D. Johnson, Justus Gibson, Erica J. Nelson, Katherine A. Suess, Sandro Tacchella, Katherine E. Whitaker, Bingjie Wang, 冰洁 王
Figure caption: ECDFs for the discrepancy statistic for the cumulative stellar mass formed M *,formed, diffuse dust optical depth  τ 2, AGN dust optical depth τ AGN, and gas-phase metallicity Z gas. This is evaluated between the 1024 node-per-layer emulator and another emulator. As ANN width increases, the ECDF tends to asymptotically approach the ECDF reached by the 1024 node-per-layer fit, which denotes the distribution of discrepancies encountered from sampling variance alone. The CDF of a standard normal is shown for reference and to demonstrate the non-Gaussianity of the distributions of discrepancies. Solid lines denote architectures deemed sufficiently accurate and precise for SED fitting in this work, while dashed–dotted lines denote emulators deemed marginally sufficient and dotted lines denoted emulators deemed insufficient.
Paper: As Simple as Possible but No Simpler: Optimizing the Performance of Neural Net Emulators for Galaxy SED Fitting
Authors: Elijah P. Mathews, Joel Leja, Joshua S. Speagle, 佳士 沈, Benjamin D. Johnson, Justus Gibson, Erica J. Nelson, Katherine A. Suess, Sandro Tacchella, Katherine E. Whitaker, Bingjie Wang, 冰洁 王
Figure caption: A comparison between posteriors recovered from 1000 Prospector fits to 3D-HST photometry, run with a 1024 node-per-layer emulator and with FSPS, to verify the ability of emulators to recover posteriors consistent with FSPS. Plots are shown for the stellar mass formed M *,formed, diffuse dust optical depth τ 2, stellar metallicity Z *, and dust power-law index n (top four panels), in addition to the SFR for the most recent 30 Myr and the mass-weighted age  〈t〉 m , which are derived parameters (bottom two panels). The posterior median from the FSPS-based fit is shown on the x-axis and the posterior median from the emulator-based fit is shown on the y-axis. The gold and blue shaded regions enclose the middle 68th and 95th percentiles of the differences in posterior medians, while the black line denotes the median difference. Shown in pink is a typical posterior width for the plotted parameter.
Paper: As Simple as Possible but No Simpler: Optimizing the Performance of Neural Net Emulators for Galaxy SED Fitting
Authors: Elijah P. Mathews, Joel Leja, Joshua S. Speagle, 佳士 沈, Benjamin D. Johnson, Justus Gibson, Erica J. Nelson, Katherine A. Suess, Sandro Tacchella, Katherine E. Whitaker, Bingjie Wang, 冰洁 王
Figure caption: Rate of 3σ  outliers (i.e., rate of  ∣Q  i;j,k ∣ ≥ 3 discrepancies) for four of the fitted parameters. We see the 3σ outlier rates generally approach the rate found in the 1024 node-per-layer emulator, which is caused only by sampling variance, as network width increases.
Paper: As Simple as Possible but No Simpler: Optimizing the Performance of Neural Net Emulators for Galaxy SED Fitting
Authors: Elijah P. Mathews, Joel Leja, Joshua S. Speagle, 佳士 沈, Benjamin D. Johnson, Justus Gibson, Erica J. Nelson, Katherine A. Suess, Sandro Tacchella, Katherine E. Whitaker, Bingjie Wang, 冰洁 王
Figure caption: An example of the emulator stitching method proposed in Section 4.3 to create a composite emulator spanning the redshift range of 0 ≤ z ≤ 12. To construct the composite emulator, six separate emulators are trained on slightly overlapping redshift domains (whose limits are represented by dashed lines), and they are then given a coefficient a  i (z) to represent the contribution they should make to the overall flux estimate. Each emulator in this example covers a nominal redshift domain of  Δz ≈ 2.5, similar to the redshift domain covered by the emulator in this work, and thus, would likely have similar emulation precision and execution time.
Paper: As Simple as Possible but No Simpler: Optimizing the Performance of Neural Net Emulators for Galaxy SED Fitting
Authors: Elijah P. Mathews, Joel Leja, Joshua S. Speagle, 佳士 沈, Benjamin D. Johnson, Justus Gibson, Erica J. Nelson, Katherine A. Suess, Sandro Tacchella, Katherine E. Whitaker, Bingjie Wang, 冰洁 王
Figure caption: A demonstration of the non-Gaussianity of the emulation errors. Plotted in gray is a histogram of the test set emulation errors for the 1024 node-per-layer emulator’s JWST NIRCam F115W filter, while plotted in gold, red, blue, and green are the probability density functions for normal, Student’s t(ν = 4), Laplace, and logistic distributions for visual comparison, whose location and scales are set to the mean and standard deviation of emulation errors for this filter.
Paper: As Simple as Possible but No Simpler: Optimizing the Performance of Neural Net Emulators for Galaxy SED Fitting
Authors: Elijah P. Mathews, Joel Leja, Joshua S. Speagle, 佳士 沈, Benjamin D. Johnson, Justus Gibson, Erica J. Nelson, Katherine A. Suess, Sandro Tacchella, Katherine E. Whitaker, Bingjie Wang, 冰洁 王
Figure caption: The posteriors for the fits to Galaxies A and B as described in Section 4.2. Left/right panels show the posteriors for the fits to Galaxy A/B for the total stellar mass formed  ﹩{\mathrm{log}}_{10}({M}_{* ,\mathrm{formed}}/{M}_{\odot })﹩ and the mass-weighted age  〈t〉m. The thick dashed black line denotes the true parameter value, while the thin colored dashed lines show the median of the posterior along with the  ±1σ quantiles.
Paper: As Simple as Possible but No Simpler: Optimizing the Performance of Neural Net Emulators for Galaxy SED Fitting
Authors: Elijah P. Mathews, Joel Leja, Joshua S. Speagle, 佳士 沈, Benjamin D. Johnson, Justus Gibson, Erica J. Nelson, Katherine A. Suess, Sandro Tacchella, Katherine E. Whitaker, Bingjie Wang, 冰洁 王
Figure caption: The emulation precision of the two emulators used to fit the two mock galaxies described in Section 4.2. Plotted in red is the emulation error for the emulator whose training set used the thinner prior distributions, and plotted in blue is the emulation error for the 1024 node-per-layer emulator described in this work. In both cases, the emulation error is evaluated using the true parameter values for the mock observations. We see that the precision of the thin tail emulator is dramatically worse for Galaxy B, whose SFH parameters are extreme, while the thick tail emulator does well for both galaxies.
Paper: As Simple as Possible but No Simpler: Optimizing the Performance of Neural Net Emulators for Galaxy SED Fitting
Authors: Elijah P. Mathews, Joel Leja, Joshua S. Speagle, 佳士 沈, Benjamin D. Johnson, Justus Gibson, Erica J. Nelson, Katherine A. Suess, Sandro Tacchella, Katherine E. Whitaker, Bingjie Wang, 冰洁 王
Figure caption: A test of Prospector 's ability to recover accurate estimates of various parameters from mock observations when paired with the 1024 node-per-layer emulator. Results are displayed similarly to the FSPS comparisons shown in Figure 7, with spreads somewhat wider than those found in that test.
Paper: As Simple as Possible but No Simpler: Optimizing the Performance of Neural Net Emulators for Galaxy SED Fitting
Authors: Elijah P. Mathews, Joel Leja, Joshua S. Speagle, 佳士 沈, Benjamin D. Johnson, Justus Gibson, Erica J. Nelson, Katherine A. Suess, Sandro Tacchella, Katherine E. Whitaker, Bingjie Wang, 冰洁 王
Figure caption: A test of Prospector 's ability to recover accurate estimates of various parameters from mock observations when paired with FSPS, similar to Figure 8.
Paper: Three-dimensional General-relativistic Simulations of Neutrino-driven Winds from Magnetized Proto–Neutron Stars
Authors: Dhruv K. Desai, Daniel M. Siegel, Brian D. Metzger
Figure caption: Histograms of various quantities relevant to r-process nucleosynthesis as measured through a 60 km spherical shell. The left panel shows the unmagnetized (no-B, black) and weakly magnetized (lo-B, blue) models, while the strongly magnetized model (hi-B) is shown on the right, broken down separately into the polar (purple) and equatorial (red) outflows, respectively (defined over the same angular domains as in Figure 5). For the unmagnetized models we show the results over the full time interval 25–55 ms, because the outflow is approximately time stationary, while for the magnetized models we separately bin results for 25–35 ms (thin lines) and 45–55 ms (thick lines). At a given time, the quantities are weighted pointwise on the spherical grid by the local mass outflow, where they are binned and normalized by the total mass outflow through the entire surface over the time interval. We approximate the outflow expansion time (Equation (4)) as ﹩{t}_{\exp }=R/v(R)﹩, where v(R) is the total wind speed measured at the shell. Threshold values for η (Equation (5)) required for neutron captures to reach the second (yellow dashed vertical line) and third (green dotted vertical line) r-process peaks (Hoffman et al. 1997) are indicated for comparison.
Paper: Three-dimensional General-relativistic Simulations of Neutrino-driven Winds from Magnetized Proto–Neutron Stars
Authors: Dhruv K. Desai, Daniel M. Siegel, Brian D. Metzger
Figure caption: Top: closed-zone ejection timescale t ej (Equation (9)) computed just after magnetic field initialization (left) and 30 ms later (right) for model hi-B in a slice through the y = 0 plane. Bottom: snapshots from model hi-B showing (left) the final entropy s proj of the closed-zone material achieved after a time t ej (Equation (9) from Thompson 2003 applied to the initial snapshot) in comparison to (right) the actual entropy s from the simulation at t ≈ 55 ms after magnetic field initialization. The red contour represents the neutrinosphere surface (﹩{\tau }_{{\bar{\nu }}_{e}}=1﹩). The analytic estimate is roughly consistent with the actual entropy achieved in the trapped zone of the wind.
Paper: Three-dimensional General-relativistic Simulations of Neutrino-driven Winds from Magnetized Proto–Neutron Stars
Authors: Dhruv K. Desai, Daniel M. Siegel, Brian D. Metzger
Figure caption: Cross section of the y = 0 magnetic dipole axis plane for the lo-B (left) and hi-B runs (right) ≈55 ms after the magnetic field is initialized, showing the ratios of the temperature T (top) and density ρ (bottom) to their respective critical values T  B  and ρ  B  below which quantizing effects of the magnetic field on the equation of state and weak interactions are expected (Equations (11) and (12)). Since T/T  B  > 1 everywhere, electrons and positrons populate many Landau levels, even in the regime where ρ < ρ  B . The magnetic winds are thus in the nonquantizing regime, justifying our negligence of magnetic field effects on the equation of state and weak interactions. The red contour indicates the ﹩{\tau }_{{\bar{\nu }}_{e}}=1﹩ neutrinosphere surface.
Paper: Three-dimensional General-relativistic Simulations of Neutrino-driven Winds from Magnetized Proto–Neutron Stars
Authors: Dhruv K. Desai, Daniel M. Siegel, Brian D. Metzger
Figure caption: Equatorial plane (z = 0) cross section at three snapshots in time (≈31 ms, 55 ms, 64 ms after dipole magnetic field initialization) for models lo-B (shown in the x < 0 domain) and hi-B (shown in the x > 0 domain). The color represents the relative level of ∇ ·  B  violations, where Δx is the grid spacing, and B is the overall strength of the magnetic field. While the constraint transport scheme maintains ∇ ·  B  to machine precision interior to the refinement level boundaries, spurious violations are introduced at the refinement boundaries due to interpolation operations.
Paper: Three-dimensional General-relativistic Simulations of Neutrino-driven Winds from Magnetized Proto–Neutron Stars
Authors: Dhruv K. Desai, Daniel M. Siegel, Brian D. Metzger
Figure caption: Comparison of wind properties with and without imposing reflection symmetry across the equatorial plane. Shown are wind cross sections in the plane of the magnetic dipole axis for specific entropies (left panel) and magnetic-to-fluid pressure ratios (right panel) time averaged over the interval t ≃ 30–35 ms after the B-field is initialized. For each panel the simulation is run across the full θ ∈ [0, π] domain (left; model no-sym-B) and reflection symmetry across the z = 0 plane is employed (right; model sym-B).
Paper: Three-dimensional General-relativistic Simulations of Neutrino-driven Winds from Magnetized Proto–Neutron Stars
Authors: Dhruv K. Desai, Daniel M. Siegel, Brian D. Metzger
Figure caption: Vertical scale height as a function of radius of the magnetic field B (black) and neutrino optical depth ﹩{\tau }_{{\bar{\nu }}_{e}}﹩ (blue) for model hi-B, normalized by the grid step size Δx. The radial profiles correspond to a slice through the magnetic dipole axis (y = 0 plane), averaged over the polar angle between θ = 0° and θ = 45°, and time averaged over the first 4 ms after the magnetic field is initialized. The discontinuities at 15 km and 30 km reflect refinement level boundaries.
Paper: Three-dimensional General-relativistic Simulations of Neutrino-driven Winds from Magnetized Proto–Neutron Stars
Authors: Dhruv K. Desai, Daniel M. Siegel, Brian D. Metzger
Figure caption: Same as Figure 7, but for the total specific energy E tot, including the effects of magnetic tension (Equation (6)). The energy grows in the equatorial belt due to neutrino heating of matter trapped in the closed zone, becoming positive by the final snapshots across a greater region extending to smaller radii approaching the PNS surface. As this high-entropy matter expands through the seed formation region (outside the cyan contour) it can potentially generate the conditions necessary for second- or third-peak r-process nucleosynthesis.
Paper: Three-dimensional General-relativistic Simulations of Neutrino-driven Winds from Magnetized Proto–Neutron Stars
Authors: Dhruv K. Desai, Daniel M. Siegel, Brian D. Metzger
Figure caption: Strength of the poloidal (left) and toroidal (right) magnetic field components for model hi-B approximately 55 ms after initialization of the magnetic field. The red contour indicates the location of the neutrinosphere.
Paper: The Gamma-Ray Pulsar Phenomenology in View of 3D Kinetic Global Magnetosphere Models
Authors: Constantinos Kalapotharakos, Zorawar Wadiasingh, Alice K. Harding, Demosthenes Kazanas
Figure caption: A schematic representation of the voltage, V, the particles encounter, in the indicated color scale, as a function of w and ﹩{{ \mathcal F }}_{\mathrm{SZ}}﹩. The red arrows show the direction toward higher FF-ness. The big dots show our models on the ﹩{{ \mathcal F }}_{\mathrm{SZ}}-w﹩ space, and each of them is numbered according to the numbers of our models (see Table 1). We also note that the solid line that connects them shows the covered pathway schematically and is not related to the axes of the ﹩(w,{{ \mathcal F }}_{\mathrm{SZ}})﹩ space. The various dashed lines demonstrate the different pathways that trace the same FF-ness, i.e., V values.
Paper: The Gamma-Ray Pulsar Phenomenology in View of 3D Kinetic Global Magnetosphere Models
Authors: Constantinos Kalapotharakos, Zorawar Wadiasingh, Alice K. Harding, Demosthenes Kazanas
Figure caption: The ϵ cut values for the separatrix zone models, α = 45° as a function of the model number. Each solid and dashed line corresponds to different YP and MP ﹩\dot{{ \mathcal E }}﹩ values, respectively. The indicated color scale denotes the increasing direction of ﹩\dot{{ \mathcal E }}﹩. Nonetheless, for clarity, the color scale has been adjusted differently for the YP and MP parameter sets to cover the corresponding entire ﹩\dot{{ \mathcal E }}﹩ range. The gray zone establishes the Fermi-compatible models.
Paper: The Gamma-Ray Pulsar Phenomenology in View of 3D Kinetic Global Magnetosphere Models
Authors: Constantinos Kalapotharakos, Zorawar Wadiasingh, Alice K. Harding, Demosthenes Kazanas
Figure caption: The sky maps for the separatrix zone model of YPs with α = 15°. The ﹩\dot{{ \mathcal E }}﹩ increases from left-hand to right-hand while the FF-ness increases from top to bottom. More specifically, the plotted sky maps correspond to the model numbers 1, 4, and 6 and ﹩\dot{{ \mathcal E }}={10}^{34},\,{10}^{36}﹩, and 1038 erg s−1. The color scale denotes the differential luminosity per steradian.