adsabs/AstroCLIMB huggingface dataset:
Paper: The Molecular Composition of Shadowed Proto-solar Disk Midplanes Beyond the Water Snowline
Authors: Shota Notsu, Kazumasa Ohno, Takahiro Ueda, Catherine Walsh, Christian Eistrup, Hideko Nomura
Figure caption: The time evolution of the radial profiles of fractional abundances with respect to total hydrogen nuclei densities for H2O (top panels), CO (second-row panels), CO2 (third-row panels), and O2 (bottom panels). The dashed and solid lines show the profiles for gaseous and icy molecules, respectively. The green, blue, red, and black lines show the profiles for different evolutional stages (t =104, 105, 5 × 105, and 106 yr), respectively. These panels show the results when assuming molecular initial abundances (the “inheritance” scenario) and for ξ CR(r) =1.0 × 10−17 [s−1]. The left panels show those for the disk midplane with the monotonically decreasing temperature and density structure (f =1.0), and the right panels show the results for the shadowed disk midplane (f =0.03).
Paper: The Molecular Composition of Shadowed Proto-solar Disk Midplanes Beyond the Water Snowline
Authors: Shota Notsu, Kazumasa Ohno, Takahiro Ueda, Catherine Walsh, Christian Eistrup, Hideko Nomura
Figure caption: The radial profiles of gas-phase fractional abundances with respect to total hydrogen nuclei densities at t =106 yr for N2H+ (﹩{n}_{{{\rm{N}}}_{2}{{\rm{H}}}^{+}}﹩/n H). These profiles show the results for ξ CR(r) =1.0 × 10−17 [s−1] and molecular initial abundances (the “inheritance” scenario). The black, red, blue, and green lines show the profiles for different values of the parameter f (=1.0, 0.3, 0.03, and 0.003), respectively.
Paper: The Molecular Composition of Shadowed Proto-solar Disk Midplanes Beyond the Water Snowline
Authors: Shota Notsu, Kazumasa Ohno, Takahiro Ueda, Catherine Walsh, Christian Eistrup, Hideko Nomura
Figure caption: Same as Figure 14, but for N2 (top panels), NH3 (second-row panels), HCN (third-row panels), and NH2CHO (bottom panels).
Paper: The Molecular Composition of Shadowed Proto-solar Disk Midplanes Beyond the Water Snowline
Authors: Shota Notsu, Kazumasa Ohno, Takahiro Ueda, Catherine Walsh, Christian Eistrup, Hideko Nomura
Figure caption: Same as Figure 17, but for N2 (top panels), NH3 (second-row panels), HCN (third-row panels), and NH2CHO (bottom panels).
Paper: The Molecular Composition of Shadowed Proto-solar Disk Midplanes Beyond the Water Snowline
Authors: Shota Notsu, Kazumasa Ohno, Takahiro Ueda, Catherine Walsh, Christian Eistrup, Hideko Nomura
Figure caption: Same as Figure 17, but for CH4 (top panels), C2H6 (second-row panels), H2CO (third-row panels), and CH3OH (bottom panels).
Paper: The Molecular Composition of Shadowed Proto-solar Disk Midplanes Beyond the Water Snowline
Authors: Shota Notsu, Kazumasa Ohno, Takahiro Ueda, Catherine Walsh, Christian Eistrup, Hideko Nomura
Figure caption: Same as Figure 14, but for CH4 (top panels), C2H6 (second-row panels), H2CO (third-row panels), and CH3OH (bottom panels).
Paper: KODIAQ-Z: Metals and Baryons in the Cool Intergalactic and Circumgalactic Gas at 2.2 ≲ z ≲ 3.6
Authors: Nicolas Lehner, Claire Kopenhafer, John M. O'Meara, J. Christopher Howk, Michele Fumagalli, J. Xavier Prochaska, Ayan Acharyya, Brian W. O'Shea, Molly S. Peeples, Jason Tumlinson, Cameron B. Hummels
Figure caption: Example of normalized spectra against the rest-frame velocity of the absorber at z = 2.55125 toward J010311+131617 that show detection of H I, C III, C IV, and O VI (the integration ranges of the profiles are shown in red). Another absorber separated by 65 km s−1 is found at z = 2.55216; in this case, the column densities can be estimated reliably in each component/absorber (see also Figure 4).
Paper: KODIAQ-Z: Metals and Baryons in the Cool Intergalactic and Circumgalactic Gas at 2.2 ≲ z ≲ 3.6
Authors: Nicolas Lehner, Claire Kopenhafer, John M. O'Meara, J. Christopher Howk, Michele Fumagalli, J. Xavier Prochaska, Ayan Acharyya, Brian W. O'Shea, Molly S. Peeples, Jason Tumlinson, Cameron B. Hummels
Figure caption: Example of an absorber identified by our automatic searching tool. For each identified candidate absorber, a similar figure is created that shows the normalized spectra (in black) of the H I transitions from the 1215 to 917 Å transitions as a function of the velocity in the redshift rest frame (indicated in the top right panel). The colored profiles are Voigt profiles for an absorber with b = 25 km s−1 and ﹩\mathrm{log}{N}_{{\rm{H}}\,{\rm\small{I}}}=15,16,17,18﹩. These are used to help assess the level of contamination in each H I transition. Ultimately, for this candidate absorber, two absorbers were identified at z = 2.55125 and 2.55216 (corresponding to v ≃ −50 and +17 km s−1 in this figure).
Paper: KODIAQ-Z: Metals and Baryons in the Cool Intergalactic and Circumgalactic Gas at 2.2 ≲ z ≲ 3.6
Authors: Nicolas Lehner, Claire Kopenhafer, John M. O'Meara, J. Christopher Howk, Michele Fumagalli, J. Xavier Prochaska, Ayan Acharyya, Brian W. O'Shea, Molly S. Peeples, Jason Tumlinson, Cameron B. Hummels
Figure caption: Comparison of several spectral energy distributions for the ionizing background radiation field. The HM05 is adopted in this work, although we systematically compare it with the results from HM12. We also show the recent EUVB models from Khaire & Srianand (2019) for comparison. The key ions used to constrain the metallicities are shown, where the dotted vertical bars show their minimum ionization energy, while their range of ionization energy is shown with the horizontal bar.
Paper: KODIAQ-Z: Metals and Baryons in the Cool Intergalactic and Circumgalactic Gas at 2.2 ≲ z ≲ 3.6
Authors: Nicolas Lehner, Claire Kopenhafer, John M. O'Meara, J. Christopher Howk, Michele Fumagalli, J. Xavier Prochaska, Ayan Acharyya, Brian W. O'Shea, Molly S. Peeples, Jason Tumlinson, Cameron B. Hummels
Figure caption: Example of the same absorber shown in Figure 3 where we show the Voigt profile fit (in red the composite profile fit, and in blue each individual component) to the individual transitions of H I (black spectra). Despite some contamination in each transition, there are enough uncontaminated regions in each profile to estimate robustly the H I column density in each component.
Paper: KODIAQ-Z: Metals and Baryons in the Cool Intergalactic and Circumgalactic Gas at 2.2 ≲ z ≲ 3.6
Authors: Nicolas Lehner, Claire Kopenhafer, John M. O'Meara, J. Christopher Howk, Michele Fumagalli, J. Xavier Prochaska, Ayan Acharyya, Brian W. O'Shea, Molly S. Peeples, Jason Tumlinson, Cameron B. Hummels
Figure caption: Distribution of the Doppler parameters (b) and H I column densities in the KODIAQ-Z sample obtained from the PF of individual components. The right and top panels show the b and log N H I  distributions, respectively. The dotted line shows the lowest fitted b-value (corresponding T ≲ 104 K); 90% of the components have 13.3 ≤ b ≤ 40 km s−1. Note that for the Keck HIRES spectra the instrumental b-value is about 4–5 km s−1, well below the minimum observed b-value, i.e., narrower H I absorbers than b < 12 km s−1 could have been detected if present.
Paper: KODIAQ-Z: Metals and Baryons in the Cool Intergalactic and Circumgalactic Gas at 2.2 ≲ z ≲ 3.6
Authors: Nicolas Lehner, Claire Kopenhafer, John M. O'Meara, J. Christopher Howk, Michele Fumagalli, J. Xavier Prochaska, Ayan Acharyya, Brian W. O'Shea, Molly S. Peeples, Jason Tumlinson, Cameron B. Hummels
Figure caption: Distribution of the redshifts and H I column densities for the absorbers in the KODIAQ-Z sample. The top and right panels show the redshift and log N H I  distributions, respectively.
Paper: KODIAQ-Z: Metals and Baryons in the Cool Intergalactic and Circumgalactic Gas at 2.2 ≲ z ≲ 3.6
Authors: Nicolas Lehner, Claire Kopenhafer, John M. O'Meara, J. Christopher Howk, Michele Fumagalli, J. Xavier Prochaska, Ayan Acharyya, Brian W. O'Shea, Molly S. Peeples, Jason Tumlinson, Cameron B. Hummels
Figure caption: Distribution of the redshifts for the QSOs and the candidate absorbers from the automatic search in KODIAQ DR2.
Paper: Hard X-Ray Polarization Catalog for a Five-year Sample of Gamma-Ray Bursts Using AstroSat CZT Imager
Authors: Tanmoy Chattopadhyay, Soumya Gupta, Shabnam Iyyani, Divita Saraogi, Vidushi Sharma, Anastasia Tsvetkova, Ajay Ratheesh, Rahul Gupta, N. P. S. Mithun, C. S. Vaishnava, Vipul Prasad, E. Aarthy, Abhay Kumar, A. R. Rao, Santosh Vadawale, Varun Bhalerao, Dipankar Bhattacharya, Ajay Vibhute, Dmitry Frederiks
Figure caption: Comparison of POLAR and CZTI polarization results. The cumulative distribution of polarization fractions reported by POLAR for seven GRBs with fluence above 10−5 erg cm−2 (10–1000 keV) is shown by a solid blue line with 1σ error boundary. The gray lines are obtained from 15 GRBs detected by CZTI with fluence above 10−5 erg cm−2 (10–1000 keV) and at angles less than 60° (see text for more details).
Paper: Hard X-Ray Polarization Catalog for a Five-year Sample of Gamma-Ray Bursts Using AstroSat CZT Imager
Authors: Tanmoy Chattopadhyay, Soumya Gupta, Shabnam Iyyani, Divita Saraogi, Vidushi Sharma, Anastasia Tsvetkova, Ajay Ratheesh, Rahul Gupta, N. P. S. Mithun, C. S. Vaishnava, Vipul Prasad, E. Aarthy, Abhay Kumar, A. R. Rao, Santosh Vadawale, Varun Bhalerao, Dipankar Bhattacharya, Ajay Vibhute, Dmitry Frederiks
Figure caption: (a) Polarization fraction of the GRBs as a function of peak energy, E peak. The 10–1000 keV fluences in erg cm−2 s−1 for the GRBs are color-coded. (b), (c) Polarization fractions of the GRBs are shown with α (b) and β (c) obtained from Band function fits to the time-integrated burst spectra. The red circles represent GRBs with Bayes factor above 3 whereas the black down arrows represent the GRBs with Bayes factor less than 3.
Paper: Hard X-Ray Polarization Catalog for a Five-year Sample of Gamma-Ray Bursts Using AstroSat CZT Imager
Authors: Tanmoy Chattopadhyay, Soumya Gupta, Shabnam Iyyani, Divita Saraogi, Vidushi Sharma, Anastasia Tsvetkova, Ajay Ratheesh, Rahul Gupta, N. P. S. Mithun, C. S. Vaishnava, Vipul Prasad, E. Aarthy, Abhay Kumar, A. R. Rao, Santosh Vadawale, Varun Bhalerao, Dipankar Bhattacharya, Ajay Vibhute, Dmitry Frederiks
Figure caption: Comparison of the ratio of single to Compton events from observed data and simulation. The observed data points are shown as black triangles. If we do not include charge sharing in the simulation, simulated ratios (red crosses) are a factor 2 higher. However, after correction for charge sharing, the simulated values shown by red triangles agree closely with the observed values.
Paper: Hard X-Ray Polarization Catalog for a Five-year Sample of Gamma-Ray Bursts Using AstroSat CZT Imager
Authors: Tanmoy Chattopadhyay, Soumya Gupta, Shabnam Iyyani, Divita Saraogi, Vidushi Sharma, Anastasia Tsvetkova, Ajay Ratheesh, Rahul Gupta, N. P. S. Mithun, C. S. Vaishnava, Vipul Prasad, E. Aarthy, Abhay Kumar, A. R. Rao, Santosh Vadawale, Varun Bhalerao, Dipankar Bhattacharya, Ajay Vibhute, Dmitry Frederiks
Figure caption: Comparison between observed (black) and simulated (red) detector plane histograms of two-pixel Compton events binned at module level for a sample of GRBs.
Paper: Exploring the Link between the X-Ray Power Spectra and Energy Spectra of Active Galactic Nuclei
Authors: Haonan Yang, 浩楠 杨, Chichuan Jin, 驰川 金, Weimin Yuan
Figure caption: The folded energy spectra and 0.3–1 keV PSDs of the four AGN that have two or more detections of high-frequency breaks. Black lines are the best-fit Model B (i.e., break power law) results for observations that report significant breaks, and are the best-fit Model A (i.e., single power law) results for observations that do not report significant breaks. The dashed lines and the dotted lines represent red noise components and Poisson terms, respectively. The LRT1 p-values of the Model A simulation are shown downside. Spectra and PSDs are shown in different colors denoting the observation date. The PSDs are arranged in order of flux.
Paper: Exploring the Link between the X-Ray Power Spectra and Energy Spectra of Active Galactic Nuclei
Authors: Haonan Yang, 浩楠 杨, Chichuan Jin, 驰川 金, Weimin Yuan
Figure caption: Similar to Figure 1, but for the 2–10 keV band.
Paper: Mid-infrared and Maser Flux Variability Correlation in Massive Young Stellar Object G036.70+00.09
Authors: Mizuho Uchiyama, Kohei Ichikawa, Koichiro Sugiyama, Yoshihiro Tanabe, Yoshinori Yonekura
Figure caption: Left: Light curve of G036.70 in the WISE W1−W2 data. Middle: CMD of W1 and W1−W2 for G036.70. Single exposures with their associated error values are indicated in gray, and the average value for each epoch is indicated in black with error bars. The magenta vector represents the extinction vectors at R V = 5.5. Right: CMD of W2 and W1−W2.
Paper: Exploring the Link between the X-Ray Power Spectra and Energy Spectra of Active Galactic Nuclei
Authors: Haonan Yang, 浩楠 杨, Chichuan Jin, 驰川 金, Weimin Yuan
Figure caption: Distributions of LRT2 statistics of Mrk 335 in the 0.3–1 keV band with 5000 data sets simulated under Model B. The model parameters are based on the posterior distribution for the 2006 observation, while the Poisson term uses the value of the observations in 2009. The black vertical line is the observed value ﹩{T}_{\mathrm{LRT}}^{\mathrm{obs}}﹩, with the corresponding p-value at the top left corner.
Paper: Exploring the Link between the X-Ray Power Spectra and Energy Spectra of Active Galactic Nuclei
Authors: Haonan Yang, 浩楠 杨, Chichuan Jin, 驰川 金, Weimin Yuan
Figure caption: Distributions of LRT1 statistics of Mrk 335 in the 0.3–1 keV band with 5000 data sets simulated under Model A. The black vertical line is the observed value ﹩{T}_{\mathrm{LRT}}^{\mathrm{obs}}﹩, with the corresponding p-value at the top left corner.
Paper: Mid-infrared and Maser Flux Variability Correlation in Massive Young Stellar Object G036.70+00.09
Authors: Mizuho Uchiyama, Kohei Ichikawa, Koichiro Sugiyama, Yoshihiro Tanabe, Yoshinori Yonekura
Figure caption: Obtained SED for G036.70 and the best-fitting result. The black points with error bars correspond to the obtained IR photometries from Spitzer, Herschel/PACS, and SPIRE. The best-fitting SED is represented by the solid black line.
Paper: Exploring the Link between the X-Ray Power Spectra and Energy Spectra of Active Galactic Nuclei
Authors: Haonan Yang, 浩楠 杨, Chichuan Jin, 驰川 金, Weimin Yuan
Figure caption: Logarithm of the PSD break frequencies against spectral slopes. The values and errors are calculated using MCMC. The data are marked as dashed lines which show the observed frequency ranges of PSDs if they do not exhibit a significant break.
Paper: Exploring the Link between the X-Ray Power Spectra and Energy Spectra of Active Galactic Nuclei
Authors: Haonan Yang, 浩楠 杨, Chichuan Jin, 驰川 金, Weimin Yuan
Figure caption: Logarithm of the PSD break frequencies against fluxes. The values and errors are calculated using MCMC. The data are marked as dashed lines which show the observed frequency ranges of PSDs if they do not exhibit a significant break.
Paper: Characterizing the 3D Kinematics of Young Stars in the Radcliffe Wave
Authors: Alan J. Tu, Catherine Zucker, Joshua S. Speagle, 佳士 沈, Angus Beane, Alyssa Goodman, João Alves, Jacqueline Faherty, Andreas Burkert
Figure caption: Top: vertical angle vs. projected position along the Radcliffe Wave for the Radcliffe Wave pre-main-sequence star sample (left) and the older main-sequence control sample (right). The gray points represent the stars in each sample and the colored dots are the binned “phase-marginalized” medians. In the upper right-hand corner of each panel we show the typical error on the vertical angle for each sample in black. In the Radcliffe Wave sample of young stars, we see a clear linear trend in phase space consistent with a wavelike oscillation. No such trend exists in the older stellar population, implying that this is not purely due to the cuts used to select both samples. Bottom: same as the top panel, but for the vertical velocity v  z  vs. projected position along the Radcliffe Wave. Unlike with the vertical angle, we find no systematic trend in the vertical velocities of the young stars as a function of position along the wave and we detect no fluctuations in the average vertical velocity at a level ⪆3 km s−1.
Paper: Characterizing the 3D Kinematics of Young Stars in the Radcliffe Wave
Authors: Alan J. Tu, Catherine Zucker, Joshua S. Speagle, 佳士 沈, Angus Beane, Alyssa Goodman, João Alves, Jacqueline Faherty, Andreas Burkert
Figure caption: 3D distribution of young stars alongside the Radcliffe Wave. We show XY (left), XZ (top right), and YZ (bottom right) projections. The navy points represent the pre-main-sequence stars (Zari et al. 2018) we use for our primary analysis without any clustering applied. The red line indicates the best-fit model of the Radcliffe Wave (Alves et al. 2020) detected in 3D dust. The 3D dust map from Green et al. (2019) integrated over the range ∣Z∣ < 300 pc is shown in the background gray scale in the left panel. The position of the Sun is marked with a yellow dot. The two red crosses mark the beginning (X, Y = −385, −222) pc and ending (X, Y = −67, 438) pc positions along the wave that we consider in Figure 3.
Paper: Characterizing the 3D Kinematics of Young Stars in the Radcliffe Wave
Authors: Alan J. Tu, Catherine Zucker, Joshua S. Speagle, 佳士 沈, Angus Beane, Alyssa Goodman, João Alves, Jacqueline Faherty, Andreas Burkert
Figure caption: A schematic illustration of our modeling approach. For a proposed wavy midplane model, we take our sample of young stars (selected relative to the best-fit model of the Radcliffe Wave estimated from 3D dust) shown in the top left panel and convert their corresponding 6D positions and velocities to their corresponding action-angle coordinates. This then provides a corresponding distribution of vertical angles, as shown in the bottom left panel. Using kernel density estimation (KDE), we then estimate both the 1D distribution in the projected position along the Radcliffe Wave as well as the 2D distribution in both the projected position and vertical angle (middle panels). Based on the estimated 1D distribution of projected positions, we then compute the expected 2D distribution assuming all stars orbit around the proposed midplane (top right panel). We then compare the two distributions using a scaled version of the Kullblack–Leibler (KL) divergence (bottom right panel). See Section 3.2 for additional details.
Paper: Characterizing the 3D Kinematics of Young Stars in the Radcliffe Wave
Authors: Alan J. Tu, Catherine Zucker, Joshua S. Speagle, 佳士 沈, Angus Beane, Alyssa Goodman, João Alves, Jacqueline Faherty, Andreas Burkert
Figure caption: A corner plot of the model parameters for the wavy midplane analysis using the epicyclic approximation and applied to the unclustered Radcliffe Wave young star sample. In the 1D distributions, the vertical dashed lines indicate the median and 2σ errors while in the 2D distributions, we demarcate the 0.5σ, 1σ, 1.5σ, and 2σ contours. See Table 1 for a description of the parameters and associated priors.
Paper: Characterizing the 3D Kinematics of Young Stars in the Radcliffe Wave
Authors: Alan J. Tu, Catherine Zucker, Joshua S. Speagle, 佳士 沈, Angus Beane, Alyssa Goodman, João Alves, Jacqueline Faherty, Andreas Burkert
Figure caption: Left: distribution of the difference in vertical angle value between the epicyclic approximation and direct integration of the orbit with gala for each of the stars with radial velocities in the unclustered pre-main-sequence sample from Zari et al. (2018). A difference of zero denotes a perfect match. Right: the difference instead plotted against the vertical angle calculated from gala, highlighting that the greatest discrepancies occur near 0, π, and 2π.
Paper: Characterizing the 3D Kinematics of Young Stars in the Radcliffe Wave
Authors: Alan J. Tu, Catherine Zucker, Joshua S. Speagle, 佳士 沈, Angus Beane, Alyssa Goodman, João Alves, Jacqueline Faherty, Andreas Burkert
Figure caption: Comparison of the Radcliffe Wave best-fit models derived using 3D dust (Alves et al. 2020; this work). The top panel shows a comparison between the 3D dust Radcliffe Wave (red) and the epicyclic fit to the unclustered stellar wave sample (navy). The middle panel shows a comparison between the 3D dust Radcliffe Wave (red) and the epicyclic fit to the clustered stellar sample (indigo). In the bottom panel, we compare all three model fits.
Paper: Characterizing the 3D Kinematics of Young Stars in the Radcliffe Wave
Authors: Alan J. Tu, Catherine Zucker, Joshua S. Speagle, 佳士 沈, Angus Beane, Alyssa Goodman, João Alves, Jacqueline Faherty, Andreas Burkert
Figure caption: Dereddened Gaia-based color–magnitude diagram showing the primary unclustered pre-main-sequence sample (navy) alongside the main-sequence control sample (green). The sharp cutoff in M  G , 0 for the pre-main-sequence sample is stipulated in Zari et al. (2018) and motivated by the need to exclude sources that are located on the main-sequence turnoff and on the faint end of the giant branch.
Paper: Characterizing the 3D Kinematics of Young Stars in the Radcliffe Wave
Authors: Alan J. Tu, Catherine Zucker, Joshua S. Speagle, 佳士 沈, Angus Beane, Alyssa Goodman, João Alves, Jacqueline Faherty, Andreas Burkert
Figure caption: Same as Figure 4, but for the Stäckel–Fudge approach applied to the unclustered Radcliffe Wave sample.
Paper: Characterizing the 3D Kinematics of Young Stars in the Radcliffe Wave
Authors: Alan J. Tu, Catherine Zucker, Joshua S. Speagle, 佳士 沈, Angus Beane, Alyssa Goodman, João Alves, Jacqueline Faherty, Andreas Burkert
Figure caption: Same as Figure 4, but for the epicyclic approximation applied to the clustered Radcliffe Wave sample.
Paper: Continued PSP/WISPR Observations of a Phaethon-related Dust Trail
Authors: Karl Battams, Angel J. Gutarra-Leon, Brendan M. Gallagher, Matthew M. Knight, Guillermo Stenborg, Sarah Tanner, Mark G. Linton, Jamey R. Szalay, Michael S. P. Kelley, Russell A. Howard
Figure caption: Plot of the apparent physical offset (in 105 kilometers) of the dust trail from Phaethon’s orbit as a function of true anomaly (degrees), based on the central peak locations of Gaussians fitted to cross-trail profiles obtained from various points throughout most of the first nine encounters. A second-order polynomial fit is shown with the fit parameters in the Figure legend along with the r 2 value (coefficient of determination, which is the square of the correlation coefficient, R) for the polynomial, but we note that this polynomial and its coefficients are not intended to be physically meaningful.
Paper: Continued PSP/WISPR Observations of a Phaethon-related Dust Trail
Authors: Karl Battams, Angel J. Gutarra-Leon, Brendan M. Gallagher, Matthew M. Knight, Guillermo Stenborg, Sarah Tanner, Mark G. Linton, Jamey R. Szalay, Michael S. P. Kelley, Russell A. Howard
Figure caption: Illustration of a cross-trail profile extracted from an L3 WISPR-O image, recorded on 2020 June 7 (first panel), and processed with the sigma filter plus smoothing algorithm. The white box outlines the ROI in which 396 cross-trail profiles were extracted. The second shows the resulting profile, averaged from these 396 profiles, and the third panel shows the result of a Gaussian fit to the profile, and the resulting fit parameters. The intensity is recorded in physical MSB units, but note that the smoothing filter can be detrimental to pixel-level photometry.
Paper: Continued PSP/WISPR Observations of a Phaethon-related Dust Trail
Authors: Karl Battams, Angel J. Gutarra-Leon, Brendan M. Gallagher, Matthew M. Knight, Guillermo Stenborg, Sarah Tanner, Mark G. Linton, Jamey R. Szalay, Michael S. P. Kelley, Russell A. Howard
Figure caption: A WISPR-O observation recorded on 2021 May 2 07:34 UT processed in three different formats. Figure 9(a) shows the L3 version of this image—that is, a fully calibrated image with the background image removed. Figure 9(b) shows the L3 image with a sigma filter applied. Figure 9(c) shows the L3 image with a sigma filter and smooth filter applied. The dust trail can be seen crossing diagonally from the top center toward the lower-left corner, more clearly in panels (b) and (c).