adsabs/AstroCLIMB huggingface dataset:
Paper: The Perkins INfrared Exosatellite Survey (PINES) I. Survey Overview, Reduction Pipeline, and Early Results
Authors: Patrick Tamburo, Philip S. Muirhead, Allison M. McCarthy, Murdock Hart, David Gracia, Johanna M. Vos, Daniella C. Bardalez Gagliuffi, Jacqueline Faherty, Christopher Theissen, Eric Agol, Julie N. Skinner, Sheila Sagear
Figure caption: A typical reduced J-band Mimir image. Bad pixels in this image are shown in white. The inset shows a zoom-in on the target in this field, which is deliberately placed in a detector region that is relatively devoid of bad pixels.
Paper: The Perkins INfrared Exosatellite Survey (PINES) I. Survey Overview, Reduction Pipeline, and Early Results
Authors: Patrick Tamburo, Philip S. Muirhead, Allison M. McCarthy, Murdock Hart, David Gracia, Johanna M. Vos, Daniella C. Bardalez Gagliuffi, Jacqueline Faherty, Christopher Theissen, Eric Agol, Julie N. Skinner, Sheila Sagear
Figure caption: Transit recovery of WASP-2 b on UT 2021 July 28. The rows show different stages of PAT, going from raw flux to a final light curve. The left column shows the full night of data, while the right column shows a zoom-in on the four blocks that cover the transit event. Top: raw flux measured for WASP-2 and four reference stars. Middle: the normalized flux of WASP-2 and the ALC constructed from the weighted mean of the four reference stars. Bottom: the normalized flux for WASP-2 corrected by the ALC and a linear baseline, along with a transit model of WASP-2 b.
Paper: The Perkins INfrared Exosatellite Survey (PINES) I. Survey Overview, Reduction Pipeline, and Early Results
Authors: Patrick Tamburo, Philip S. Muirhead, Allison M. McCarthy, Murdock Hart, David Gracia, Johanna M. Vos, Daniella C. Bardalez Gagliuffi, Jacqueline Faherty, Christopher Theissen, Eric Agol, Julie N. Skinner, Sheila Sagear
Figure caption: Estimated J-band transit-detection sensitivity for all of the targets in the PINES sample (colored points), assuming purely Gaussian noise as determined by the J-band noise model shown in Figure 9. Astrophysical or systematic noise sources, which are not captured in this model, will degrade this sensitivity estimation. Targets in this panel are colored by their spectral type, and the black line shows a third-degree polynomial fit to the points. The histogram above the axis shows the J-band magnitudes of targets in the PINES sample (the binning matches that in the top panel of Figure 2).
Paper: The Perkins INfrared Exosatellite Survey (PINES) I. Survey Overview, Reduction Pipeline, and Early Results
Authors: Patrick Tamburo, Philip S. Muirhead, Allison M. McCarthy, Murdock Hart, David Gracia, Johanna M. Vos, Daniella C. Bardalez Gagliuffi, Jacqueline Faherty, Christopher Theissen, Eric Agol, Julie N. Skinner, Sheila Sagear
Figure caption: The background estimation process used for aperture photometry. Left: a circular annulus is placed at the measured source position (red x), with bad pixels shown in white. Middle: pixels outside of the annulus (and if necessary, those containing sources) are ignored. Right: a histogram of the resulting pixel values. The background is estimated as the sigma-clipped mean of these values (orange line).
Paper: The Perkins INfrared Exosatellite Survey (PINES) I. Survey Overview, Reduction Pipeline, and Early Results
Authors: Patrick Tamburo, Philip S. Muirhead, Allison M. McCarthy, Murdock Hart, David Gracia, Johanna M. Vos, Daniella C. Bardalez Gagliuffi, Jacqueline Faherty, Christopher Theissen, Eric Agol, Julie N. Skinner, Sheila Sagear
Figure caption: Panels (a)–(e): theoretical response to changing PWV levels for different spectral types in various NIR filters. Panel (f): the magnitude of the PWV response of an L6 dwarf calibrated to the response of a G0 in each filter. The second-order extinction effect is minimized in MKO J band.
Paper: The Perkins INfrared Exosatellite Survey (PINES) I. Survey Overview, Reduction Pipeline, and Early Results
Authors: Patrick Tamburo, Philip S. Muirhead, Allison M. McCarthy, Murdock Hart, David Gracia, Johanna M. Vos, Daniella C. Bardalez Gagliuffi, Jacqueline Faherty, Christopher Theissen, Eric Agol, Julie N. Skinner, Sheila Sagear
Figure caption: A sky map of the PINES sample. Targets that have been observed as of 2021 October are shown in green, while those that have yet to be observed are shown in black. Individual targets are shown as filled circles, while groups of targets are outlined with solid lines. The inset shows a zoom-in on one group and visualizes the order in which its members were targeted during PINES observations.
Paper: The Perkins INfrared Exosatellite Survey (PINES) I. Survey Overview, Reduction Pipeline, and Early Results
Authors: Patrick Tamburo, Philip S. Muirhead, Allison M. McCarthy, Murdock Hart, David Gracia, Johanna M. Vos, Daniella C. Bardalez Gagliuffi, Jacqueline Faherty, Christopher Theissen, Eric Agol, Julie N. Skinner, Sheila Sagear
Figure caption: Comparison of the PTO auto-guider performance (left column) vs. the PINES guiding system (right column). Top: measured x pixel shifts. Middle: measured y pixel (decl. axis) shifts. Bottom: light curves resulting from the two guiding approaches, which exhibit similar scatter.
Paper: The Perkins INfrared Exosatellite Survey (PINES) I. Survey Overview, Reduction Pipeline, and Early Results
Authors: Patrick Tamburo, Philip S. Muirhead, Allison M. McCarthy, Murdock Hart, David Gracia, Johanna M. Vos, Daniella C. Bardalez Gagliuffi, Jacqueline Faherty, Christopher Theissen, Eric Agol, Julie N. Skinner, Sheila Sagear
Figure caption: Left: an example of a guide field image, with guide stars indicated with circles (with purple indicating the target and red indicating other sources). Bad pixels in this image have been interpolated with a 2D-Gaussian kernel to improve source-detection efficiency. Right: the guide field synthetic image for this field.
Paper: The Perkins INfrared Exosatellite Survey (PINES) I. Survey Overview, Reduction Pipeline, and Early Results
Authors: Patrick Tamburo, Philip S. Muirhead, Allison M. McCarthy, Murdock Hart, David Gracia, Johanna M. Vos, Daniella C. Bardalez Gagliuffi, Jacqueline Faherty, Christopher Theissen, Eric Agol, Julie N. Skinner, Sheila Sagear
Figure caption: The FFT convolution of a science field synthetic image and a guide field synthetic image, which is used to determine the shifts needed to correct the PTO’s pointing during PINES observations.
Paper: The Long-term Spectroscopic and Photometric Behavior of the Carbon Star RS Cygni
Authors: Robert R. Cadmus
Figure caption: The variations in the strengths of selected features in the spectrum of RS Cyg as a function of phase. (a)–(c) Balmer emission lines; (d)–(f) C2 bands; (g)–(i) CN bands; (j)–(l) other features. A few very discordant points are outside the plotted regions. Zero phase is at minimum light. The arbitrary flux units are the same for all the emission features.
Paper: The Long-term Spectroscopic and Photometric Behavior of the Carbon Star RS Cygni
Authors: Robert R. Cadmus
Figure caption: The strengths of the Hα (panel (a)) and Hβ (panel (b)) emission lines in the spectrum of RS Cyg, as well as the V flux (panel (c)), indicated by the sizes of the symbols, as functions of JD and phase. Zero phase is at minimum light.
Paper: The Long-term Spectroscopic and Photometric Behavior of the Carbon Star RS Cygni
Authors: Robert R. Cadmus
Figure caption: The strengths of selected spectral features as a function of JD (points) compared with the spline fit to the photometric V-flux curve (line).
Paper: Earth as a Proxy Exoplanet: Simulating DSCOVR/EPIC Observations Using the Earth Spectrum Simulator
Authors: Lixiang Gu, Zhao-Cheng Zeng, Siteng Fan, Vijay Natraj, Jonathan H. Jiang, David Crisp, Yuk L. Yung, Yongyun Hu
Figure caption: Reflectance difference between HITRAN 2020 and HITRAN 2008 in the 551 nm channel. Tests are done for the eleven different sets of profiles shown in Figure A2, over three different underlying surface types: (a) ocean, (b) forest, and (c) desert. For each set of profiles over each underlying surface type, eight different viewing geometries are tested (colored dots): solar zenith angle (equal to viewing zenith angle) varies from 10°to 80°. The relative azimuth angle is assumed to be 170°.
Paper: Earth as a Proxy Exoplanet: Simulating DSCOVR/EPIC Observations Using the Earth Spectrum Simulator
Authors: Lixiang Gu, Zhao-Cheng Zeng, Siteng Fan, Vijay Natraj, Jonathan H. Jiang, David Crisp, Yuk L. Yung, Yongyun Hu
Figure caption: (a) Scatter plots of simulated disk-integrated reflectance against observations for the original simulation (blue dots) and the “10% higher cloud effective pressure” experiment (red dots) in the two oxygen absorption channels. Linear regression results for the original simulation (blue line) and the experiment (red line) are also given. (b) Histograms of ice cloud-covered pixel reflectance for the original simulation (blue) and the experiment (red). (c) Same as (b), but for liquid cloud-covered pixels.
Paper: Earth as a Proxy Exoplanet: Simulating DSCOVR/EPIC Observations Using the Earth Spectrum Simulator
Authors: Lixiang Gu, Zhao-Cheng Zeng, Siteng Fan, Vijay Natraj, Jonathan H. Jiang, David Crisp, Yuk L. Yung, Yongyun Hu
Figure caption: Profiles of (a) temperature and (b) H2O used for the reflectance comparison between HITRAN 2008 and HITRAN 2020.
Paper: Earth as a Proxy Exoplanet: Simulating DSCOVR/EPIC Observations Using the Earth Spectrum Simulator
Authors: Lixiang Gu, Zhao-Cheng Zeng, Siteng Fan, Vijay Natraj, Jonathan H. Jiang, David Crisp, Yuk L. Yung, Yongyun Hu
Figure caption: Histograms of (a) ice cloud-covered, (b) liquid cloud-covered, and (c) clear sky pixel reflectance for simulations using approximate (2S-ESS; blue) and numerically exact (VLIDORT; red) RT models.
Paper: Earth as a Proxy Exoplanet: Simulating DSCOVR/EPIC Observations Using the Earth Spectrum Simulator
Authors: Lixiang Gu, Zhao-Cheng Zeng, Siteng Fan, Vijay Natraj, Jonathan H. Jiang, David Crisp, Yuk L. Yung, Yongyun Hu
Figure caption: Same as Figure 8, but for clear-sky pixels.
Paper: Earth as a Proxy Exoplanet: Simulating DSCOVR/EPIC Observations Using the Earth Spectrum Simulator
Authors: Lixiang Gu, Zhao-Cheng Zeng, Siteng Fan, Vijay Natraj, Jonathan H. Jiang, David Crisp, Yuk L. Yung, Yongyun Hu
Figure caption: Distribution of the eight surface types at (a) 9:08 UTC, 2016 April 5, and (b) 14:47 UTC, 2016 August 7.
Paper: The TESS-Keck Survey. XI. Mass Measurements for Four Transiting Sub-Neptunes Orbiting K Dwarf TOI–1246
Authors: Emma V. Turtelboom, Lauren M. Weiss, Courtney D. Dressing, Grzegorz Nowak, Enric Pallé, Corey Beard, Sarah Blunt, Casey Brinkman, Ashley Chontos, Zachary R. Claytor, Fei Dai, Paul A. Dalba, Steven Giacalone, Erica Gonzales, Caleb K. Harada, Michelle L. Hill, Rae Holcomb, Judith Korth, Jack Lubin, Thomas Masseron, Mason MacDougall, Andrew W. Mayo, Teo Močnik, Joseph M. Akana Murphy, Alex S. Polanski, Malena Rice, Ryan A. Rubenzahl, Nicholas Scarsdale, Keivan G. Stassun, Dakotah B. Tyler, Judah Van Zandt, Ian J. M. Crossfield, Hans J. Deeg, Benjamin Fulton, Davide Gandolfi, Andrew W. Howard, Dan Huber, Howard Isaacson, Stephen R. Kane, Kristine W. F. Lam, Rafael Luque, Eduardo L. Martín, Giuseppe Morello, Jaume Orell-Miquel, Erik A. Petigura, Paul Robertson, Arpita Roy, Vincent Van Eylen, David Baker, Alexander A. Belinski, Allyson Bieryla, David R. Ciardi, Karen A. Collins, Neil Cutting, Devin J. Della-Rose, Taylor B. Ellingsen, E. Furlan, Tianjun Gan, Crystal L. Gnilka, Pere Guerra, Steve B. Howell, Mary Jimenez, David W. Latham, Maude Larivière, Kathryn V. Lester, Jorge Lillo-Box, Lindy Luker, Christopher R. Mann, Peter P. Plavchan, Boris Safonov, Brett Skinner, Ivan A. Strakhov, Justin M. Wittrock, Douglas A. Caldwell, Zahra Essack, Jon M. Jenkins, Elisa V. Quintana, George R. Ricker, Roland Vanderspek, S. Seager, Joshua N. Winn
Figure caption: High-multiplicity (N pl  ≥ 4) planet systems where all planets are confirmed and have radius measurements, ordered by increasing innermost orbital period. Point size is determined by planet radius, and planets with measured masses are shaded according to the color bar on the right of the figure. Planets with upper limit mass measurements do not have a black edge, and are colored according to the upper limit. The effective temperatures of the systems’ host stars are indicated using the semicircles on the left of each row, shaded according to the second color bar. TOI-1246 is one of only five systems with measured masses for all four planets, and has a unique system architecture within this group. *V1298 Tau and K2-266 are the only systems in this population that are brighter than TOI-1246. **We note that the masses shown for the two outer planets in the Kepler-282 system are nominal TTV masses and are likely overestimates (Xie 2014). ***Kepler-132 is a binary star system that hosts four planets (at 6.2d, 6.4d, 18.0d, and 110d), but it is unknown which planets orbit which star.
Paper: The TESS-Keck Survey. XI. Mass Measurements for Four Transiting Sub-Neptunes Orbiting K Dwarf TOI–1246
Authors: Emma V. Turtelboom, Lauren M. Weiss, Courtney D. Dressing, Grzegorz Nowak, Enric Pallé, Corey Beard, Sarah Blunt, Casey Brinkman, Ashley Chontos, Zachary R. Claytor, Fei Dai, Paul A. Dalba, Steven Giacalone, Erica Gonzales, Caleb K. Harada, Michelle L. Hill, Rae Holcomb, Judith Korth, Jack Lubin, Thomas Masseron, Mason MacDougall, Andrew W. Mayo, Teo Močnik, Joseph M. Akana Murphy, Alex S. Polanski, Malena Rice, Ryan A. Rubenzahl, Nicholas Scarsdale, Keivan G. Stassun, Dakotah B. Tyler, Judah Van Zandt, Ian J. M. Crossfield, Hans J. Deeg, Benjamin Fulton, Davide Gandolfi, Andrew W. Howard, Dan Huber, Howard Isaacson, Stephen R. Kane, Kristine W. F. Lam, Rafael Luque, Eduardo L. Martín, Giuseppe Morello, Jaume Orell-Miquel, Erik A. Petigura, Paul Robertson, Arpita Roy, Vincent Van Eylen, David Baker, Alexander A. Belinski, Allyson Bieryla, David R. Ciardi, Karen A. Collins, Neil Cutting, Devin J. Della-Rose, Taylor B. Ellingsen, E. Furlan, Tianjun Gan, Crystal L. Gnilka, Pere Guerra, Steve B. Howell, Mary Jimenez, David W. Latham, Maude Larivière, Kathryn V. Lester, Jorge Lillo-Box, Lindy Luker, Christopher R. Mann, Peter P. Plavchan, Boris Safonov, Brett Skinner, Ivan A. Strakhov, Justin M. Wittrock, Douglas A. Caldwell, Zahra Essack, Jon M. Jenkins, Elisa V. Quintana, George R. Ricker, Roland Vanderspek, S. Seager, Joshua N. Winn
Figure caption: Mass–radius plot showing the four planets orbiting TOI-1246 (TOI-1246 b: purple, TOI-1246c: blue, TOI-1246 d: light blue, TOI-1246 e: pink). The parameter space that the fifth nontransiting planet candidate could occupy is shown in green (we exclude potential compositions more dense than 100% Fe). Theoretical composition curves from Zeng et al. (2019) are shown in gray. Earth (E), Venus (V), Uranus (U), and Neptune (N) are also shown for context, with the precise masses and radii for these planets lying in the center of the letter symbol. The subset of confirmed planets in systems with two or more planets, and with mass and radius measurements with >3σ precision, are plotted in black with gray error bars.
Paper: The Perkins INfrared Exosatellite Survey (PINES) I. Survey Overview, Reduction Pipeline, and Early Results
Authors: Patrick Tamburo, Philip S. Muirhead, Allison M. McCarthy, Murdock Hart, David Gracia, Johanna M. Vos, Daniella C. Bardalez Gagliuffi, Jacqueline Faherty, Christopher Theissen, Eric Agol, Julie N. Skinner, Sheila Sagear
Figure caption: The average 5 minutes standard deviation (﹩{\bar{\sigma }}_{5\min }﹩) of PINES targets observed in J band (points with error bars). The dashed line indicates the expected noise performance from Tamburo & Muirhead (2019), while the solid line shows an updated calculation using measured seeing, background, and throughput values, along with a logistic noise floor for targets brighter than m  J  ≈ 14.
Paper: The Long-term Spectroscopic and Photometric Behavior of the Carbon Star RS Cygni
Authors: Robert R. Cadmus
Figure caption: The ΔV and ΔB light curves for RS Cyg. The photometric measurements are shown with small symbols, the spline fit with the curve, and the dates of the spectroscopic observations with large symbols. The scale for the ΔB data is compressed by a factor of 2 relative to that for the ΔV data to emphasize the similarity between the two.
Paper: The Long-term Spectroscopic and Photometric Behavior of the Carbon Star RS Cygni
Authors: Robert R. Cadmus
Figure caption: A rectified average spectrum of RS Cyg with features of interest identified.
Paper: The Long-term Spectroscopic and Photometric Behavior of the Carbon Star RS Cygni
Authors: Robert R. Cadmus
Figure caption: The variations in the spectrum of RS Cyg as a function of wavelength and phase. Lighter colors indicate higher intensity.
Paper: The Long-term Spectroscopic and Photometric Behavior of the Carbon Star RS Cygni
Authors: Robert R. Cadmus
Figure caption: (a) The Fourier spectrum of the RS Cyg light curve. (b) The contribution of the first component to the light curve.
Paper: The Long-term Spectroscopic and Photometric Behavior of the Carbon Star RS Cygni
Authors: Robert R. Cadmus
Figure caption: A representative spectrum of RS Cyg.
Paper: Improving the Spatial Resolution of Solar Images Based on an Improved Conditional Denoising Diffusion Probability Model
Authors: Wei Song, Wen Ma, Ying Ma, Xiaobing Zhao, Ganghua Lin
Figure caption: The three rows are the comparison of the power spectrum, scatter plot, and gray histogram of the SR image, GST image, and HMI image, respectively. The dotted lines in the scatter plot represent auxiliary lines with slopes of 0.5, 1, and 2 in turn. The left column compares the HMI image, SR image, and GST image. The right column compares the HMI image, blurred SR image, and blurred GST image.
Paper: Improving the Spatial Resolution of Solar Images Based on an Improved Conditional Denoising Diffusion Probability Model
Authors: Wei Song, Wen Ma, Ying Ma, Xiaobing Zhao, Ganghua Lin
Figure caption: Peak S/N, SSIM, and rms indexes of test results. The black lines in (a) and (b) represent the indexes of the HMI image and GST image, while the green and red lines represent the indexes of our SR images, SR images of SAGAN and GST images, respectively. The black, blue, green, and red lines in (c) represent the indexes of the HMI image, GST image, our SR images, and SR images of SAGAN, respectively. (d) represents the SSIM index of the GST images, and the index of our SR images and the SR images of SAGAN after blurring.
Paper: Improving the Spatial Resolution of Solar Images Based on an Improved Conditional Denoising Diffusion Probability Model
Authors: Wei Song, Wen Ma, Ying Ma, Xiaobing Zhao, Ganghua Lin
Figure caption: Five reconstruction results. The images from left to right correspond to the HMI image, the GST image, the SAGAN SR image, and our SR images, respectively. The field of view is about 30″ × 30″. Red dotted boxes are used to facilitate the comparison of images.
Paper: Improving the Spatial Resolution of Solar Images Based on an Improved Conditional Denoising Diffusion Probability Model
Authors: Wei Song, Wen Ma, Ying Ma, Xiaobing Zhao, Ganghua Lin
Figure caption: The overall framework of our ICDDPM. The number after n is the number of the channel.  y ,  x  0, and  ϵ   θ  represent the HMI image, GST image, and prediction noise, respectively.
Paper: Improving the Spatial Resolution of Solar Images Based on an Improved Conditional Denoising Diffusion Probability Model
Authors: Wei Song, Wen Ma, Ying Ma, Xiaobing Zhao, Ganghua Lin
Figure caption: (a) Shows the HMI image, the SR image blurred to the resolution of the HMI image, and the residual image from left to right; (b) shows the GST image, the SR image, and the prediction residual image from left to right. Blue dotted boxes are used to facilitate the comparison of images. The SR image in the first row in (a) and (b) is the result of our model, and the SR image in the second row is the result of SAGAN.
Paper: Improving the Spatial Resolution of Solar Images Based on an Improved Conditional Denoising Diffusion Probability Model
Authors: Wei Song, Wen Ma, Ying Ma, Xiaobing Zhao, Ganghua Lin
Figure caption: Shows the reconstructed small-scale structures of the solar penumbra (top), umbra (middle), and granulation (bottom) in turn. The first row is the HMI image, the second row is the GST image, the third row is the SR image of SAGAN, and the fourth row is our SR image. Red dotted boxes are used to facilitate the comparison of images.
Paper: Improving the Spatial Resolution of Solar Images Based on an Improved Conditional Denoising Diffusion Probability Model
Authors: Wei Song, Wen Ma, Ying Ma, Xiaobing Zhao, Ganghua Lin
Figure caption: The reconstruction process of a solar image. The numbers below each image represent the number of iterations. The number of reconstruction step S is 10.
Paper: H-AMR: A New GPU-accelerated GRMHD Code for Exascale Computing with 3D Adaptive Mesh Refinement and Local Adaptive Time Stepping
Authors: M. T. P. Liska, K. Chatterjee, D. Issa, D. Yoon, N. Kaaz, A. Tchekhovskoy, D. van Eijnatten, G. Musoke, C. Hesp, V. Rohoza, S. Markoff, A. Ingram, M. van der Klis
Figure caption: A 3D isocontour rendering of density at different times in our simulation, showing a single tearing cycle of the disk: at the initial time shown, t  =  42,500r  g /c (top left panel), the disk is intact. However, at t  =  47,500r  g /c, the inner disk of size ∼ 20r  g  tears off from the outer disk and starts to precess independently of the outer disk. Eventually, the inner precessing disk gets consumed by the black hole, and the entire disk appears intact again at the last time shown, t  =  82,500r  g /c (bottom right panel). During each tearing cycle, the torque from the spinning black hole overcomes the viscous torques holding the disk together, and the disk tears apart. This results in a rapidly precessing inner subdisk physically detached from the outer disk. This subdisk can sustain several precession periods before it shrinks and disappears into the black hole and the tearing cycle repeats. Disk tearing and precession is an attractive model to explain type C QPOs in the light curves of XRBs (e.g., van der Klis 2006).
Paper: H-AMR: A New GPU-accelerated GRMHD Code for Exascale Computing with 3D Adaptive Mesh Refinement and Local Adaptive Time Stepping
Authors: M. T. P. Liska, K. Chatterjee, D. Issa, D. Yoon, N. Kaaz, A. Tchekhovskoy, D. van Eijnatten, G. Musoke, C. Hesp, V. Rohoza, S. Markoff, A. Ingram, M. van der Klis
Figure caption: Left panel: the ratio between internal energy (u  g ) and rest mass density (ρ) during a spherical off-center explosion that passes through two internal and one external SMR layer in addition to the polar axis. The different meshblocks are separated by white lines. Black lines illustrate the distance from the center of the explosion in steps of 1r  g . The front of the shock wave becomes less resolved at larger radii owing to the logarithmic spacing of the grid. Right panel: the ratio between the magnetic energy (b 2) and rest mass density (ρ) during a magnetized off-center explosion that passes through two internal and one external SMR layer in addition to the polar axis. When the explosion passes through the polar singularity, only minor artifacts in the internal energy and magnetic field strength are detected, which is consistent with other (GR)MHD codes that utilize similar (transmissive) boundary conditions (e.g., Mewes et al. 2018, 2020).