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Paper: Kinematically Complex Circumgalactic Gas Around a Low-mass Galaxy: Filamentary Inflow and Counterrotation in J0910b
Authors: Zeren Lin, D. Christopher Martin, Mateusz Matuszewski, James D. Neill, Drew M. Miles, Vincent Picouet, Nikolaus Z. Prusinski, Keri Hoadley, Rosalie McGurk
Figure caption: Radial binning results for the unsmoothed data cubes from KCWI-blue (top row) and KCWI-red (bottom row). Left: the color scale shows the surface brightness in each bin, integrated over a 4 Å window around [O III] λ5007 (5484–5488 Å) for the blue channel and Hα (7188–7192 Å) for the red channel. Thin boundaries delineate each bin, and SNR labels are placed at the geometric center of their respective bins. SNR values are shown for bins with 2.5 ≤ SNR ≤ 7 (KCWI-blue) and 2.5 ≤ SNR ≤ 11 (KCWI-red), with the upper limits chosen to exclude regions adjacent to the galaxy continuum. Some bins with relatively high surface brightness, particularly near the edges of the plots, lack SNR labels because their higher noise causes them to fall below the threshold. Right: individual spectra from each bin (light gray), with the corresponding SNR label to the left. The solid black line shows the median spectrum, and the blue-shaded region encloses the 25th–75th percentiles. A vertical dashed line marks the wavelength corresponding to the systemic redshift of J0910b for each emission line, and the light-gray shaded regions denote the ±2 Å windows around [O III] λλ4959, 5007, Hβ, Hα, and [N II] λλ6548, 6583.
Paper: Kinematically Complex Circumgalactic Gas Around a Low-mass Galaxy: Filamentary Inflow and Counterrotation in J0910b
Authors: Zeren Lin, D. Christopher Martin, Mateusz Matuszewski, James D. Neill, Drew M. Miles, Vincent Picouet, Nikolaus Z. Prusinski, Keri Hoadley, Rosalie McGurk
Figure caption: White-band images (∼160 Å) of the field from KCWI-blue (top) and KCWI-red (bottom). Emission-line regions (e.g., Hβ, [O III], Hα, [N II]) and strong sky lines (e.g., [O I] λ5577) are excluded. Red and blue regions show positive and negative surface brightness, the latter due to continuum sources in the NAS sky field (J0910a) after sky subtraction. Black contours mark continuum detections (SNR = 5). Dark gray rectangles show the KCWI fields of view (offset2, offset3; Figure 1; Table B1). Both panels cover the same sky area: the KCWI-red rectangles appear broader due to larger dithers, while the KCWI-blue NAS rectangles are narrower due to more consistent pointings. The R.A./decl. grid (gray) appears diagonal because of the field rotation, with north pointing down-right and east up-right (see Figure 1 for orientation). Concentric circles have 5″ spacing (∼9 kpc at z = 0.096) with 30° azimuthal divisions, centered on J0910b.
Paper: Kinematically Complex Circumgalactic Gas Around a Low-mass Galaxy: Filamentary Inflow and Counterrotation in J0910b
Authors: Zeren Lin, D. Christopher Martin, Mateusz Matuszewski, James D. Neill, Drew M. Miles, Vincent Picouet, Nikolaus Z. Prusinski, Keri Hoadley, Rosalie McGurk
Figure caption: Emission maps for [O III] 5007 (top row) and Hα (bottom row) at varying SNR thresholds. Lowering the threshold reveals a modest expansion of the emission region, indicating an ionization-bounded structure. Surface brightness is measured in 10−16 erg cm−2 s−1 arcsec−2 in 4 Å bins for [O III] (5484–5488 Å) and Hα (7188–7192 Å). Lowering the threshold reveals a modest expansion of the emission region, indicating an ionization-bounded structure (discussed further in Section 5.2.2).
Paper: ORACLE: A Real-time, Hierarchical, Deep Learning Photometric Classifier for the LSST
Authors: Ved G. Shah, Alex Gagliano, Konstantin Malanchev, Gautham Narayan, Alex I. Malz
Figure caption: Distribution of the number of days (since trigger) required for confident classification of TDEs at the three levels of granularity. There is a clear increase in the granularity of confident classifications produced by ORACLE as more photometry becomes available at later times.
Paper: ORACLE: A Real-time, Hierarchical, Deep Learning Photometric Classifier for the LSST
Authors: Ved G. Shah, Alex Gagliano, Konstantin Malanchev, Gautham Narayan, Alex I. Malz
Figure caption: Confusion matrices for classification at the leaves, as a function of the number of days since event trigger.
Paper: ORACLE: A Real-time, Hierarchical, Deep Learning Photometric Classifier for the LSST
Authors: Ved G. Shah, Alex Gagliano, Konstantin Malanchev, Gautham Narayan, Alex I. Malz
Figure caption: Per-class F-1 scores for the level_1 (top) and level_2 (bottom) as a function of the number of days since event trigger, for the full ORACLE model (solid lines) as well as ORACLE-lite (dotted lines).
Paper: ORACLE: A Real-time, Hierarchical, Deep Learning Photometric Classifier for the LSST
Authors: Ved G. Shah, Alex Gagliano, Konstantin Malanchev, Gautham Narayan, Alex I. Malz
Figure caption: ROC curves for classification at the leaves, as a function of the number of days since the event trigger.
Paper: ORACLE: A Real-time, Hierarchical, Deep Learning Photometric Classifier for the LSST
Authors: Ved G. Shah, Alex Gagliano, Konstantin Malanchev, Gautham Narayan, Alex I. Malz
Figure caption: ROC curves for classification at level 1, as a function of the number of days since the event trigger.
Paper: ORACLE: A Real-time, Hierarchical, Deep Learning Photometric Classifier for the LSST
Authors: Ved G. Shah, Alex Gagliano, Konstantin Malanchev, Gautham Narayan, Alex I. Malz
Figure caption: Transient-host separation for Type II SNe and TDEs.
Paper: ORACLE: A Real-time, Hierarchical, Deep Learning Photometric Classifier for the LSST
Authors: Ved G. Shah, Alex Gagliano, Konstantin Malanchev, Gautham Narayan, Alex I. Malz
Figure caption: Confusion matrices for classification at level 2, as a function of the number of days since event trigger.
Paper: ORACLE: A Real-time, Hierarchical, Deep Learning Photometric Classifier for the LSST
Authors: Ved G. Shah, Alex Gagliano, Konstantin Malanchev, Gautham Narayan, Alex I. Malz
Figure caption: Examples of well-sampled light curves for CaRT, SNII, SNIax, and SNIb/c from the ELAsTiCC data set.
Paper: ORACLE: A Real-time, Hierarchical, Deep Learning Photometric Classifier for the LSST
Authors: Ved G. Shah, Alex Gagliano, Konstantin Malanchev, Gautham Narayan, Alex I. Malz
Figure caption: ROC curves for classification at level 2, as a function of the number of days since the event trigger.
Paper: Multiwavelength Observations of the Apparently Nonrepeating FRB 20250316A
Authors: Ye Li, Hui Sun, Lei Qian, Dong-Yue Li, Yan-Long Hua, Li-Ping Xin, Cheng-Kui Li, Yi-Han Wang, Jia-Rui Niu, Tian-Rui Sun, Zhu-Heng Yao, Jin-Jun Geng, Chi-Chuan Jin, Nanda Rea, Yuan Liu, Zhi-Chen Pan, Tao An, Vadim Burwitz, Zhi-Ming Cai, Jin-Huang Cao, Yong Chen, Hua-Qing Cheng, Wei-Wei Cui, Hua Feng, Peter Friedrich, Da-Wei Han, Jing-Wei Hu, Lei Hu, Yu-Xiang Huang, Shu-Mei Jia, Ji-An Jiang, Bin Li, Feng Li, Ming Liang, Yi-Fang Liang, Hao Liu, He-Yang Liu, Hua-Qiu Liu, Norbert Meidinger, Hai-Wu Pan, Arne Rau, Xin-Wen Shu, Chun Sun, Lian Tao, Jin-Long Tang, Zhen Wan, Hai-Ren Wang, Jian Wang, Jing Wang, Yun-Fei Xu, Yongquan Xue, Xuan Yang, Da-Zhi Yao, Yuhan Yao, Wen Zhao, Xiao-Fan Zhao, Hong-Fei Zhang, Jia-Heng Zhang, Juan Zhang, Mo Zhang, Song-Bo Zhang, Wen-Da Zhang, Xiao-Ling Zhang, Yong-He Zhang, Yong-Kun Zhang, Xian-Zhong Zheng, Yu-Hao Zhu, Ying-Xi Zuo, Sheng-Li Sun, Jian-Yan Wei, Wei-Wei Zhu, Peng Jiang, Weimin Yuan, Xue-Feng Wu, Bing Zhang
Figure caption: X-ray and optical images of the FRB 20250316A field. Top left: the EP-WXT image obtained from the observation 3.5 hr after the FRB, with the source and background regions marked for upper-limit analysis. Top right: the stacked image from all FXT observations, with a yellow circle centered on the position initially reported from the early detection. The red star marks the position of FRB 20250316A. Bottom left: Chandra image. An X-ray source CXOU J120943.7+585051 (cyan) offset by ∼7″ from the FRB position (red circle; projected distance: 1.36 kpc) is located within the error circle of EP J120944.2+585060 (yellow), along with one faint Chandra object (green) at a separation of ∼22″ from the first. Bottom right: WFST image. Both FRB 20250316A (red) and CXOU J120943.7+585051 (cyan) reside in separate extended regions.
Paper: Multiwavelength Observations of the Apparently Nonrepeating FRB 20250316A
Authors: Ye Li, Hui Sun, Lei Qian, Dong-Yue Li, Yan-Long Hua, Li-Ping Xin, Cheng-Kui Li, Yi-Han Wang, Jia-Rui Niu, Tian-Rui Sun, Zhu-Heng Yao, Jin-Jun Geng, Chi-Chuan Jin, Nanda Rea, Yuan Liu, Zhi-Chen Pan, Tao An, Vadim Burwitz, Zhi-Ming Cai, Jin-Huang Cao, Yong Chen, Hua-Qing Cheng, Wei-Wei Cui, Hua Feng, Peter Friedrich, Da-Wei Han, Jing-Wei Hu, Lei Hu, Yu-Xiang Huang, Shu-Mei Jia, Ji-An Jiang, Bin Li, Feng Li, Ming Liang, Yi-Fang Liang, Hao Liu, He-Yang Liu, Hua-Qiu Liu, Norbert Meidinger, Hai-Wu Pan, Arne Rau, Xin-Wen Shu, Chun Sun, Lian Tao, Jin-Long Tang, Zhen Wan, Hai-Ren Wang, Jian Wang, Jing Wang, Yun-Fei Xu, Yongquan Xue, Xuan Yang, Da-Zhi Yao, Yuhan Yao, Wen Zhao, Xiao-Fan Zhao, Hong-Fei Zhang, Jia-Heng Zhang, Juan Zhang, Mo Zhang, Song-Bo Zhang, Wen-Da Zhang, Xiao-Ling Zhang, Yong-He Zhang, Yong-Kun Zhang, Xian-Zhong Zheng, Yu-Hao Zhu, Ying-Xi Zuo, Sheng-Li Sun, Jian-Yan Wei, Wei-Wei Zhu, Peng Jiang, Weimin Yuan, Xue-Feng Wu, Bing Zhang
Figure caption: The timeline of the FRB 20250316A follow-up observations. For EP/WXT, only those observations within 12 hr before and after the FRB are presented. Vertical gray lines indicate the time of FRB 20250316A and the time at which FRB 20250316A was localized to be arcsecond accuracy.
Paper: ORACLE: A Real-time, Hierarchical, Deep Learning Photometric Classifier for the LSST
Authors: Ved G. Shah, Alex Gagliano, Konstantin Malanchev, Gautham Narayan, Alex I. Malz
Figure caption: Sample light curves, using SNANA calibrated flux (see Table 1, Equation (1)), from each of the 19 leaf classes. The predicted class score of the true class is plotted using a dotted black line. The detections are plotted using the star marker with error bars, while nondetections are plotted using the cross marker. Continued in Figure 20.
Paper: Multiwavelength Observations of the Apparently Nonrepeating FRB 20250316A
Authors: Ye Li, Hui Sun, Lei Qian, Dong-Yue Li, Yan-Long Hua, Li-Ping Xin, Cheng-Kui Li, Yi-Han Wang, Jia-Rui Niu, Tian-Rui Sun, Zhu-Heng Yao, Jin-Jun Geng, Chi-Chuan Jin, Nanda Rea, Yuan Liu, Zhi-Chen Pan, Tao An, Vadim Burwitz, Zhi-Ming Cai, Jin-Huang Cao, Yong Chen, Hua-Qing Cheng, Wei-Wei Cui, Hua Feng, Peter Friedrich, Da-Wei Han, Jing-Wei Hu, Lei Hu, Yu-Xiang Huang, Shu-Mei Jia, Ji-An Jiang, Bin Li, Feng Li, Ming Liang, Yi-Fang Liang, Hao Liu, He-Yang Liu, Hua-Qiu Liu, Norbert Meidinger, Hai-Wu Pan, Arne Rau, Xin-Wen Shu, Chun Sun, Lian Tao, Jin-Long Tang, Zhen Wan, Hai-Ren Wang, Jian Wang, Jing Wang, Yun-Fei Xu, Yongquan Xue, Xuan Yang, Da-Zhi Yao, Yuhan Yao, Wen Zhao, Xiao-Fan Zhao, Hong-Fei Zhang, Jia-Heng Zhang, Juan Zhang, Mo Zhang, Song-Bo Zhang, Wen-Da Zhang, Xiao-Ling Zhang, Yong-He Zhang, Yong-Kun Zhang, Xian-Zhong Zheng, Yu-Hao Zhu, Ying-Xi Zuo, Sheng-Li Sun, Jian-Yan Wei, Wei-Wei Zhu, Peng Jiang, Weimin Yuan, Xue-Feng Wu, Bing Zhang
Figure caption: The X-ray light curve of EP J120944.2+585060/CXOU J120943.7+585051 observed by EP-FXT (blue) and Chandra (green). Errors show 1σ statistical uncertainties. The dashed line shows the weighted mean flux derived from EP-FXT observations. The slightly higher flux measured by EP-FXT may be due to contamination from the nearby Chandra source.
Paper: ORACLE: A Real-time, Hierarchical, Deep Learning Photometric Classifier for the LSST
Authors: Ved G. Shah, Alex Gagliano, Konstantin Malanchev, Gautham Narayan, Alex I. Malz
Figure caption: Mean class scores (across all samples of the true class) for all leaf classes in the taxonomy as a function of days since trigger, categorized by the true class. The wide dashed line in each plot shows the mean class score (or pseudoprobability) of the true class. The shaded gray region highlights the pretrigger duration. Continued in Figure 18.
Paper: ORACLE: A Real-time, Hierarchical, Deep Learning Photometric Classifier for the LSST
Authors: Ved G. Shah, Alex Gagliano, Konstantin Malanchev, Gautham Narayan, Alex I. Malz
Figure caption: Continuation of data displayed in Figure 19.
Paper: Multiwavelength Observations of the Apparently Nonrepeating FRB 20250316A
Authors: Ye Li, Hui Sun, Lei Qian, Dong-Yue Li, Yan-Long Hua, Li-Ping Xin, Cheng-Kui Li, Yi-Han Wang, Jia-Rui Niu, Tian-Rui Sun, Zhu-Heng Yao, Jin-Jun Geng, Chi-Chuan Jin, Nanda Rea, Yuan Liu, Zhi-Chen Pan, Tao An, Vadim Burwitz, Zhi-Ming Cai, Jin-Huang Cao, Yong Chen, Hua-Qing Cheng, Wei-Wei Cui, Hua Feng, Peter Friedrich, Da-Wei Han, Jing-Wei Hu, Lei Hu, Yu-Xiang Huang, Shu-Mei Jia, Ji-An Jiang, Bin Li, Feng Li, Ming Liang, Yi-Fang Liang, Hao Liu, He-Yang Liu, Hua-Qiu Liu, Norbert Meidinger, Hai-Wu Pan, Arne Rau, Xin-Wen Shu, Chun Sun, Lian Tao, Jin-Long Tang, Zhen Wan, Hai-Ren Wang, Jian Wang, Jing Wang, Yun-Fei Xu, Yongquan Xue, Xuan Yang, Da-Zhi Yao, Yuhan Yao, Wen Zhao, Xiao-Fan Zhao, Hong-Fei Zhang, Jia-Heng Zhang, Juan Zhang, Mo Zhang, Song-Bo Zhang, Wen-Da Zhang, Xiao-Ling Zhang, Yong-He Zhang, Yong-Kun Zhang, Xian-Zhong Zheng, Yu-Hao Zhu, Ying-Xi Zuo, Sheng-Li Sun, Jian-Yan Wei, Wei-Wei Zhu, Peng Jiang, Weimin Yuan, Xue-Feng Wu, Bing Zhang
Figure caption: Averaged number of unrelated X-ray sources within the angular resolution for EP/FXT and Chandra telescope.
Paper: ORACLE: A Real-time, Hierarchical, Deep Learning Photometric Classifier for the LSST
Authors: Ved G. Shah, Alex Gagliano, Konstantin Malanchev, Gautham Narayan, Alex I. Malz
Figure caption: Continuation of data displayed in Figure 17.
Paper: 3D Modeling of Moist Convective Inhibition in Idealized Sub-Neptune Atmospheres
Authors: Namrah Habib, Raymond T. Pierrehumbert
Figure caption: Atmospheric state for the CM1 simulations initialized on (a) the dry then moist adiabat, (b) the moist adiabat, and (c) the superadiabatic state. In each row, the panels show from left to right, profiles of temperature (K), the temperature difference between the final and initial state (K), the vapor mixing ratio (kg kg−1), relative humidity, and vertical cross sections taken in the middle of the y-domain of vertical velocity (m s−1) and condensate mixing ratio (g kg−1). In the temperature panels, the gray dashed and solid lines plot dry and moist adiabats, and the gray dotted–dashed line plots the gray gas pure radiative-equilibrium temperature profile. The dashed gray line in the vapor mixing ratio panels indicates the critical vapor mixing ratio of the final state. Initial states are illustrated by blue lines in the profile plots, whereas the final state from the CM1 simulation is shown by the solid black line. The cross sections are shown for the final state. In panels (a) and (b), we observe only the initial stages of steeping toward a pure radiative-equilibrium superadiabatic state, as highlighted in the temperature difference profiles. The simulations show long radiative timescales, and the results presented here are not in a statistical-equilibrium state.
Paper: 3D Modeling of Moist Convective Inhibition in Idealized Sub-Neptune Atmospheres
Authors: Namrah Habib, Raymond T. Pierrehumbert
Figure caption: Snapshots of vertical velocity (top row), vapor mixing ratio (middle row), and condensate mixing ratio (bottom row) during the early rapid convective mixing phase in the isothermal simulations. All four isothermal simulations undergo a similar rapid convective mixing phase within the first 12–15 hr. Here, we present the early mixing of the qv,s < qcrit test case. Mixing initiates near the top of the domain, driven by dense parcels sinking. Within the convecting layer, as compensating rising air parcels become supersaturated, water vapor condenses within them. The condensate then falls through lower cells and evaporates in subsaturated grid cells. The convecting layer moves down through the atmosphere until it reaches the surface or a neutrally stable layer. In the isothermal simulation initialized with qv,s < qcrit (shown here), the convecting layer stops and stabilizes at the top of the Guillot stable region rather than reaching the surface, as in the other three isothermal simulations. After the initial rapid mixing, the isothermal simulations reach a convectively stable state, which is subsequently altered on a much slower timescale by radiative processes.
Paper: 3D Modeling of Moist Convective Inhibition in Idealized Sub-Neptune Atmospheres
Authors: Namrah Habib, Raymond T. Pierrehumbert
Figure caption: Eddy diffusivity (left panel) and vertical velocities (right panel) of the CM1 simulation initialized on a dry then moist adaibat. In the left panel, the eddy diffusivity from the sub-grid CM1 TKE scheme is shown in green, the resolved Kzz, calculated using Equation (18), is shown in black, and the eddy diffusivity from J. Leconte et al. (2024) is shown in blue. In the right panel, the rms velocity, as well as the maximum upward and maximum downward velocity from the CM1 simulation are shown in black solid, dashed, and dotted lines, respectively. The rms velocity profile from J. Leconte et al. (2024) is shown in blue for comparison. As before, the brown dashed lines mark the convectively stable region. Note, the J. Leconte et al. (2024) profile is shifted upward, such that the convective inhibition layer in their result lies within the brown dashed lines for comparative purposes.
Paper: 3D Modeling of Moist Convective Inhibition in Idealized Sub-Neptune Atmospheres
Authors: Namrah Habib, Raymond T. Pierrehumbert
Figure caption: Vertical velocity (top row) and condensate mixing ratio (bottom row) cross sections in (x, z) taken in the middle of the y-domain for five time steps in the CM1 simulation initialized on the dry adiabat to the level of saturation from which point the initial state followed a moist adiabat. The vertical velocity cross sections show three distinct layers: a dry convective region near the surface, a layer where convection is inhibited and velocities are nearly zero, and a layer of weak moist convection in the upper atmosphere. The corresponding condensate mixing ratio plots show that a cloud deck forms in the moist convection layer, and condensates fall through and evaporate in the convective inhibition layer.
Paper: 3D Modeling of Moist Convective Inhibition in Idealized Sub-Neptune Atmospheres
Authors: Namrah Habib, Raymond T. Pierrehumbert
Figure caption: Eddy diffusivity (left panel) and vertical velocities (right panel) of the CM1 simulation initialized on a moist adaibat. In the left panel, the eddy diffusivity from the CM1 test case is calculated using Equation (18). In the right panel, the rms velocity, as well as maximum upward and maximum downward velocity from the CM1 simulation are shown in black solid, dashed, and dotted lines, respectively. The green line plots the eddy diffusivity and vertical velocity output from the CM1 sub-grid turbulence parameterization. As before, the brown dashed lines mark the convectively stable region.
Paper: 3D Modeling of Moist Convective Inhibition in Idealized Sub-Neptune Atmospheres
Authors: Namrah Habib, Raymond T. Pierrehumbert
Figure caption: Domain-mean sensible and latent heat fluxes for the CM1 test case initialized on a dry then moist adiabat, averaged over the final 25 days of the simulation. The sharp drop off to zero sensible heat flux within the stable layer indicates suppressed convection. Latent heat flux dominates transport in the condensation-driven convective inhibition layer, and positive Qlatent values suggest upward vapor transport driven by evaporation.
Paper: 3D Modeling of Moist Convective Inhibition in Idealized Sub-Neptune Atmospheres
Authors: Namrah Habib, Raymond T. Pierrehumbert
Figure caption: Eddy diffusivity (left panel) and vertical velocities (right panel) of the CM1 simulation initialized on a superadiabatic profile. In the left panel, the eddy diffusivity from the CM1 test case is calculated using Equation (18) and shown by the black line. In the right panel, the rms velocity, as well as maximum upward and maximum downward velocity from the CM1 simulation are shown in black solid, dashed, and dotted lines, respectively. The green line plots the eddy diffusivity and vertical velocity output from the CM1 sub-grid turbulence parameterization. The brown dashed lines mark the convectively stable region.