adsabs/AstroCLIMB huggingface dataset:
Paper: DELIGHT: Deep Learning Identification of Galaxy Hosts of Transients using Multiresolution Images
Authors: Francisco Förster, Alejandra M. Muñoz Arancibia, Ignacio Reyes-Jainaga, Alexander Gagliano, Dylan Britt, Sara Cuellar-Carrillo, Felipe Figueroa-Tapia, Ava Polzin, Yara Yousef, Javier Arredondo, Diego Rodríguez-Mancini, Javier Correa-Orellana, Amelia Bayo, Franz E. Bauer, Márcio Catelan, Guillermo Cabrera-Vives, Raya Dastidar, Pablo A. Estévez, Giuliano Pignata, Lorena Hernández-García, Pablo Huijse, Esteban Reyes, Paula Sánchez-Sáez, Mauricio Ramírez, Daniela Grandón, Jonathan Pineda-García, Francisca Chabour-Barra, Javier Silva-Farfán
Figure caption: Three examples of how the semimajor axis of the galaxies were determined. In the top row we show SN2009jy; in the middle row, ZTF19acbwhqc; and in the bottom row, ZTF19acbwmqd. We show the original 480 × 480 pix PanSTARRS r-band image in the first column and the five central 30 × 30 pix multiresolution images in the following columns. The SExtractor detected object ellipses are shown, with the ellipse in black having the closest normalized distance from its center to the labeled position. The black arrow points to the best ellipse center, and the white and red dot mark the labeled host position. In the title, a is the semimajor axis, and error/a is the distance between the object’s inferred center and the labeled position divided by the semimajor axis. In the top row, the nearest normalized-distance object detected in level 1 is coincident with the labeled position within 1.4% of the inferred semimajor axis, so the associated semimajor axis, 17.″3, is accepted. In the middle row, the nearest normalized-distance object detected in level 3 is coincident with the labeled position within 1.3% of the inferred semimajor axis, so the associated semimajor axis, 3.″2, is accepted. In the bottom row, the nearest normalized-distance object detected in level 5 is coincident with the labeled position within 3.0% of the inferred semimajor axis, so the associated semimajor axis, 1.″0, is accepted. Note that the semimajor axis tends to be larger for lower-resolution images, that are more sensitive to faint surface brightness regions of the host galaxy. Also note that SExtractor cannot represent the largest galaxy correctly in the original resolution because of all the small-scale structures visible.
Paper: DELIGHT: Deep Learning Identification of Galaxy Hosts of Transients using Multiresolution Images
Authors: Francisco Förster, Alejandra M. Muñoz Arancibia, Ignacio Reyes-Jainaga, Alexander Gagliano, Dylan Britt, Sara Cuellar-Carrillo, Felipe Figueroa-Tapia, Ava Polzin, Yara Yousef, Javier Arredondo, Diego Rodríguez-Mancini, Javier Correa-Orellana, Amelia Bayo, Franz E. Bauer, Márcio Catelan, Guillermo Cabrera-Vives, Raya Dastidar, Pablo A. Estévez, Giuliano Pignata, Lorena Hernández-García, Pablo Huijse, Esteban Reyes, Paula Sánchez-Sáez, Mauricio Ramírez, Daniela Grandón, Jonathan Pineda-García, Francisca Chabour-Barra, Javier Silva-Farfán
Figure caption: DELIGHT architecture diagram. The input of the network are five 30 × 30 pixel images centered around the position of the candidate with different resolutions and fields of view (see Figure 2). This set of images is rotated and flipped to generate seven more sets used as parallel inputs to the network. Each image within each set is processed by a combination of convolutional layers with 3 × 3 kernel size, no padding, and ReLU activation functions (conv+relu), shown as yellow rectangular cuboids; and 2 × 2 max-pooling layers (max pool), shown as red rectangular cuboids. At this stage we use the same weights and biases for every image given that the problem is approximately scale-free. Each output is then flattened into 656 neuron vectors (purple rectangular cuboids), and the five flattened outputs are concatenated into a layer of 3280 neurons (purple rectangular cuboid). This layer is fully connected with a layer of 685 neurons using a tanh activation function (green cuboid), which is then fully connected to the two neuron output layer (small green cuboid) without activation function representing the predicted host center in pixels. Each of the eight sets of five images produces an output vector, which can be rotated/flipped to produce a cloud of eight predicted host centers per candidate.
Paper: DELIGHT: Deep Learning Identification of Galaxy Hosts of Transients using Multiresolution Images
Authors: Francisco Förster, Alejandra M. Muñoz Arancibia, Ignacio Reyes-Jainaga, Alexander Gagliano, Dylan Britt, Sara Cuellar-Carrillo, Felipe Figueroa-Tapia, Ava Polzin, Yara Yousef, Javier Arredondo, Diego Rodríguez-Mancini, Javier Correa-Orellana, Amelia Bayo, Franz E. Bauer, Márcio Catelan, Guillermo Cabrera-Vives, Raya Dastidar, Pablo A. Estévez, Giuliano Pignata, Lorena Hernández-García, Pablo Huijse, Esteban Reyes, Paula Sánchez-Sáez, Mauricio Ramírez, Daniela Grandón, Jonathan Pineda-García, Francisca Chabour-Barra, Javier Silva-Farfán
Figure caption: Prediction error vs. angular separation distance between the transient candidate and the host-galaxy center for the different methods tested in this work. Catastrophic errors are clustered near the identity line (gray, dotted lines). These errors correspond to cases where a large nearby host galaxy is confused with a smaller, distant galaxy, which is closer in projection.
Paper: DELIGHT: Deep Learning Identification of Galaxy Hosts of Transients using Multiresolution Images
Authors: Francisco Förster, Alejandra M. Muñoz Arancibia, Ignacio Reyes-Jainaga, Alexander Gagliano, Dylan Britt, Sara Cuellar-Carrillo, Felipe Figueroa-Tapia, Ava Polzin, Yara Yousef, Javier Arredondo, Diego Rodríguez-Mancini, Javier Correa-Orellana, Amelia Bayo, Franz E. Bauer, Márcio Catelan, Guillermo Cabrera-Vives, Raya Dastidar, Pablo A. Estévez, Giuliano Pignata, Lorena Hernández-García, Pablo Huijse, Esteban Reyes, Paula Sánchez-Sáez, Mauricio Ramírez, Daniela Grandón, Jonathan Pineda-García, Francisca Chabour-Barra, Javier Silva-Farfán
Figure caption: Comparison between the true host position and the DELIGHT-predicted position in 10 random examples from the ALeRCE sample. Each column shows the set of five multiresolution images for a given galaxy, from smallest to largest field of view (highest to smallest resolution) from top to bottom. The red solid arrows represent the true host position (obtained via visual crossmatching with catalog positions in NED, SIMBAD, and SDSS DR16), the black dotted arrows represent the mean DELIGHT-predicted position, and the violet points represent the eight DELIGHT-predicted positions for the eight rotations and flips.
Paper: DELIGHT: Deep Learning Identification of Galaxy Hosts of Transients using Multiresolution Images
Authors: Francisco Förster, Alejandra M. Muñoz Arancibia, Ignacio Reyes-Jainaga, Alexander Gagliano, Dylan Britt, Sara Cuellar-Carrillo, Felipe Figueroa-Tapia, Ava Polzin, Yara Yousef, Javier Arredondo, Diego Rodríguez-Mancini, Javier Correa-Orellana, Amelia Bayo, Franz E. Bauer, Márcio Catelan, Guillermo Cabrera-Vives, Raya Dastidar, Pablo A. Estévez, Giuliano Pignata, Lorena Hernández-García, Pablo Huijse, Esteban Reyes, Paula Sánchez-Sáez, Mauricio Ramírez, Daniela Grandón, Jonathan Pineda-García, Francisca Chabour-Barra, Javier Silva-Farfán
Figure caption: Distribution of errors between the predicted and labeled positions of the hosts using different methods (see Section 2) compared to the distribution of host angular separations from the position of the transient. We use both linear and logarithmic scales in the errors (left and right, respectively), and a regular and cumulative histogram (top and bottom, respectively).
Paper: DELIGHT: Deep Learning Identification of Galaxy Hosts of Transients using Multiresolution Images
Authors: Francisco Förster, Alejandra M. Muñoz Arancibia, Ignacio Reyes-Jainaga, Alexander Gagliano, Dylan Britt, Sara Cuellar-Carrillo, Felipe Figueroa-Tapia, Ava Polzin, Yara Yousef, Javier Arredondo, Diego Rodríguez-Mancini, Javier Correa-Orellana, Amelia Bayo, Franz E. Bauer, Márcio Catelan, Guillermo Cabrera-Vives, Raya Dastidar, Pablo A. Estévez, Giuliano Pignata, Lorena Hernández-García, Pablo Huijse, Esteban Reyes, Paula Sánchez-Sáez, Mauricio Ramírez, Daniela Grandón, Jonathan Pineda-García, Francisca Chabour-Barra, Javier Silva-Farfán
Figure caption: Crossmatched photometric redshift differences. Top row: scatter plots of the redshifts determined using the method’s predicted position vs. its difference with the redshift determined using the true host position, indicating the fraction of crossmatches with the given method (a proxy for completeness). Bottom row: histograms of the redshift errors, indicating the fraction of errors whose absolute value is larger than 0.05, a proxy for contamination.
Paper: DELIGHT: Deep Learning Identification of Galaxy Hosts of Transients using Multiresolution Images
Authors: Francisco Förster, Alejandra M. Muñoz Arancibia, Ignacio Reyes-Jainaga, Alexander Gagliano, Dylan Britt, Sara Cuellar-Carrillo, Felipe Figueroa-Tapia, Ava Polzin, Yara Yousef, Javier Arredondo, Diego Rodríguez-Mancini, Javier Correa-Orellana, Amelia Bayo, Franz E. Bauer, Márcio Catelan, Guillermo Cabrera-Vives, Raya Dastidar, Pablo A. Estévez, Giuliano Pignata, Lorena Hernández-García, Pablo Huijse, Esteban Reyes, Paula Sánchez-Sáez, Mauricio Ramírez, Daniela Grandón, Jonathan Pineda-García, Francisca Chabour-Barra, Javier Silva-Farfán
Figure caption: Comparison between spectroscopic and photometric redshifts in the test-set crossmatched sample. The photometric error dispersion considering all the samples is 0.051, and the dispersion after removing redshift errors with absolute value larger than 0.5 is 0.026.
Paper: DELIGHT: Deep Learning Identification of Galaxy Hosts of Transients using Multiresolution Images
Authors: Francisco Förster, Alejandra M. Muñoz Arancibia, Ignacio Reyes-Jainaga, Alexander Gagliano, Dylan Britt, Sara Cuellar-Carrillo, Felipe Figueroa-Tapia, Ava Polzin, Yara Yousef, Javier Arredondo, Diego Rodríguez-Mancini, Javier Correa-Orellana, Amelia Bayo, Franz E. Bauer, Márcio Catelan, Guillermo Cabrera-Vives, Raya Dastidar, Pablo A. Estévez, Giuliano Pignata, Lorena Hernández-García, Pablo Huijse, Esteban Reyes, Paula Sánchez-Sáez, Mauricio Ramírez, Daniela Grandón, Jonathan Pineda-García, Francisca Chabour-Barra, Javier Silva-Farfán
Figure caption: Distribution of the DELIGHT prediction errors and SExtractor-inferred host semimajor axes using logarithmic bins. Dotted lines indicate the region where errors would equal the SExtractor semimajor axis and the inferred isophotal semimajor axis (3 times the SExtractor semimajor axis).
Paper: DELIGHT: Deep Learning Identification of Galaxy Hosts of Transients using Multiresolution Images
Authors: Francisco Förster, Alejandra M. Muñoz Arancibia, Ignacio Reyes-Jainaga, Alexander Gagliano, Dylan Britt, Sara Cuellar-Carrillo, Felipe Figueroa-Tapia, Ava Polzin, Yara Yousef, Javier Arredondo, Diego Rodríguez-Mancini, Javier Correa-Orellana, Amelia Bayo, Franz E. Bauer, Márcio Catelan, Guillermo Cabrera-Vives, Raya Dastidar, Pablo A. Estévez, Giuliano Pignata, Lorena Hernández-García, Pablo Huijse, Esteban Reyes, Paula Sánchez-Sáez, Mauricio Ramírez, Daniela Grandón, Jonathan Pineda-García, Francisca Chabour-Barra, Javier Silva-Farfán
Figure caption: Histogram of test-set spectroscopic and photometric redshifts obtained after crossmatching the labeled host positions with SDSS DR17 using a search radius of 0.′5.
Paper: Extremely Low Mass Ratio Contact Binaries. I. The First Photometric and Spectroscopic Investigations of Ten Systems
Authors: Kai Li, Xiang Gao, Xin-Yi Liu, Xing Gao, Ling-Zhi Li, Xu Chen, Guo-You Sun
Figure caption: The H α  line region of LAMOST spectra of the ten binaries, the red lines represent the spectra of the targets, the black lines refer to the synthesized spectra produced by STARMOD, while the blue ones display the subtracted spectra. All the ten targets exhibit obvious excess H α  emission lines.
Paper: Extremely Low Mass Ratio Contact Binaries. I. The First Photometric and Spectroscopic Investigations of Ten Systems
Authors: Kai Li, Xiang Gao, Xin-Yi Liu, Xing Gao, Ling-Zhi Li, Xu Chen, Guo-You Sun
Figure caption: The relation between logJorb and logM  T  of the detached binaries from Eker et al. (2006) and the contact binaries from Li et al. (2021b). The crosses represent the detached binaries, the solid circles display the contact binaries, and the open circles denote our ten targets. The dashed line refers to the boundary between detached and contact binaries derived by Eker et al. (2006).
Paper: Extremely Low Mass Ratio Contact Binaries. I. The First Photometric and Spectroscopic Investigations of Ten Systems
Authors: Kai Li, Xiang Gao, Xin-Yi Liu, Xing Gao, Ling-Zhi Li, Xu Chen, Guo-You Sun
Figure caption: The M-R and M-L diagrams for the ten contact binaries, the solid line represents the ZAMS line, while the dashed one refers the TAMS line. The solid circles display the primary components, while the open ones plot the secondary ones.
Paper: Extremely Low Mass Ratio Contact Binaries. I. The First Photometric and Spectroscopic Investigations of Ten Systems
Authors: Kai Li, Xiang Gao, Xin-Yi Liu, Xing Gao, Ling-Zhi Li, Xu Chen, Guo-You Sun
Figure caption: The relationship between the period (P) and semimajor axis (a) of the contact binaries whose temperatures are smaller than 10000 K taken from Li et al. (2021b).
Paper: Blackbody Temperature of 200+ Stellar Flares Observed with the CoRoT Satellite
Authors: M. Cristina Rabello Soares, Marcia C. de Freitas, Bernardo P. L. Ferreira
Figure caption: First row: weighted mean flare temperatures, ﹩{\bar{T}}_{\mathrm{flare}}﹩(k), of the 209 flares and their standard deviation, ﹩{\sigma }_{{T}_{\mathrm{flare}}}(k)﹩. The flares in a given star are shown in the same color. They are ordered with increasing mean temperature of all flares in a given star. Second row: same as the first row, but as function of spectral type, going from late- to early-type stars, in intervals of half a spectral class. The spectral type at the center of each interval is shown at the bottom of the panel. Inside each spectral class interval, the flare temperatures are in ascending order. The different colors are for the different luminosity classes. Third row: weighted average of the temperature of the flares vs. the average of the spectral subclass corresponding to the flares within each interval of half a spectral class. The averages for a given luminosity class, when there are four or more flares, are shown in different colors (as in the second row). The averages including all luminosity classes are shown in black, and their linear regression is given by the black dashed line. The vertical error bars correspond to the standard deviation of the flare temperature weighted average, and the horizontal error bars correspond to the standard deviation of the average of the spectral subclass. The absence of a horizontal bar means that only one spectral type was used in the temperature averaged.
Paper: Blackbody Temperature of 200+ Stellar Flares Observed with the CoRoT Satellite
Authors: M. Cristina Rabello Soares, Marcia C. de Freitas, Bernardo P. L. Ferreira
Figure caption: Top: weighted mean of the wavelength limits for each light curve, ﹩{\bar{\lambda }}_{\mathrm{Blue}}(l)﹩ (blue symbols) and ﹩{\bar{\lambda }}_{\mathrm{Red}}(l)﹩ (red symbols), as a function of the observed mean stellar flux in the Red channel, ﹩{F}_{\mathrm{Red}}^{\mathrm{obs}}(l)﹩, divided by its maximum value among the analyzed light curves. The error bars correspond to the uncertainties in the weighted averages. The limits of a given light curve in the Blue and Red channels are connected by a vertical dashed black line for better visualization. We observe an increase in ﹩{\bar{\lambda }}_{\mathrm{Red}}﹩ at small values of the stellar Red flux, indicating a narrowing of this channel. We do not observe any variation in the wavelength limits as a function of the Blue or White stellar flux. Bottom: the CoRoT Response Function for the Faint Stars channel (Figure 14 in Auvergne et al. 2009) is shown in black. The wavelength limits (from the top panel) are shown in the color of their respective band. The ones for the Red channel are displaced vertically by −0.04 for a better visualization.
Paper: Blackbody Temperature of 200+ Stellar Flares Observed with the CoRoT Satellite
Authors: M. Cristina Rabello Soares, Marcia C. de Freitas, Bernardo P. L. Ferreira
Figure caption: Flare energy ratio, E Blue/E Red, as a function of flare temperature, ﹩{T}_{\mathrm{flare}}﹩, given by the rightmost term in Equation (9). Each color is for a given light curve l. For a better visualization, only light curves with three or more observed flares are plotted. The filled circles are the observed flare energy ratio and the correspondent estimated flare temperature, ﹩{T}_{\mathrm{flare}}﹩(k).
Paper: Blackbody Temperature of 200+ Stellar Flares Observed with the CoRoT Satellite
Authors: M. Cristina Rabello Soares, Marcia C. de Freitas, Bernardo P. L. Ferreira
Figure caption: ED observed in the Blue channel vs. in the Red channel. There are 209 flares observed in both the Red and Blue channels, shown as black circles. A similar number of flares is only seen in the Blue or Red channel, which are shown as small blue and red diamonds, respectively, with the ED on the other channel set to 1. The solid green line is given by EDBlue = 2.36 EDRed.
Paper: Blackbody Temperature of 200+ Stellar Flares Observed with the CoRoT Satellite
Authors: M. Cristina Rabello Soares, Marcia C. de Freitas, Bernardo P. L. Ferreira
Figure caption: Blue vs. Red flare peak amplitude normalized by its quiescent state shown as black circles. Flares that are only seen in the Blue or Red channel are shown as small blue and red diamonds, respectively, with the peak amplitude ratio on the other channel set to 0.001. The solid green line corresponds to (a 0/F qu)Blue = 2.75 (a 0/F qu)Red.
Paper: Blackbody Temperature of 200+ Stellar Flares Observed with the CoRoT Satellite
Authors: M. Cristina Rabello Soares, Marcia C. de Freitas, Bernardo P. L. Ferreira
Figure caption: Flare light curves for CoRoT 106048015 obtained in the Blue (left) and Red (right) channels. The solid line shows the fitted model.
Paper: NGC 6153: Reality is Complicated 
Authors: Michael G. Richer, Anabel Arrieta, Lorena Arias, Lesly Castañeda-Carlos, Silvia Torres-Peimbert, José Alberto López, Adolfo Galindo
Figure caption: These panels present the PV diagrams of the [O III] λ4363,4959 lines and the [O III] temperature (bottom). The contours in all panels are those of the intensity of [O III] λ4363. The white color in the temperature map includes positions with zero values or unphysical values. There is a mild temperature gradient from the zone close to the central star (near the systemic velocity and in the middle of the slit) to zones farther away (the smallest and largest velocities and toward the top of the slit).
Paper: NGC 6153: Reality is Complicated 
Authors: Michael G. Richer, Anabel Arrieta, Lorena Arias, Lesly Castañeda-Carlos, Silvia Torres-Peimbert, José Alberto López, Adolfo Galindo
Figure caption: These panels present the PV diagrams of the lines of [Ar III] λ7135,7751,5191 in the left column and the [Ar III] temperature from the [Ar III] λλ5191/7135 and 5191/7751 line ratios in the right column. The contours are of the intensity of the [Ar III] λ7135 line. The color scale in the right column is the same as that used for the [O III] temperature in Figure 14.
Paper: NGC 6153: Reality is Complicated 
Authors: Michael G. Richer, Anabel Arrieta, Lorena Arias, Lesly Castañeda-Carlos, Silvia Torres-Peimbert, José Alberto López, Adolfo Galindo
Figure caption: These panels present the ratio of Hβ (left column) and Hγ (right column) with respect to [O III] λ4959. The ratio images assume temperatures of 3000 K, 6000 K, 8000 K, and 10,000 K (top to bottom) when broadening the PV diagram of [O III] λ4959. In the top row, the contours are those of the PV diagram for [O III] λ4959. In the bottom row, the contours are those of Hβ (left column) and Hγ (right column). The ratios best approximate a constant value for a temperature of 8000 K.
Paper: NGC 6153: Reality is Complicated 
Authors: Michael G. Richer, Anabel Arrieta, Lorena Arias, Lesly Castañeda-Carlos, Silvia Torres-Peimbert, José Alberto López, Adolfo Galindo
Figure caption: These panels present the ratios of the PV diagrams of the C II, N II, O II, and Ne II lines, as indicated in each panel. In all panels, the contours are of the intensity of the numerator. No correction for thermal broadening was applied to any of the PV diagrams. The C II λ4267/O II λ4649 and O II λλ6509,6510/N II λ5680 ratios required modeling multiple C II and O II lines. The horizontal bands in the O II λ6509/N II λ5680 ratio are due to the poor background subtraction for O II λ6509. The ratio of PV diagrams all approximate a constant value, indicating that these permitted lines of C II, N II, O II, and Ne II arise from the same plasma component.
Paper: NGC 6153: Reality is Complicated 
Authors: Michael G. Richer, Anabel Arrieta, Lorena Arias, Lesly Castañeda-Carlos, Silvia Torres-Peimbert, José Alberto López, Adolfo Galindo
Figure caption: These panels present the ratio of the PV diagram of He I λ4471 (left column) and He I λ4922 (right column) with respect to [O III] λ4959. The ratios assume temperatures of 3000 K, 6000 K, 8000 K, and 10,000 K (top to bottom). In the top row, the contours are those of the PV diagram for [O III] λ4959. In the bottom row, the contours are those of He I λ4471 (left) and He I λ4922 (right). Again, the ratios are most constant for a temperature of 8000 K.
Paper: NGC 6153: Reality is Complicated 
Authors: Michael G. Richer, Anabel Arrieta, Lorena Arias, Lesly Castañeda-Carlos, Silvia Torres-Peimbert, José Alberto López, Adolfo Galindo
Figure caption: These panels present the PV diagrams for the O II λ4649 and [O III] λ4959 lines and the ratio O II λ4649/[O III] λ4959. The contours represent the intensity of the O II λ4649 line. Both lines are single lines from the CD2 wavelength interval from the same ion, so there are no corrections for the intrinsic line structure or thermal broadening (supposing they arise from the same plasma component). The solid black color at the right is due to contamination of the PV diagram of O II λ4649 by C III λ4650.
Paper: NGC 6153: Reality is Complicated 
Authors: Michael G. Richer, Anabel Arrieta, Lorena Arias, Lesly Castañeda-Carlos, Silvia Torres-Peimbert, José Alberto López, Adolfo Galindo
Figure caption: These panels present the ratio of the He I λ4922 line with respect to Hβ (left column) and Hγ (right column), assuming temperatures of 3000 K, 6000 K, 8000 K, and 10,000 K (top to bottom). The contours are those of the PV diagram for He I λ4922 in the top row, but of Hβ (left) and Hγ (right) in the bottom row. The ratios are most constant when the assumed temperature to broaden the He I lines is 8000 K.
Paper: NGC 6153: Reality is Complicated 
Authors: Michael G. Richer, Anabel Arrieta, Lorena Arias, Lesly Castañeda-Carlos, Silvia Torres-Peimbert, José Alberto López, Adolfo Galindo
Figure caption: Left panel: this plot presents the line profile for the spatial interval used to compute the velocity splitting (see Figure 2) for the [O III] λ4959 line as well as the models based upon this line for the Hβ and He I λ4471 lines. Right panel: this plot presents the model of the Hβ line based upon the [O III] λ4959 line from the left panel as well as the profiles of this model after broadening with a Gaussian to match the thermal line width of the Hβ line for temperatures of 3000 K, 6000 K, 8000 K, and 10,000 K. The latter is the largest modification made to the [O III] line profile.