--- license: cc-by-4.0 task_categories: - image-to-image tags: - astronomy - supernovae - panstarrs - delight size_categories: - 100K

Column	Type	Description
Image and label
`image`	`(5,1,30,30)` float32	Multi-resolution PanSTARRS r-band cutout, centered on the simulated transient position.
`host_pos`	float32 × 2	Offset `[x, y]` from the simulated transient to the host galaxy, in level-0 pixels.
Identification
`oid`	string	Identifier of the real transient this galaxy came from. Repeats across the draws of the same galaxy.
`host_name`	string	Catalog name of the host galaxy.
Host galaxy
`host_redshift`	float64	Redshift of the host; `NaN` when unknown.
`hostsize`	float64	Angular size of the host galaxy from the catalog.
`host_ra`	float64	Right ascension of the host, in degrees.
`host_dec`	float64	Declination of the host, in degrees.
Real transient position
`meanra`	float64	Mean right ascension of the real transient, in degrees. Not the center of this cutout.
`meandec`	float64	Mean declination of the real transient, in degrees. Not the center of this cutout.
`sn_ra`	float64	Right ascension of the real supernova, in degrees.
`sn_dec`	float64	Declination of the real supernova, in degrees.
Sérsic fit — r band, from CasJobs
`rSerRadius`	float64	Effective radius Re of the r-band Sérsic fit, in arcsec. Defines the sampling region.
`rSerMag`	float64	Magnitude of the r-band Sérsic fit.
`rSerAb`	float64	Axis ratio b/a of the fitted ellipse, between 0 and 1. Defines the sampling region.
`rSerPhi`	float64	Position angle of the fitted ellipse, in degrees. Defines the sampling region.
`rSerRa`	float64	Right ascension of the Sérsic fit center, in degrees.
`rSerDec`	float64	Declination of the Sérsic fit center, in degrees.
Cross-validation
`fold`	int64	Cross-validation fold, from 1 to 5, inherited from the source galaxy.

## References [1] Förster, F., Muñoz Arancibia, A. M., Reyes-Jainaga, I., et al. 2022, *DELIGHT: Deep Learning Identification of Galaxy Hosts of Transients using Multiresolution Images*, The Astronomical Journal, 164, 195. [doi:10.3847/1538-3881/ac912a](https://doi.org/10.3847/1538-3881/ac912a) ```bibtex @article{Forster_2022, doi = {10.3847/1538-3881/ac912a}, url = {https://doi.org/10.3847/1538-3881/ac912a}, year = {2022}, month = {oct}, publisher = {The American Astronomical Society}, volume = {164}, number = {5}, pages = {195}, author = {F\"orster, Francisco and Mu\~noz Arancibia, Alejandra M. and Reyes-Jainaga, Ignacio and Gagliano, Alexander and Britt, Dylan and Cuellar-Carrillo, Sara and Figueroa-Tapia, Felipe and Polzin, Ava and Yousef, Yara and Arredondo, Javier and Rodr\'iguez-Mancini, Diego and Correa-Orellana, Javier and Bayo, Amelia and Bauer, Franz E. and Catelan, M\'arcio and Cabrera-Vives, Guillermo and Dastidar, Raya and Est\'evez, Pablo A. and Pignata, Giuliano and Hern\'andez-Garc\'ia, Lorena and Huijse, Pablo and Reyes, Esteban and S\'anchez-S\'aez, Paula and Ram\'irez, Mauricio and Grand\'on, Daniela and Pineda-Garc\'ia, Jonathan and Chabour-Barra, Francisca and Silva-Farf\'an, Javier}, title = {DELIGHT: Deep Learning Identification of Galaxy Hosts of Transients using Multiresolution Images}, journal = {The Astronomical Journal}, } ```