We report the first spatially resolved detection of the near-infrared [C I] λ8727 emission from the outer pair of low-ionization structures in the planetary nebula NGC 7009 from data obtained by the Multi Unit Spectroscopic Explorer integral field unit. This atomic carbon emission marks the transition zone between ionized and neutral gas and for

We analyze the evolution of massive (log 10[M ⋆/M ⊙] > 10) galaxies at z ∼ 4–8 selected from JWST Cosmic Evolution Early Release Survey (CEERS). We infer the physical properties of all galaxies in the CEERS NIRCam imaging through spectral energy distribution (SED) fitting with dense basis to select a sample of high-redshift massive galaxies. Where

Time-domain astrophysics continues to grow rapidly, with the inception of new surveys drastically increasing data volumes. Democratized, distributed approaches to training sets for machine learning classifiers are crucial to make the most of this torrent of discovery - with citizen science approaches proving effective at meeting these requirements

We present the analysis of the microlensing event OGLE-2015-BLG-0845, which was affected by both the microlensing parallax and xallarap effects. The former was detected via the simultaneous observations from the ground and Spitzer, and the latter was caused by the orbital motion of the source star in a relatively close binary. The combination of

NGC 5128 (Cen A) is the nearest giant elliptical galaxy and one of the brightest extragalactic radio sources in the sky, boasting a prominent dust lane and jets emanating from its nuclear supermassive black hole. In this paper, we construct the star formation history (SFH) of two small fields in the halo of NGC 5128: a northeastern field (Field 1)

Current and future Type Ia Supernova (SN Ia) surveys will need to adopt new approaches to classifying SNe and obtaining their redshifts without spectra if they wish to reach their full potential. We present here a novel approach that uses only photometry to identify SNe Ia in the 5-yr Dark Energy Survey (DES) data set using the SUPERNNOVA