The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015–2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14 000 deg² of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance.

The rare case of changing-look (CL) active galactic nuclei (AGNs), with the appearance or disappearance of broad Balmer emission lines within a few years, challenges our understanding of the AGN unified model. We present a sample of 21 new CL AGNs at 0.08 < z < 0.58 , which doubles the number of such objects known to date. These new CL AGNs were discovered in various ways, from (1) repeat spectra in the SDSS, (2) repeat spectra in the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) and SDSS, and (3) photometric variability and new spectroscopic observations. We use the photometric data from surveys, including the SDSS imaging survey, the Pan-STARRS1, the DESI Legacy imaging survey, the Wide-field Infrared Survey Explorer (WISE), the Catalina Real-time Transient Survey, and the Palomar Transient Factory. The estimated upper limits of the transition timescale of the CL AGNs in this sample spans from 0.9 to 13 years in the rest-frame. The continuum flux in the optical and mid-infrared becomes brighter when the CL AGNs turn on, or vice versa. Variations of more than 0.2 mag in the W1 band were detected in 15 CL AGNs during the transition. The optical and mid-infrared variability is not consistent with the scenario of variable obscuration in 10 CL AGNs at more than the 3σ confidence level. We confirm a bluer-when-brighter trend in the optical. However, the mid-infrared WISE colors W1–W2 become redder when the objects become brighter in the W1 band, possibly due to a stronger hot dust contribution in the W2 band when the AGN activity becomes stronger. The physical mechanism of type transition is important for understanding the evolution of AGNs.

We present Data Releases 4 and 5 of the quasar catalog from the quasar survey by the Large Sky Area Multi-object Fiber Spectroscopic Telescope (LAMOST), which includes quasars observed between 2015 September and 2017 June. There are a total of 19,253 quasars identified by visual inspections of the spectra. Among them, 11,458 were independently discovered by LAMOST, in which 3296 were reported by the SDSS DR12 and DR14 quasar catalog after our survey began, while the remaining 8162 are new discoveries of LAMOST. We provide the emission line measurements for Hα, Hβ, Mg ii, and/or C iv for 18,100 quasars. Since LAMOST does not have absolute flux calibration information, we obtain the monochromatic continuum luminosities by fitting the SDSS photometric data using the quasar spectra, and then estimate the black hole masses. The catalog and spectra for these quasars are available online. This is the third installment in the series of LAMOST quasar surveys that has released spectra for ∼43,000 quasars to date. There are 24,772 independently discovered quasars, 17,128 of which are newly discovered. In addition to this great supplement to the new quasar discoveries, LAMOST has also provided a large database (overlapped with SDSS) for investigating quasar spectral variability and discovering unusual quasars, including changing-look quasars, with ongoing and upcoming large surveys.

We report the fourth installment in the series of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) quasar survey, which includes quasars observed between 2017 September and 2021 June. There are in total 13,066 quasars reliably identified, of which 6685 are newly discovered that are not reported in the Sloan Digital Sky Survey (SDSS) DR14 quasar catalog or Million Quasars catalog. Because LAMOST does not provide accurate absolute flux calibration, we recalibrate the spectra with the SDSS/Pan-STARRS1 multiband photometric data. The emission-line properties of Hα, Hβ, Mg ii, and C iv and the continuum luminosities are measured by fitting the recalibrated spectra. We also estimate the single-epoch virial black hole masses (M _BH) using the derived emission-line and continuum parameters. This is the first time that the emission-line and continuum fluxes were estimated based on LAMOST recalibrated quasar spectra. The catalog and spectra for these quasars are available online. After the 9 yr LAMOST quasar survey, there are in total 56,175 identified quasars, of which 24,127 are newly discovered. The LAMOST quasar survey not only discovers a great number of new quasars but also provides a database for investigating the spectral variability of the quasars observed by both LAMOST and SDSS and finding rare quasars, including changing-look quasars and broad absorption line quasars.

Quasars behind the Galactic plane (GPQs) are important astrometric references and useful probes of Milky Way gas. However, the search for GPQs is difficult due to large extinctions and high source densities in the Galactic plane. Existing selection methods for quasars developed using high Galactic latitude (high-b) data cannot be applied to the Galactic plane directly because the photometric data obtained from high-b regions and the Galactic plane follow different probability distributions. To alleviate this data set shift problem for quasar candidate selection, we adopt a transfer-learning framework at both the data and algorithm levels. At the data level, to make a training set in which a data set shift is modeled, we synthesize quasars and galaxies behind the Galactic plane based on SDSS sources and the Galactic dust map. At the algorithm level, to reduce the effect of class imbalance, we transform the three-class classification problem for stars, galaxies, and quasars into two binary classification tasks. We apply the XGBoost algorithm to Pan-STARRS1 (PS1) and AllWISE photometry for classification and an additional cut on Gaia proper motion to remove stellar contaminants. We obtain a reliable GPQ candidate catalog with 160,946 sources located at ∣b∣ ≤ 20° in the PS1-AllWISE footprint. Photometric redshifts of GPQ candidates achieved with the XGBoost regression algorithm show that our selection method can identify quasars in a wide redshift range (0 < z ≲ 5). This study extends the systematic searches for quasars to the dense stellar fields and shows the feasibility of using astronomical knowledge to improve data mining under complex conditions in the big-data era.

Quasars behind the Galactic plane (GPQs) are important astrometric references and valuable probes of Galactic gas, yet the search for GPQs is difficult due to severe extinction and source crowding in the Galactic plane. In this paper, we present a sample of 204 spectroscopically confirmed GPQs at ∣b∣ < 20°, 191 of which are new discoveries. This GPQ sample covers a wide redshift range from 0.069 to 4.487. For the subset of 230 observed GPQ candidates, the lower limit of the purity of quasars is 85.2%, and the lower limit of the fraction of stellar contaminants is 6.1%. Using a multicomponent spectral fitting, we measure the emission line and continuum flux of the GPQs, and estimate their single-epoch virial black hole masses. Due to selection effects raised from Galactic extinction and target magnitude, these GPQs have higher black hole masses and continuum luminosities in comparison to the SDSS DR7 quasar sample. The spectral-fitting results and black hole mass estimates are compiled into a main spectral catalog, and an extended spectral catalog of GPQs. The successful identifications prove the reliability of both our GPQ selection methods and the GPQ candidate catalog, shedding light on the astrometric and astrophysical programs that make use of a large sample of GPQs in the future.