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The James Webb Space Telescope (JWST) observations have revolutionized extragalactic research, particularly with the discovery of little red dots (LRD), which we propose are dust-reddened broad-line active galactic nuclei (AGNs). Their unique v-shape spectral feature observed through JWST/NIRCam challenges us to discern the relative contributions of the galaxy and AGN. We study a spectral energy distribution (SED) model for LRDs from rest-frame UV to infrared bands. We hypothesize that the incident radiation from an AGN, characterized by a typical SED, is embedded in an extended dusty medium with an extinction law similar to those seen in dense regions such as Orion Nebula or certain AGN environments. The UV-optical spectrum is described by dust-attenuated AGN emission, featuring a red optical continuum at $\lambda>4000$ A and a flat UV spectral shape established through a gray extinction curve at $\lambda<3000$ A, due to the absence of small-size grains. There is no need for additional stellar emission or AGN scattered light. In the infrared, the SED is shaped by an extended dust and gas distribution ($\gamma<1$; $\rho\propto r^{-\gamma}$) with a characteristic gas density of $\simeq 10-10^3~{\rm cm}^{-3}$, which allows relatively cool dust temperatures to dominate the radiation, thereby shifting the energy peak from near- to mid-infrared bands. This model, unlike the typical AGN hot torus models, can produce an infrared SED flattening that is consistent with LRD observations through JWST MIRI. Such a density structure can arise from the coexistence of inflows and outflows during the early assembly of galactic nuclei. This might be the reason why LRDs emerge preferentially in the high-redshift universe younger than one billion years., Comment: 14 pages, 6 figures

We report on the discovery of two low-luminosity, broad-line AGN at $z>5$ identified using JWST NIRSpec spectroscopy from the CEERS Survey. We detect broad H$\alpha$ emission from both sources, with FWHM of $2038\pm286$ and $1807\pm207$ km s$^{-1}$, resulting in black hole (BH) masses that are 1-2 dex below that of existing samples of luminous quasars at $z>5$. The first source, CEERS 1670 at $z=5.242$, is 2-3 dex fainter than known quasars at similar redshifts and was previously identified as a candidate low-luminosity AGN based on its rest-frame optical SED. We measure a BH mass of $M_{\rm BH}=1.3\pm0.4\times 10^{7}~M_{\odot}$, confirming that this AGN is powered by the least-massive BH known in the universe at the end of cosmic reionization. The second source, CEERS 3210 at $z=5.624$, is inferred to be a heavily obscured, broad-line AGN caught in a transition phase between a dust-obscured starburst and an unobscured quasar. We estimate its BH mass to be $M_{\rm BH}\simeq 0.9-4.7 \times 10^{7}~M_{\odot}$, depending on the level of dust obscuration assumed. We derive host stellar masses, $M_\star$, allowing us to place constraints on the BH-galaxy mass relationship in the lowest mass range yet probed in the early universe. The $M_{\rm BH}/M_\star$ ratio for CEERS 1670, in particular, is consistent with or higher than the empirical relationship seen in massive galaxies at $z=0$. We examine the emission-line ratios of both sources and find that their location on the BPT and OHNO diagrams is consistent with model predictions for low-metallicity AGN with $Z/Z_\odot \simeq 0.2-0.4$. The spectroscopic identification of low-luminosity, broad-line AGN at $z>5$ with $M_{\rm BH}\simeq 10^{7}~M_{\odot}$ demonstrates the capability of JWST to push BH masses closer to the range predicted for the BH seed population and provides a unique opportunity to study the early stages of BH-galaxy assembly., Comment: 16 pages, 8 figures, submitted to ApJL

We report a candidate of a low-luminosity active galactic nucleus (AGN) at z=5 that was selected from the first near-infrared images of the JWST CEERS project. This source, named CEERS-AGN-z5-1 at absolute 1450 A magnitude M1450=-19.5 +/- 0.3, was found via a visual selection of compact sources from a catalog of Lyman break galaxies at z>4, taking advantage of the superb spatial resolution of the JWST/NIRCam images. The 20 photometric data available from CFHT, HST, Spitzer, and JWST suggest that the continuum shape of this source is reminiscent of that for an unobscured AGN, and there is a clear color excess in the filters where the redshifted Hbeta+[OIII] and Halpha are covered. The estimated line luminosity is L_Hbeta+[OIII] =10^43.0 erg s-1 and L_Halpha =10^42.9 erg s-1 with the corresponding rest-frame equivalent width EW_{Hbeta+[OIII]} =1100 A and EW_Halpha =1600 A, respectively. Our SED fitting analysis favors the scenario that this object is either a strong broad-line emitter or even a super-Eddington accreting black hole (BH), although a possibility of an extremely young galaxy with moderate dust attenuation is not completely ruled out. The bolometric luminosity, L_bol=2.5 +/- 0.3 \times 10^44 erg s-1, is consistent with those of z<0.35 broad-line AGNs with M_BH = 10^6 M_sun accreting at the Eddington limit. This new AGN population at the first 1.1 billion years of the universe may close the gap between the observed BH mass range at high redshift and that of BH seeds. Spectroscopic confirmation is awaited to secure the redshift and its AGN nature., Comment: 13 pages, 4 figures, accepted for publication in ApJL

Monocular visual odometry (VO) is an important task in robotics and computer vision. Thus far, how to build accurate and robust monocular VO systems that can work well in diverse scenarios remains largely unsolved. In this paper, we propose a framework to exploit monocular depth estimation for improving VO. The core of our framework is a monocular depth estimation module with a strong generalization capability for diverse scenes. It consists of two separate working modes to assist the localization and mapping. With a single monocular image input, the depth estimation module predicts a relative depth to help the localization module on improving the accuracy. With a sparse depth map and an RGB image input, the depth estimation module can generate accurate scale-consistent depth for dense mapping. Compared with current learning-based VO methods, our method demonstrates a stronger generalization ability to diverse scenes. More significantly, our framework is able to boost the performances of existing geometry-based VO methods by a large margin.