We report fourteen and twenty-eight protocluster candidates at z = 5.7 and 6.6 over 14 and 19 deg2 areas, respectively, selected from 2,230 Lyα emitters (LAEs) photometrically identified with Subaru/Hyper Suprime-Cam (HSC) deep images. Six out of the 42 protocluster candidates include at least 1 spectroscopically confirmed LAEs at redshifts up to z = 6.574. By the comparisons with the cosmological Lyα radiative transfer (RT) model reproducing LAEs with the reionization effects, we find that more than a half of these protocluster candidates might be progenitors of the present-day clusters with a mass of ≳ 1014M⊙. We also investigate the correlation between LAE overdensity and Lya rest-frame equivalent width (EW), because the cosmological Lyα RT model suggests that a slope of EW-overdensity relation is steepened towards the epoch of cosmic reionization (EoR), due to the existence of the ionized bubbles around galaxy overdensities easing the escape of Lyα emission from the partly neutral intergalactic medium. The available HSC data suggest that the slope of the EW-overdensity correlation does not evolve from the post-reionization epoch z = 5.7 to the EoR z = 6.6 beyond the moderately large statistical errors.

The massive galaxies and their central supermassive black holes (SMBHs) co-evolution scenario proposes that a gas-rich major merger can trigger the central starburst and feeding the SMBH accretion, and then star formation is eventually quenched by quasar feedback. In this evolutionary sequence, dust-obscured quasars may represent the critical transition phase between starburst and unobscured quasars. Modeling the panchromatic emission of these hidden monsters provides a unique way to explore their physical properties and therefore the co-evolution between SMBHs and their hosts. However, most of modelling methods are not suitable for the extremely luminous systems with obscured Active Galactic Nucleus (AGN) emission. Here we present two case studies of panchromatic modeling of the extremely luminous dust-obscured quasars at the cosmic noon.

LSST and Euclid must address the daunting challenge of analyzing the unprecedented volumes of imaging and spectroscopic data that these next-generation instruments will generate. A promising approach to overcoming this challenge involves rapid, automatic image processing using appropriately trained Deep Learning (DL) algorithms. However, reliable application of DL requires large, accurately labeled samples of training data. Galaxy Zoo Express (GZX) is a recent experiment that simulated using Bayesian inference to dynamically aggregate binary responses provided by citizen scientists via the Zooniverse crowd-sourcing platform in real time. The GZX approach enables collaboration between human and machine classifiers and provides rapidly generated, reliably labeled datasets, thereby enabling online training of accurate machine classifiers. We present selected results from GZX and show how the Bayesian aggregation engine it uses can be extended to efficiently provide object-localization and bounding-box annotations of two-dimensional data with quantified reliability. DL algorithms that are trained using these annotations will facilitate numerous panchromatic data modeling tasks including morphological classification and substructure detection in direct imaging, as well as decontamination and emission line identification for slitless spectroscopy. Effectively combining the speed of modern computational analyses with the human capacity to extrapolate from few examples will be critical if the potential of forthcoming large-scale surveys is to be realized.

Understanding the formation of the first galaxies (FGs) is one of the most important topics in modern cosmology. In this proceeding, we briefly summarize the results of chemical enrichment from the Pop III supernovae during the assembly of the FGs. This early chemical enrichment plays an important role in triggering the Pop II star formation. Generally speaking, there are two major enrichment channels, inside-out (internal) and outside-in (external). Our results suggest that the external channel of chemical enrichment only works if the Pop III stars are very massive stars of 200–260 M⊙, which produce strong enough radiative feedback and supernova to derive the external metal mixing down to the center of the nearby halo.

We investigate the stellar population of star-forming galaxies at z ∼ 4 by focusing on their slope of rest-frame ultraviolet continuum called UV spectral slope β. We analyze the sample of bright Lyman Break Galaxies (LBGs) with Subaru/i′≤26.0in the Subaru/XMM-Newton Deep Survey field. Our detailed SED fitting analysis indicates that the LBGs with observed UV slope > −1.7, , Av > 1.0, and intrinsic UV slope < −2.5 are the intrinsically active star-forming galaxies with star formation rates larger than a few × 102 M⊙yr−1. A significant fraction of the UV-selected LBGs at z ∼ 4 is on-going active and dust obscured star-forming galaxies.

The Coma supercluster is one of the largest, nearby (∼100h−1Mpc) gravitationally bound structures known in the universe. It comprises two large clusters of galaxies and several galaxy groups intersected by a complex network of filaments, providing the perfect laboratory for studying the evolution of galaxies in a range of ‘continuous’ environments. We characterised the different components of the environment to study the properties of galaxies in the optical and ultraviolet (UV) wavebands. Our analysis shows that galaxies experience accelerated evolution as they approach the spine of the filament, suggesting that the intermediate-density environment prevalent in the filaments can accelerate the evolution of galaxies.

Magnetic field plays an important role in star formation and galaxy evolution. Previous studies discussed about the origin of magnetic field and its effect to the environment. With the recent advancement of supercomputers, adding the magnetic field to a cosmological hydrodynamic simulations only become feasible. In this proceeding, we present the results of high-resolution magneto-hydrodynamic simulation with GIZMO and compare our simulation result with the previous literature and the observations.

We construct an X-ray spectral model for the clumpy torus in an active galactic nucleus (AGN), utilizing the Monte Carlo simulation for Astrophysics and Cosmology framework (MONACO: Odaka et al.2016). The geometry of the torus is the same as that in Nenkova et al. (2008), which assumes a power law distribution of clumps in the radial direction and a normal distribution in the elevation direction. We apply our model to the broadband X-ray spectrum of the Circinus galaxy observed with XMM-Newton, Suzaku, and NuSTAR. Our model can well reproduce the observed X-ray spectrum, yielding a hydrogen column density along the line-of-sight ${N_{\rm{H}}^{\rm{LOS}}} = 4.86_{ - 0.04}^{ + 0.07} \times {10^{24}}$ cm−2 and a torus angular width ${sigma = 14.7_{ - 0.39}^{ + 0.44}}$ degree.

The derivation of accurate stellar populations of galaxies is a non-trivial task because of the well-known age-metallicity degeneracy. We aim to break this degeneracy by invoking a chemical evolution model (CEM) for isolated disk galaxy, where its metallicity enrichment history (MEH) is modelled to be tightly linked to its star formation history (SFH). Our CEM has been successfully tested on several local group dwarf galaxies whose SFHs and MEHs have been both independently measured from deep colour-magnitude diagrams of individual stars. By introducing the CEM into the stellar population fitting algorithm as a prior, we expect that the SFH of galaxies could be better constrained.

Early-type galaxies (ETGs) are of crucial importance to trace back the galaxy mass assembly across cosmic time, yet their formation and quenching remain remarkably elusive. The discoveries of massive, dead galaxies at ever-growing redshifts provided compelling evidence to push their formation up to redshift > 4–5 when the Universe was barely 1 Gyr old. In this talk I will present our results on the ages of a new sample of ETGs at z ∼ 3, built by exploiting HST WFC3/G141 rest-frame optical/near-UV grism spectroscopy to study the nature of 10 passive galaxy candidates at 2.5 < z < 3.5 in COSMOS.

This work is part of a PhD project aimed at quantifying the parent space density of distant genuine passive galaxies. I will also discuss the importance of multi-wavelength data in clarifying the degree of contamination by dusty star-forming galaxies affecting the color selection.

By considering a modified version of the evolutionary population synthesis (EPS) model for stellar populations (SPs) comprising binary stars, the retrieved galaxy and HII-region parameters/properties differ from the case of neglecting binary stars. The retrieved age, stellar metallicity and mass of galaxies increase (e.g. ∼ 0.2 dex when using spectral fitting algorithm), whilst the star formation rate decreases (∼0.2 dex). The radiation fields from intermediate-age SPs with binary stars could be potentially important ionizing sources in HII regions. Under this possibility, the theoretical division between star forming galaxy and AGN on the diagnostic diagrams would move towards the up-right corner and the retrieved gaseous metallicity would decrease.

Our prediction for the birth rate of binary neutron stars in SPs ranges from 10−9 to 10−6${\M {^\minus 1_\odot}} $ yr−1 when the kick velocity is from 0 to 190 km s−1.

Starburst galaxies are often found to be the result of galaxy mergers. As a result, galaxy mergers are often believed to lie above the galaxy main sequence: the tight correlation between stellar mass and star formation rate. Here, we aim to test this claim.

Deep learning techniques are applied to images from the Sloan Digital Sky Survey to provide visual-like classifications for over 340 000 objects between redshifts of 0.005 and 0.1. The aim of this classification is to split the galaxy population into merger and non-merger systems and we are currently achieving an accuracy of 92.5%. Stellar masses and star formation rates are also estimated using panchromatic data for the entire galaxy population. With these preliminary data, the mergers are placed onto the full galaxy main sequence, where we find that merging systems lie across the entire star formation rate - stellar mass plane.

We highlight the challenges as well as lessons learnt in the derivation of the photometric redshifts for ∼4 million galaxies at 0 < z ≲ 6 contained in the Spitzer Extragalactic Representative Volume Survey (SERVS) and summarise the photometric redshift results recently published in Pforr et al. (2019). The inhomogeneous nature of the ancillary photometry for SERVS presents a similar situation to the one future, large, extragalactic surveys with e.g. LSST and JWST will face. We employ template SED-fitting to determine photometric redshifts. Our comparison of photometric redshifts to ∼75.000 public, spectroscopic redshifts results in an average σNMAD of ∼0.038 and outlier fraction of 3.7% for sources with the best photometric coverage. We find that photometric redshifts are determined most robustly when filter bands are numerous and cover a wide wavelength range. We highlight some possible improvements for the photometric redshifts in SERVS in the future.

The Herschel Extragalactic Legacy Project (HELP) focuses to publish an astronomical multiwavelength catalogue of millions of objects over 1300 deg2 of the Herschel Space Observatory survey fields. Millions of galaxies with ultraviolet–far infrared photometry make HELP a perfect sample for testing spectral energy distribution fitting models, and to prepare tools for next-generation data. In the frame of HELP collaboration we estimated the main physical properties of all galaxies from the HELP database and we checked a new procedure to select peculiar galaxies from large galaxy sample and we investigated the influence of used modules for stellar mass estimation.

The estimation of interstellar dust masses is an important pursuit in our understanding of both local and early Universe – see e.g. the “dust budget crisis”. One of the most used methods of estimating dust masses – dust emission fitting – requires an estimate of the dust opacity at far-infrared and submillimeter wavelengths, but in most models this quantity is based on extrapolation rather than on actual measurements. It is becoming more and more evident that the opacity in typical dust models differs from that of dust analogs measured in the lab, meaning that astronomical dust mass estimations may need to be revised. To estimate the systematic errors introduced by this mismatch, we calculated dust emission for a model where dust far-infrared opacity is the same as that measured in lab samples, then we fit the synthetic emission with a typical (modified blackbody) dust model. Our results show that, if interstellar dust is indeed similar to the lab dust analogs, most fits may overestimate dust masses by as much as an order of magnitude.

We analyse the dust-to-gas mass ratio (DGR) in nearby galaxies on kiloparsec scales. We focus on their dependence on metallicity and the CO-to-H2 conversion factor, αco. We use a sample of 25 nearby galaxies from SINGS and combine our data with CO (2-1) and H I observations from the HERACLES and THINGS surveys. We implement a Hierarchical Bayesian method to derive the dust mass via fitting the infrared data from 100 to 500 μm with a single modified blackbody. We find that the DGR-metallicity relation follows a power law and we study its strong dependency on the conversion factor αco. Our results indicate a strong connection between interstellar dust and gas. The resolved DGR-metallicity relation cannot be represented with a single power law. The scatter in this relation shows the strong impact of several processes that take place in every galaxy.

The infrared (IR) galaxies detected at Herschel/SPIRE 250 μm band over the AKARI’s NEP-Wide field are various types of dusty star-forming (SF) galaxies ranging from quiescent to starbursts, having mid-IR polycyclic aromatic hydrocarbon (PAH) features near 8 μm. The measurements of the 8 μm luminosity (L8μm) along with the total infrared luminosity (LIR) based on the physical modeling of SEDs a take unique advantage of the continuous near- to mid-IR coverage, far-IR data points, and spectroscopically determined accurate redshifts. Our sample shows shortage of 8 μm luminosity compared to the total IR luminosity. This deficit gets severe in more luminous IR galaxies, suggesting PAH molecules in these galaxies are destroyed by a strong radiation field from SF regions, or the existence of a unexpectedly large amount of cold dust in the ISM that contributes to LIR.

We calculate the spectral energy distribution of the first galaxies which contain pre-main-sequence stars by using the stellar evolution code Modules for Experiments in Stellar Astrophysics, the spectra model BT-Settl, and the stellar population synthesis code PEGASE. We calculate the galaxy spectral energy distribution for Salpeter Initial Mass Function. We find that very young first galaxies are bright also in mid-infrared, and the contribution of pre-main-sequence stars can be significant over 0.1 Myr after a star-formation episode.

Optical properties of infrared-bright (IR-bright) dust-obscured galaxies (DOGs) are reported. DOGs are faint in optical but very bright in mid-IR, which are powered by active star formation (SF) or active galactic nucleus (AGN), or both. The DOGs is a candidate population that are evolving from a gas-rich merger to a quasar. By combining three catalogs of optical (Subaru Hyper Suprime-Cam), near-IR (VIKING), and mid-IR (ALLWISE), we have discovered 571 IR-bright DOGs. Using their spectral energy distributions, we classified the selected DOGs into the SF-dominated DOGs and the AGN-dominated DOGs. We found that the SF-dominated DOGs show a redder optical color than the AGN-dominated DOGs. Interestingly, some DOGs shows extremely blue color in optical (blue-excess DOGs: bluDOGs). A possible origin for this blue excess is either the leaked AGN light or stellar UV light from nuclear starbursts. The BluDOGs may be in the transition phase from obscured AGNs to unobscured AGNs.

Interstellar dust is traced by not only thermal emission but also scattered light. The scattered light spectrum observed from ultraviolet (UV) to near-infrared (IR) is useful to constrain some dust properties, such as size distribution, albedo, and composition. Milky Way Galaxy is a unique environment to observe the diffuse scattered light because we can extract it by removing the contribution of starlight. We have observed the UV to near-IR scattered light with space instruments, including Diffuse Infrared Background Experiment (DIRBE), Hubble Space Telescope (HST), and Multi-purpose Infra-Red Imaging System (MIRIS). The scattered light spectrum is marginally consistent with prediction from a recent dust model including carbonaceous and silicate grains with polycyclic aromatic hydrocarbon (PAH). Based on the MIRIS observation of a diffuse cloud, we compare the scattered light color with the dust model with or without grains larger than 1 micrometer. The result shows that the color is consistent with the model without the large grains, which is consistent with recent simulations of dust growth in low-density regions. However, some observations have shown the spectral excess at ∼ 0.6 micrometer wavelength, suggesting the presence of extended red emission (ERE) which cannot be explained by the conventional dust model.