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We present a proof-of-concept simulation-based inference on $\Omega_{\rm m}$ and $\sigma_{8}$ from the SDSS BOSS LOWZ NGC catalog using neural networks and domain generalization techniques without the need of summary statistics. Using rapid lightcone simulations, ${\rm L{\scriptsize -PICOLA}}$, mock galaxy catalogs are produced that fully incorporate the observational effects. The collection of galaxies is fed as input to a point cloud-based network, ${\texttt{Minkowski-PointNet}}$. We also add relatively more accurate ${\rm G{\scriptsize ADGET}}$ mocks to obtain robust and generalizable neural networks. By explicitly learning the representations which reduces the discrepancies between the two different datasets via the semantic alignment loss term, we show that the latent space configuration aligns into a single plane in which the two cosmological parameters form clear axes. Consequently, during inference, the SDSS BOSS LOWZ NGC catalog maps onto the plane, demonstrating effective generalization and improving prediction accuracy compared to non-generalized models. Results from the ensemble of 25 independently trained machines find $\Omega_{\rm m}=0.339 \pm 0.056$ and $\sigma_{8}=0.801 \pm 0.061$, inferred only from the distribution of galaxies in the lightcone slices without relying on any indirect summary statistics. A single machine that best adapts to the ${\rm G{\scriptsize ADGET}}$ mocks yields a tighter prediction of $\Omega_{\rm m}=0.282 \pm 0.014$ and $\sigma_{8}=0.786 \pm 0.036$. We emphasize that adaptation across multiple domains can enhance the robustness of the neural networks in observational data., Comment: 28 pages, 14 figures; Accepted for publication in ApJ

The problem of career trajectory prediction (CTP) aims to predict one's future employer or job position. While several CTP methods have been developed for this problem, we posit that none of these methods (1) jointly considers the mutual ternary dependency between three key units (i.e., user, position, and company) of a career and (2) captures the characteristic shifts of key units in career over time, leading to an inaccurate understanding of the job movement patterns in the labor market. To address the above challenges, we propose a novel solution, named as CAPER, that solves the challenges via sophisticated temporal knowledge graph (TKG) modeling. It enables the utilization of a graph-structured knowledge base with rich expressiveness, effectively preserving the changes in job movement patterns. Furthermore, we devise an extrapolated career reasoning task on TKG for a realistic evaluation. The experiments on a real-world career trajectory dataset demonstrate that CAPER consistently and significantly outperforms four baselines, two recent TKG reasoning methods, and five state-of-the-art CTP methods in predicting one's future companies and positions-i.e., on average, yielding 6.80% and 34.58% more accurate predictions, respectively.

Quiescent galaxies are predominantly observed in local galaxy clusters. However, the fraction of quiescent galaxies in high-redshift clusters significantly varies among different clusters. In this study, we present the results of an analysis of the star formation (SF) properties of $z \sim 0.87$ clusters and groups from a cosmological hydrodynamical simulation Horizon Run 5. We investigate the correlation between the quiescent galaxy fraction (QF) of these model clusters/groups and their various internal or external properties. We find that halo mass is one of the most important characteristics as higher mass clusters and groups have higher QFs. We also find that other properties such as stellar-mass ratio and Friends-of-Friends fraction, which measures the proportion of the area around a cluster occupied by dense structures, may mildly affect the QFs of clusters and groups. This may indicate that the evolutionary history as well as the large-scale environment of clusters and groups also play a certain role in determining the SF status of high-redshift galaxy clusters and groups., Comment: 8 pages, 9 figures

We test whether Lyman alpha emitters (LAEs) and Lyman-break galaxies (LBGs) can be good tracers of high-z large-scale structures, using the Horizon Run 5 cosmological hydrodynamical simulation. We identify LAEs using the Ly{\alpha} emission line luminosity and its equivalent width, and LBGs using the broad-band magnitudes at z~2.4, 3.1, and 4.5. We first compare the spatial distributions of LAEs, LBGs, all galaxies, and dark matter around the filamentary structures defined by dark matter. The comparison shows that both LAEs and LBGs are more concentrated toward the dark matter filaments than dark matter. We also find an empirical fitting formula for the vertical density profile of filaments as a binomial power-law relation of the distance to the filaments. We then compare the spatial distributions of the samples around the filaments defined by themselves. LAEs and LBGs are again more concentrated toward their filaments than dark matter. We also find the overall consistency between filamentary structures defined by LAEs, LBGs, and dark matter, with the median spatial offsets that are smaller than the mean separation of the sample. These results support the idea that the LAEs and LBGs could be good tracers of large-scale structures of dark matter at high redshifts., Comment: 20 pages, 15 figures, 2 tables, accepted for publication in ApJ

To understand the formation and evolution of massive cosmic structures, studying them at high redshift, in the epoch when they formed the majority of their mass is essential. The One-hundred-deg$^2$ DECam Imaging in Narrowbands (ODIN) survey is undertaking the widest-area narrowband program to date, to use Ly$\alpha$-emitting galaxies (LAEs) to trace the large-scale structure (LSS) of the Universe at three cosmic epochs. In this work, we present results at $z$ = 3.1 based on early ODIN data in the COSMOS field. We identify and characterize protoclusters and cosmic filaments using multiple methods and discuss their strengths and weaknesses. We then compare our observations against the IllustrisTNG suite of cosmological hydrodynamical simulations. The two are in excellent agreement, with a similar number and angular size of structures identified above a specified density threshold. We are able to recover the simulated protoclusters with $\log$(M$_{z=0}$/$M_\odot$) $\gtrsim$ 14.4 in $\sim$ 60\% of the cases. With these objects we show that the descendant masses of the protoclusters in our sample can be estimated purely based on our 2D measurements, finding a median $z$ = 0 mass of $\sim10^{14.5}$M$_\odot$. The lack of information on the radial extent of each protocluster introduces a $\sim$0.4~dex uncertainty in its descendant mass. Finally, we show that the recovery of the cosmic web in the vicinity of protoclusters is both efficient and accurate. The similarity of our observations and the simulations imply that our structure selection is likewise robust and efficient, demonstrating that LAEs are reliable tracers of the LSS., Comment: 26 pages, 18 figures; submitted to ApJ

Surface-adsorbed rare-earth nanostructures are ideal platforms to investigate the interplay between intra-atomic interactions and multi-orbital spin configurations. However, addressing these properties has posed severe experimental and theoretical challenges. Here, we use the orbital selectivity offered by X-ray absorption spectroscopy to quantify the Coulomb integrals of Nd atoms on conductive surfaces, as well as the variation of individual orbital occupation upon cluster nucleation. Using X-ray magnetic circular dichroism we identify magnetic moments of the order of \MK{few tens of}~$\mu_{\rm{B}}$ at the $5d$ orbitals and their magnetic coupling with the $4f$ spins. Our results validate orbital-resolved X-ray spectroscopy as a reliable method for quantifying complex multi-orbital interactions in surface-adsorbed lanthanides.

Metallicity offers a unique window into the baryonic history of the cosmos, being instrumental in probing evolutionary processes in galaxies between different cosmic environments. We aim to quantify the contribution of these environments to the scatter in the mass-metallicity relation (MZR) of galaxies. By analysing the galaxy distribution within the cosmic skeleton of the Horizon Run 5 cosmological hydrodynamical simulation at redshift $z = 0.625$, computed using a careful calibration of the T-ReX filament finder, we identify galaxies within three main environments: nodes, filaments and voids. We also classify galaxies based on the dynamical state of the clusters and the length of the filaments in which they reside. We find that the cosmic environment significantly contributes to the scatter in the MZR; in particular, both the gas metallicity and its average relative standard deviation increase when considering denser large-scale environments. The difference in the average metallicity between galaxies within relaxed and unrelaxed clusters is $\approx 0.1 \text{ dex}$, with both populations displaying positive residuals, $\delta Z_{g}$, from the averaged MZR. Moreover, the difference in metallicity between node and void galaxies accounts for $\approx 0.14 \, \text{dex}$ in the scatter of the MZR at stellar mass $M_{\star} \approx 10^{9.35}\,\text{M}_{\odot}$. Finally, both the average [O/Fe] in the gas and the galaxy gas fraction decrease when moving to higher large-scale densities in the simulation, suggesting that the cores of cosmic environments host, on average, older and more massive galaxies, whose enrichment is affected by a larger number of Type Ia Supernova events., Comment: 17 pages, 17 figures

Matrix completion is an important area of research in recommender systems. Recent methods view a rating matrix as a user-item bi-partite graph with labeled edges denoting observed ratings and predict the edges between the user and item nodes by using the graph neural network (GNN). Despite their effectiveness, they treat each rating type as an independent relation type and thus cannot sufficiently consider the ordinal nature of the ratings. In this paper, we explore a new approach to exploit rating ordinality for GNN, which has not been studied well in the literature. We introduce a new method, called ROGMC, to leverage Rating Ordinality in GNN-based Matrix Completion. It uses cumulative preference propagation to directly incorporate rating ordinality in GNN's message passing, allowing for users' stronger preferences to be more emphasized based on inherent orders of rating types. This process is complemented by interest regularization which facilitates preference learning using the underlying interest information. Our extensive experiments show that ROGMC consistently outperforms the existing strategies of using rating types for GNN. We expect that our attempt to explore the feasibility of utilizing rating ordinality for GNN may stimulate further research in this direction., Comment: 4 pages, 2 figures, 3 tables

One intriguing approach for studying the dynamical evolution of galaxy clusters is to compare the spatial distributions among various components, such as dark matter, member galaxies, gas, and intracluster light (ICL). Utilizing the recently introduced Weighted Overlap Coefficient (WOC) \citep{2022ApJS..261...28Y}, we analyze the spatial distributions of components within 174 galaxy clusters ($M_{\rm tot}> 5 \times 10^{13} M_{\odot}$, $z=0.625$) at varying dynamical states in the cosmological hydrodynamical simulation Horizon Run 5. We observe that the distributions of gas and the combination of ICL with the brightest cluster galaxy (BCG) closely resembles the dark matter distribution, particularly in more relaxed clusters, characterized by the half-mass epoch. The similarity in spatial distribution between dark matter and BCG+ICL mimics the changes in the dynamical state of clusters during a major merger. Notably, at redshifts $>$ 1, BCG+ICL traced dark matter more accurately than the gas. Additionally, we examined the one-dimensional radial profiles of each component, which show that the BCG+ICL is a sensitive component revealing the dynamical state of clusters. We propose a new method that can approximately recover the dark matter profile by scaling the BCG+ICL radial profile. Furthermore, we find a recipe for tracing dark matter in unrelaxed clusters by including the most massive satellite galaxies together with BCG+ICL distribution. Combining the BCG+ICL and the gas distribution enhances the dark matter tracing ability. Our results imply that the BCG+ICL distribution is an effective tracer for the dark matter distribution, and the similarity of spatial distribution may be a useful probe of the dynamical state of a cluster., Comment: 23 pages, 12 figures, accepted for publication in ApJ

We introduce a novel halo/galaxy matching technique between two cosmological simulations with different resolutions, which utilizes the positions and masses of halos along their subhalo merger tree. With this tool, we conduct a study of resolution biases through the {\it galaxy-by-galaxy} inspection of a pair of simulations that have the same simulation configuration but different mass resolutions, utilizing a suite of {\sc IllustrisTNG} simulations to assess the impact on galaxy properties. We find that, with the subgrid physics model calibrated for TNG100-1, subhalos in TNG100-1 (high resolution) have $\lesssim0.5$ dex higher stellar masses than their counterparts in the TNG100-2 (low-resolution). It is also discovered that the subhalos with $M_{\mathrm{gas}}\sim10^{8.5}\,{\rm M}_\odot$ in TNG100-1 have $\sim0.5$ dex higher gas mass than those in TNG100-2. The mass profiles of the subhalos reveal that the dark matter masses of subhalos in TNG100-2 converge well with those from TNG100-1, except within 4 kpc of the resolution limit. The differences in stellar mass and hot gas mass are most pronounced in the central region. We exploit machine learning to build a correction mapping for the physical quantities of subhalos from low- to high-resolution simulations (TNG300-1 and TNG100-1), which enables us to find an efficient way to compile a high-resolution galaxy catalog even from a low-resolution simulation. Our tools can easily be applied to other large cosmological simulations, testing and mitigating the resolution biases of their numerical codes and subgrid physics models., Comment: 24 pages, 14 figures; Accepted for publication in to ApJ

WebAssembly (Wasm) is a low-level bytecode language and virtual machine, intended as a compilation target for a wide range of programming languages, which is seeing increasing adoption across diverse ecosystems. As a young technology, Wasm continues to evolve -- it reached version 2.0 last year and another major update is expected soon. For a new feature to be standardised in Wasm, four key artefacts must be presented: a formal (mathematical) specification of the feature, an accompanying prose pseudocode description, an implementation in the official reference interpreter, and a suite of unit tests. This rigorous process helps to avoid errors in the design and implementation of new Wasm features, and Wasm's distinctive formal specification in particular has facilitated machine-checked proofs of various correctness properties for the language. However, manually crafting all of these artefacts requires expert knowledge combined with repetitive and tedious labor, which is a burden on the language's standardization process and authoring of the specification. This paper presents Wasm SpecTec, a technology to express the formal specification of Wasm through a domain-specific language. This DSL allows all of Wasm's currently handwritten specification artefacts to be error-checked and generated automatically from a single source of truth, and is designed to be easy to write, read, compare, and review. We believe that Wasm SpecTec's automation and meta-level error checking will significantly ease the current burden of the language's specification authors. We demonstrate the current capabilities of Wasm SpecTec by showcasing its proficiency in generating various artefacts, and describe our work towards replacing the manually written official Wasm specification document with specifications generated by Wasm SpecTec., Comment: 5 pages, 7 figures

The magnetic dilution of Vanadyl phthalocyanine (VOPc) within the isostructural diamagnetic Titanyl phthalocyanine (TiOPc) affords promising molecular spin qubit platforms for solid-state quantum computing. The development of quantitative methods for determining how the interactions with a supporting substrate impact the electronic structure of the system are fundamental to determine their potential integration in physical devices. In this work we propose a combined approach based on X-ray absorption spectroscopy (XAS), atomic multiplet calculations, and density functional theory (DFT) to investigate the 3d orbital level structure of VOPc on TiOPc/Ag(100). We characterize VOPc in different molecular environments realized by changing the thickness of TiOPc interlayer and adsorption configuration on Ag(100). Depending on the molecular film structure, we find characteristic XAS features that we analyze using atomic multiplet calculations. We use a Bayesian optimization algorithm to accelerate the parameter search process in the multiplet calculations and identify the ground state properties, such as the 3d orbital occupancy and splitting, as well as intra-atomic interactions. Our analysis indicates that VOPc retains its spin S = 1/2 character in all configurations. Conversely, the energy separation and sequence of the unoccupied V 3d orbitals sensitively depend on the interaction with the surface and TiOPc interlayer. We validate the atomic orbital picture obtained from the multiplet model by comparison with DFT, which further allows us to understand the VOPc electronic properties using a molecular orbital description., Comment: https://journals.aps.org/prb/accepted/fa07aO95X4f10b4334a769f8107f50ef629b9b212

Designer heterostructures, where the desired physics emerges from the controlled interactions between different components, represent one of the most powerful strategies to realize unconventional electronic states. This approach has been particularly fruitful in combining magnetism and superconductivity to create exotic superconducting states. In this work, we use a heterostructure platform combining supramolecular metal complexes (SMCs) with a quasi-2D van der Waals (vdW) superconductor NbSe$_2$. Our scanning tunneling microscopy (STM) measurements demonstrate the emergence of Yu-Shiba-Rusinov (YSR) bands arising from the interaction between the SMC magnetism and the NbSe$_2$ superconductivity. Using X-ray absorption spectroscopy (XAS) and X-ray magnetic circular dichroism (XMCD) measurements, we show the presence of antiferromagnetic coupling between the SMC units. These result in the emergence of an unconventional $3\times3$ reconstruction in the magnetic ground state that is directly reflected in real space modulation of the YSR bands. The combination of flexible molecular building blocks, frustrated magnetic textures, and superconductivity in heterostructures establishes a fertile starting point to fabricating tunable quantum materials, including unconventional superconductors and quantum spin liquids.

We use the Horizon Run 5 cosmological simulation to study the effect of galaxy intrinsic properties and the local environment on AGNs characterized by their threshold of the accretion rate. We select galaxies in the stellar mass range $10^{9.5} \le M^{}{*}/M^{}{\odot} \le 10^{10.5}$ in the snapshot at redshift $z$=0.625. Among various intrinsic properties, we find that the star formation rate of the host galaxy is most correlated to the AGN activity. To quantify the environment, we use background galaxy number density (large-scale environment) and distance and morphological type of the nearest neighbors (small-scale environment), and study their relative effects on the AGN properties. We find that, compared to the background density, the nearest neighbor environment is the dominant quantity determining the bolometric luminosity, star formation rate, and kinematic properties of AGNs and better dictates the gas mass of the host galaxy. We show that the cold gas content in the host galaxies is crucial in triggering AGN activity. However, when the nearest neighbor environment effects start to act at the neighbor distance of less than about half the virial radius of the neighbor, the neighbor environmental effects are the most dominant factor for quasar activity., Comment: 25 pages, 18 figures, 1 table, published in the the Astrophysical Journal (ApJ)

We propose a new method for finding galaxy protoclusters that is motivated by structure formation theory and also directly applicable to observations. We adopt the conventional definition that a protocluster is a galaxy group whose virial mass $M_{\rm vir} < M_{\rm cl}$ at its epoch, where $M_{\rm cl}=10^{14}\,M_{\odot}$, but would exceed that limit when it evolves to $z=0$. We use the critical overdensity for complete collapse at $z = 0$ predicted by the spherical top-hat collapse model to find the radius and total mass of the regions that would collapse at $z=0$. If the mass of a region centered at a massive galaxy exceeds $M_{\rm cl}$, the galaxy is at the center of a protocluster. We define the outer boundary of protocluster as the zero-velocity surface at the turnaround radius so that the member galaxies are those sharing the same protocluster environment and showing some conformity in physical properties. We use the cosmological hydrodynamical simulation Horizon Run 5 (HR5) to calibrate this prescription and demonstrate its performance. We find that the protocluster identification method suggested in this study is quite successful. Its application to the high redshift HR5 galaxies shows a tight correlation between the mass within the protocluster regions identified according to the spherical collapse model and the final mass to be found within the clusters at $z=0$, meaning that the regions can be regarded as the bona-fide protoclusters with high reliability. We also confirm that the redshift-space distortion does not significantly affect the performance of the protocluster identification scheme., Comment: 23 pages, 21 figures. submitted to ApJ. Any comments are welcome

Self-supervised learning is crucial for clinical imaging applications, given the lack of explicit labels in healthcare. However, conventional approaches that rely on precise vision-language alignment are not always feasible in complex clinical imaging modalities, such as cardiac magnetic resonance (CMR). CMR provides a comprehensive visualization of cardiac anatomy, physiology, and microstructure, making it challenging to interpret. Additionally, CMR reports require synthesizing information from sequences of images and different views, resulting in potentially weak alignment between the study and diagnosis report pair. To overcome these challenges, we propose \textbf{CMRformer}, a multimodal learning framework to jointly learn sequences of CMR images and associated cardiologist's reports. Moreover, one of the major obstacles to improving CMR study is the lack of large, publicly available datasets. To bridge this gap, we collected a large \textbf{CMR dataset}, which consists of 13,787 studies from clinical cases. By utilizing our proposed CMRformer and our collected dataset, we achieved remarkable performance in real-world clinical tasks, such as CMR image retrieval and diagnosis report retrieval. Furthermore, the learned representations are evaluated to be practically helpful for downstream applications, such as disease classification. Our work could potentially expedite progress in the CMR study and lead to more accurate and effective diagnosis and treatment., Comment: 24 pages

We investigate the impact of the surface brightness (SB) limit on the galaxy stellar mass functions (GSMFs) using mock surveys generated from the Horizon Run 5 (HR5) simulation. We compare the stellar-to-halo-mass relation, GSMF, and size-stellar mass relation of the HR5 galaxies with empirical data and other cosmological simulations. The mean SB of simulated galaxies are computed using their effective radii, luminosities, and colors. To examine the cosmic SB dimming effect, we compute $k$-corrections from the spectral energy distributions of individual simulated galaxy at each redshift, apply the $k$-corrections to the galaxies, and conduct mock surveys based on the various SB limits. We find that the GSMFs are significantly affected by the SB limits at a low-mass end. This approach can ease the discrepancy between the GSMFs obtained from simulations and observations at $0.625\le z\le 2$. We also find that a redshift survey with a SB selection limit of $\left<\mu_r\right>^e =$ 28 mag arcsec${}^{-2}$ will miss 20% of galaxies with $M_\star^g=10^{9}~{\rm M_\odot}$ at $z=0.625$. The missing fraction of low-surface-brightness galaxies increases to 50%, 70%, and 98% at $z=0.9$, 1.1, and 1.9, respectively, at the SB limit., Comment: 27 pages, 30 figures, accepted for publication in ApJ

The self-organization is one of the most interesting phenomena in the non-equilibrium complex system, generating ordered structures of different sizes and durations. In tokamak plasmas, various self-organized phenomena have been reported, and two of them, coexisting in the near-marginal (interaction dominant) regime, are avalanches and the $E \times B$ staircase. Avalanches mean the ballistic flux propagation event through successive interactions as it propagates, and the $E \times B$ staircase means a globally ordered pattern of self-organized zonal flow layers. Various models have been suggested to understand their characteristics and relation, but experimental researches have been mostly limited to the demonstration of their existence. Here we report detailed analyses of their dynamics and statistics and explain their relation. Avalanches influence the formation and the width distribution of the $E \times B$ staircase, while the $E \times B$ staircase confines avalanches within its mesoscopic width until dissipated or penetrated. Our perspective to consider them the self-organization phenomena enhances our fundamental understanding of them as well as links our findings with the self-organization of mesoscopic structures in various complex systems.

We investigate the formation and morphological evolution of the first galaxies in the cosmic morning ($10 \gtrsim z \gtrsim 4$) using the Horizon Run 5 (HR5) simulation. For galaxies above the stellar mass $M_{\star, {\rm min}} = 2\times 10^9\,M_{\odot}$, we classify them into disk, spheroid, and irregular types according to their asymmetry and stellar mass morphology. We find that about 2/3 of the galaxies have a S\'{e}rsic index $< 1.5$, reflecting the dominance of disk-type morphology in the cosmic morning. The rest are evenly distributed as incidental and transient irregulars or spheroids. These fractions are roughly independent of redshift and stellar mass up to $\sim10^{10}\,M_{\odot}$. Almost all the first galaxies with $M_{\star}> M_{\star, {\rm min}}$ at $z>4$ form at initial peaks of the matter density field. Large-scale structures in the universe emerge and grow like cosmic rhizomes as the underlying matter density fluctuations grow and form associations of galaxies in rare overdense regions and the realm of the galactic world is stretched into relatively lower-density regions along evolving filaments. The cosmic web of galaxies forms at lower redshifts when most rhizomes globally percolate. The primordial angular momentum produced by the induced tidal torques on protogalactic regions is correlated with the internal kinematics of galaxies and tightly aligned with the angular momentum of the total galaxy mass. The large-scale tidal field imprinted in the initial conditions seems responsible for the dominance of disk morphology, and for the tendency of galaxies to re-acquire a disk post-distortion., Comment: 26 pages, 21 figures, accepted for publication in ApJ

We investigate the formation of jellyfish galaxies using radiation-hydrodynamic simulations of gas-rich dwarf galaxies with a multi-phase interstellar medium (ISM). We find that the ram-pressure-stripped (RPS) ISM is the dominant source of molecular clumps in the near wake within 10 kpc from the galactic plane, while in-situ formation is the major channel for dense gas in the distant tail of the gas-rich galaxy. Only 20% of the molecular clumps in the near wake originate from the intracluster medium (ICM); however, the fraction reaches 50% in the clumps located at $80\,{\rm kpc}$ from the galactic center since the cooling time of the RPS gas tends to be short due to the ISM--ICM mixing ($\lesssim$ 10 Myr). The tail region exhibits a star formation rate of $0.001-0.01\,{\rm M_{\odot}\,yr^{-1}}$, and most of the tail stars are born in the stripped wake within 10 kpc from the galactic plane. These stars induce bright H$\alpha$ blobs in the tail, while H$\alpha$ tails fainter than $6\times10^{38}\,{\rm erg\,s^{-1}\,kpc^{-2}}$ are mostly formed via collisional radiation and heating due to mixing. We also find that the stripped tails have intermediate X-ray to H$\alpha$ surface brightness ratios (1.5$\lesssim F_{\rm X}/F_{\rm H\alpha}\lesssim$20), compared to the ISM ($\lesssim$1.5) or pure ICM ($\gg$20). Our results suggest that jellyfish features emerge when the ISM from gas-rich galaxies is stripped by strong ram pressure, mixes with the ICM, and enhances the cooling in the tail., Comment: 19 pages, 15 figures; Accepted for publication in ApJ

We present that a statistical method known as the Complexity-Entropy analysis is useful to characterize a state of plasma turbulence and flux in the resonant magnetic perturbation (RMP) edge localized mode (ELM) control experiment. The RMP ELM suppression phase with the stochastic pedestal top temperature fluctuation can be distinguished from the natural ELM free phase with the chaotic fluctuation. It is discussed that the stochastic temperature fluctuation localized near the pedestal top can be originated from the narrow layer of the field penetration near the pedestal top. The forced magnetic island can emit the resonant drift wave of comparable sizes (relatively low-k) in the RMP ELM suppression phase, and it can results in the generation of stochastic higher wavenumber fluctuations coupled to tangled fields around the island. The analysis of the ion saturation current measurement around the main outer striking point on the divertor shows that it also becomes more stochastic as the stronger plasma response to the RMP field is expected.

The absence of high Eddington ratio, obscured Active Galactic Nuclei (AGN) in local ($z\lesssim0.1$) samples of moderate luminosity AGN has generally been explained to result from radiation pressure on the dusty gas governing the level of nuclear ($\lesssim10$pc) obscuration. However, very high accretion rates are routinely reported among obscured quasars at higher luminosities, and may require a different feedback mechanism. We compile constraints on obscuration and Eddington ratio for samples of X-ray, optical, infrared, and submm selected AGN at quasar luminosities. Whereas moderate luminosity, obscured AGN in the local universe have a range of lower Eddington ratios ($f_{\rm Edd} \sim 0.001-0.1$), the most luminous ($L_{\rm bol} \gtrsim 10^{46} $erg s$^{-1}$) IR/submm-bright, obscured quasars out to $z\sim3$ commonly have very high Eddington ratios ($f_{\rm Edd} \sim 0.1-1$). This apparent lack of radiation pressure feedback in luminous obscured quasars is likely coupled with AGN timescales, such that a higher fraction of luminous obscured quasars are seen due to the short timescale for which quasars are most luminous. Adopting quasar evolutionary scenarios, extended ($\sim10^{2-3}$pc) obscuration may work together with the shorter timescales to explain the observed fraction of obscured, luminous quasars, while outflows driven by radiation pressure will slowly clear this material over the AGN lifetime., Comment: 15 pages, 6 figures, accepted to ApJ, typos corrected

We investigate the impact of ram pressure stripping due to the intracluster medium (ICM) on star-forming disk galaxies with a multi-phase interstellar medium (ISM) maintained by strong stellar feedback. We carry out radiation-hydrodynamics simulations of an isolated disk galaxy embedded in a 10^11 Msun dark matter halo with various ICM winds mimicking the cluster outskirts (moderate) and the central environment (strong). We find that both star formation quenching and triggering occur in ram pressure-stripped galaxies, depending on the strength of the winds. HI and H$_2$ in the outer galactic disk are significantly stripped in the presence of the moderate winds, whereas turbulent pressure provides support against ram pressure in the central region where star formation is active. Moderate ICM winds facilitate gas collapsing, increasing the total star formation rates by ~40% when the wind is oriented face-on or ~80% when it is edge-on. In contrast, strong winds rapidly blow away neutral and molecular hydrogen gas from the galaxy, suppressing the star formation by a factor of two within ~200 Myr. Dense gas clumps with N_H > 10 Msun pc^-2 are easily identified in extraplanar regions, but no significant young stellar populations are found in such clumps. In our attempts to enhance radiative cooling by adopting a colder ICM of T=10^6K, only a few additional stars are formed in the tail region, even if the amount of newly cooled gas increases by an order of magnitude., Comment: 26 pages, 17 figures, accepted for publication in ApJ

Mass segregation, a tendency of more massive galaxies being distributed closer to the cluster center, is naturally expected from dynamical friction, but its presence is still controversial. Using deep optical observations of 14 Abell clusters (KYDISC) and a set of hydrodynamic simulations (YZiCS), we find in some cases a hint of mass segregation inside the virial radius. Segregation is visible more clearly when the massive galaxy fraction is used instead of mean stellar mass. The trend is more significant in the simulations than in the observations. To find out the mechanisms working on mass segregation, we look into the evolution of individual clusters simulated. We find that the degree of mass segregation is different for different clusters: the trend is visible only for low-mass clusters. We compare the masses of galaxies and their dark haloes at the time of infall and at the present epoch to quantify the amount of tidal stripping. We then conclude that satellites that get accreted at earlier epochs or galaxies in more massive clusters go through more tidal stripping. These effects in combination result in a correlation between the host halo mass and the degree of stellar mass segregation., Comment: 10 pages, 8 figures, 2 tables. Accepted for publication in ApJ

We present the stellar populations of 138 compact elliptical galaxies (cEs) in the redshift range of $z < 0.05$ using the Sloan Digital Sky Survey (SDSS) DR12. Our cEs are divided into those with [cE(w)] and without [cE(w/o)] a bright ($M_{r} < -21$ mag) host galaxy. We investigated the stellar population properties of cEs based on the Lick line indices extracted from SDSS spectra. cE(w)s show [Z/H] and \afe\ distributions skewed toward higher values compared to those of the cE(w/o)s. No statistically significant difference in age distribution was found between the cE(w)s and cE(w/o)s. In the mass-metallicity distribution, cE(w)s deviate from the relation observed for early-type galaxies at a given stellar mass, whereas cE(w/o)s conform to the relation. Based on the different features in the stellar populations of cE(w)s and cE(w/o)s, we can propose two different cE formation channels tracing different original masses of the progenitors. cE(w)s would be the remnant cores of the massive progenitor galaxies whose outer parts are tidally stripped by a massive neighboring galaxy (i.e., nurture origin). In contrast, cE(w/o)s are likely the faint end of early-type galaxies maintaining in-situ evolution in an isolated environment with no massive galaxy nearby (i.e., nature origin). Our results reinforce the propositions that cEs comprise a mixture of galaxies with two types of origins depending on their local environment., Comment: 11 pages, 8 figures, Accepted for publication in ApJ

Horizon Run 5 (HR5) is a cosmological hydrodynamical simulation which captures the properties of the Universe on a Gpc scale while achieving a resolution of 1kpc. Inside the simulation box we zoom-in on a high-resolution cuboid region with a volume of $1049\times119\times127\,{\rm cMpc}^3$.The sub-grid physics chosen to model galaxy formation includes radiative heating/cooling, UV background, star formation, supernova feedback, chemical evolution tracking the enrichment of oxygen and iron, the growth of supermassive black holes and feedback from active galactic nuclei (AGN) in the form of a dual jet-heating mode. For this simulation we implemented a hybrid MPI-OMP version of RAMSES, specifically targeted for modern many-core many thread parallel architectures. In addition to the traditional simulation snapshots, light-cone data was generated on the fly. For the post-processing, we extended the Friends-of-Friend (FoF) algorithm and developed a new galaxy finder PGalF to analyse the outputs of HR5. The simulation successfully reproduces observations, such as the cosmic star formation history and connectivity of galaxy distribution, We identify cosmological structures at a wide range of scales, from filaments with a length of several cMpc, to voids with a radius of ~100 cMpc. The simulation also indicates that hydrodynamical effects on small scales impact galaxy clustering up to very large scales near and beyond the baryonic acoustic oscillation (BAO) scale. Hence, caution should be taken when using that scale as a cosmic standard ruler: one needs to carefully understand the corresponding biases. The simulation is expected to be an invaluable asset for the interpretation of upcoming deep surveys of the Universe., Comment: The dimension of the zoom-in region has been corrected