arXiv subjects

Jaehyun Lee

Publications and source records attributed to Jaehyun Lee.

At least 55 records · Page 3Linked to original sources

arXiv2025

Tracing the Formation History of Intrahalo Light with Horizon Run 5

We investigate the formation history of intrahalo light (IHL) using the high-resolution (~1 kpc), large-scale (~Gpc) cosmological hydrodynamical simulation, Horizon Run 5 (HR5). IHL particles are identified by carefully considering both their binding energies and positions with respect to the tidal radii of individual galaxies. By analyzing more than 1,200 galaxy groups and clusters with $\geq 10^{13} M_{\odot}$ and tracing their individual IHL particles back in time, we classify the origin of each IHL particle at each epoch based on the status of the originating galaxy into three categories: brightest halo galaxy (BHG) formation/merger, satellite galaxy stripping, and pre-processing. Our study reveals that the IHL production through BHG formation/merger is the predominant production channel, contributing over 60\% of the total IHL mass across all redshifts. The second most significant IHL production channel is pre-processing, providing more than 20\% in the final HR5 snapshot. Stripping is negligible at $z>4$ but becomes gradually more important as halos mature at $z<4$. Finally, we verify that IHL production through the disruption of dwarf galaxies and in-situ formation is negligible, contributing less than ~3\% and ~0.5\% to the total IHL production, respectively.

astro-ph.GA↗

arXiv2025

Jellyfish Galaxies in Magnetic Fields: Insights from Numerical Simulations

Jellyfish galaxies provide direct evidence of ram pressure stripping in cluster environments. We investigate the role of magnetic fields in the formation of jellyfish galaxies with a multiphase interstellar medium (ISM) using radiation magneto-hydrodynamic simulations. We impose magnetized (MHD) and non-magnetized (HD) winds on the gas-rich dwarf galaxies containing the magnetized or non-magnetized ISM. The MHD winds strip the disk gas more effectively than the HD winds because of the magnetic force acting against the local density gradient, which results in remarkably different ram pressure stripped features. The magnetic fields induced by the MHD winds generate a strong magnetic pressure, which forms smoothed disks and tail gas features. Since the stripped ISM in MHD wind cases travels while being nearly isolated from the intracluster medium (ICM), the stripped ISM mostly forms stars within 20~kpc of the galactic disks. In contrast, non-magnetized winds facilitate the efficient mixing of the stripped ISM with the ICM, resulting in the formation of abundant warm clouds that cool and collapse in the distant ($\sim50-100\,$kpc) tails at times of a few hundred Myr. Consequently, distant tail star formation occurs only in the HD wind runs. Finally, despite the different tail features, the star formation rates in the disk remain similar owing to the interplay between the increased gas stripping and the gas density increase in the disks of the MHD wind runs. These results suggest that the magnetized ICM may have a significant influence on jellyfish galaxies, whereas the magnetized ISM play a minor role.

astro-ph.GA↗

arXiv2025

ODIN: Star Formation Histories Reveal Formative Starbursts Experienced by Lyman Alpha Emitting Galaxies at Cosmic Noon

In this work, we test the frequent assumption that Lyman Alpha Emitting galaxies (LAEs) are experiencing their first major burst of star formation at the time of observation. To this end, we identify 74 LAEs from the ODIN Survey with rest-UV-through-NIR photometry from UVCANDELS. For each LAE, we perform non-parametric star formation history (SFH) reconstruction using the Dense Basis Gaussian process-based method of spectral energy distribution fitting. We find that a strong majority (67%) of our LAE SFHs align with the frequently assumed archetype of a first major star formation burst, with at most modest star formation rates (SFRs) in the past. However, the rest of our LAE SFHs have significant amounts of star formation in the past, with 28% exhibiting earlier bursts of star formation with the ongoing burst having the highest SFR (dominant bursts), and the final 5% having experienced their highest SFR in the past (non-dominant bursts). Combining the SFHs indicating first and dominant bursts, ~95% of LAEs are experiencing their largest burst yet -- a formative burst. We also find that the fraction of total stellar mass created in the last 200 Myr is ~1.3 times higher in LAEs than in mass-matched Lyman Break Galaxy (LBG) samples, and that a majority of LBGs are experiencing dominant bursts, reaffirming that LAEs differ from other star forming galaxies. Overall, our results suggest that multiple evolutionary paths can produce galaxies with strong observed Ly$α$ emission.

astro-ph.GA↗

arXiv2025

Galaxy populations in protoclusters at cosmic noon

We investigate the physical properties and redshift evolution of simulated galaxies residing in protoclusters at cosmic noon, to understand the influence of the environment on galaxy formation. This work is to build clear expectations for the ongoing ODIN survey, devoted to mapping large-scale structures at z=2.4, 3.1, and 4.5 using Ly$α$-emitting galaxies (LAEs) as tracers. From the IllustrisTNG simulations, we define subregions centered on the most massive clusters ranked by total stellar mass at z=0 and study the properties of galaxies within, including LAEs. To model the LAE population, we take a semi-analytical approach that assigns Ly$α$ luminosity and equivalent width based on the UV luminosities to galaxies in a probabilistic manner. We investigate stellar mass, star formation rate, major mergers, and specific star formation rate of the population of star-forming galaxies and LAEs in the field and protocluster environment and trace their evolution. We find that the overall shape of the UV luminosity function (LF) in simulated protocluster environments is characterized by a shallower faint-end slope and an excess on the bright end, signaling different formation histories for galaxies therein. The difference is milder for the Ly$α$ LF. While protocluster galaxies follow the same SFR-$M_{\odot}$ scaling relation as average field galaxies, a larger fraction appears to have experienced major mergers in the last 200 Myr and as a result shows enhanced star formation at a ~60% level, leading to a flatter distribution in both SFR and $M_{\odot}$ relative to galaxies in the average field. We find that protocluster galaxies, including LAEs, begin to quench much earlier (z~0.8-1.6) than field galaxies (z~0.5-0.9); our result is in agreement with recent observational results and highlights the importance of large-scale environment on the overall formation history of galaxies.

astro-ph.GA↗

arXiv2025

Modeling submillimeter galaxies in cosmological simulations: Contribution to the cosmic star formation density and predictions for future surveys

Submillimeter galaxies (SMGs) constitute a key population of bright star-forming galaxies at high redshift. These galaxies challenge galaxy formation models, particularly in reproducing their observed number counts and redshift distributions. Furthermore, although SMGs contribute significantly to the cosmic star formation rate density (SFRD), their precise role remains uncertain. Upcoming surveys, such as the Ultra Deep Survey with the TolTEC camera, are expected to offer valuable insights into SMG properties and their broader impact. Robust modeling of SMGs in a cosmologically representative volume is necessary to investigate their nature in preparation for next-generation submillimeter surveys. We implement and test parametric relations derived from radiative transfer calculations across three cosmological simulations: EAGLE, IllustrisTNG, and FLAMINGO. Particular emphasis is placed on the FLAMINGO due to their large volume and robust statistical sampling of SMGs. Based on the model that best reproduces observations, we forecast submillimeter fluxes within the simulations, analyze the properties of SMGs, and evaluate their evolution over cosmic time. Our results show that the FLAMINGO reproduces the observed redshift distribution and source number counts of SMGs without requiring a top-heavy initial mass function. On the other hand, the EAGLE and IllustrisTNG show a deficit of bright SMGs. We find that SMGs with S850 > 1 mJy contribute up to 27% of the SFRD at z=2.6 in the FLAMINGO, consistent with recent observations. Flux density functions reveal a rise in SMG abundance from z = 6 to 2.5, followed by a sharp decline in the number of brighter SMGs from z = 2.5 to 0. Leveraging the SMG population in FLAMINGO, we forecast that the TolTEC UDS will detect 80,000 sources over 0.8 deg^2 at 1.1 mm (at the 4σ detection limit), capturing about 50% of the cosmic SFRD at z=2.5.

astro-ph.CO↗

arXiv2025

Testing Lyman Alpha Emitters and Lyman-Break Galaxies as Tracers of Large-Scale Structures at High Redshifts

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 Lyα 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.

astro-ph.GA↗

arXiv2024

ODIN: Identifying Protoclusters and Cosmic Filaments Traced by Ly$α$-emitting Galaxies

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$α$-emitting galaxies (LAEs) to trace the large-scale structure (LSS) of the Universe on the scale of 10 - 100 cMpc 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.

astro-ph.GA↗

arXiv2024

RAMSES-yOMP: Performance Optimizations for the Astrophysical Hydrodynamic Simulation Code RAMSES

Developing an efficient code for large, multiscale astrophysical simulations is crucial in preparing the upcoming era of exascale computing. RAMSES is an astrophysical simulation code that employs parallel processing based on the Message Passing Interface (MPI). However, it has limitations in computational and memory efficiency when using a large number of CPU cores. The problem stems from inefficiencies in workload distribution and memory allocation that inevitably occur when a volume is simply decomposed into domains equal to the number of working processors. We present RAMSES-yOMP, which is a modified version of RAMSES designed to improve parallel scalability. Major updates include the incorporation of Open Multi-Processing into the MPI parallelization to take advantage of both the shared and distributed memory models. Utilizing this hybrid parallelism in high-resolution benchmark simulations with full prescriptions for baryonic physics, we achieved a performance increase of a factor of 2 in the total run-time, while using 75% less memory and 30% less storage compared to the original code, when using the same number of processors. These improvements allow us to perform larger or higher-resolution simulations than what was feasible previously.

astro-ph.IM↗

arXiv2024

Emergence of the Galaxy Morphology-Star Formation Activity-Clustercentric Radius Relations in Galaxy Clusters

We investigate when and how the relations of galaxy morphology and star forming activity with clustercentric radius become evident in galaxy clusters. We identify 162 galaxy clusters with total mass $M_{\rm tot}^{\rm cl} > 5 \times 10^{13} {\rm M}_\odot$ at $z = 0.625$ in the Horizon Run 5 (HR5) cosmological hydrodynamical simulation and study how the properties of the galaxies with stellar mass $M_\ast > 5 \times 10^9 {\rm M}_\odot$ near the cluster main progenitors have evolved in the past. Galaxies are classified into disk, spheroid, and irregular morphological types according to the asymmetry and Sersic index of their stellar mass distribution. We also classify galaxies into active and passive ones depending on their specific star-formation rate. We find that the morphology-clustercentric radius relation (MRR) emerges at $z \simeq 1.8$ as the fraction of spheroidal types exceeds 50% in the central region ($d \lesssim 0.1 R_{200}$). Galaxies outside the central region remain disk-dominated. Numerous encounters between galaxies in the central region seem to be responsible for the morphology transformation from disks to spheroids. We also find that the star formation activity-clustercentric radius relation emerges at an epoch different from that of MRR. At $z\simeq0.8$, passive galaxies start to dominate the intermediate radius region ($0.1\lesssim d/R_{200} \lesssim0.3$) and this "quenching region" grows inward and outward thereafter. The region dominated by early-type galaxies (spheroids and passive disks) first appears at the central region at $z\simeq 1.8$, expands rapidly to larger radii as the population of passive disks grows in the intermediate radii, and clusters are dominated by early types after $z\simeq 0.8$.

astro-ph.GA↗

arXiv2024

ODIN: Strong Clustering of Protoclusters at Cosmic Noon

The One-hundred-deg$^2$ DECam Imaging in Narrowbands (ODIN) survey is carrying out a systematic search for protoclusters during Cosmic Noon, using Ly$α$-emitting galaxies (LAEs) as tracers. Once completed, ODIN aims to identify hundreds of protoclusters at redshifts of 2.4, 3.1, and 4.5 across seven extragalactic fields, covering a total area of up to 91~deg$^2$. In this work, we report strong clustering of high-redshift protoclusters through the protocluster-LAE cross-correlation function measurements of 150 protocluster candidates at $z~=~2.4$ and 3.1, identified in two ODIN fields with a total area of 13.9 deg$^2$. At $z~=~2.4$ and 3.1, respectively, the inferred protocluster biases are $6.6^{+1.3}_{-1.1}$ and $6.1^{+1.3}_{-1.1}$, corresponding to mean halo masses of $\log \langle M /M_\odot\rangle = 13.53^{+0.21}_{-0.24}$ and $12.96^{+0.28}_{-0.33}$. By the present day, these protoclusters are expected to evolve into virialized galaxy clusters with a mean mass of $\sim$ $10^{14.5}~M_\odot$. By comparing the observed number density of protoclusters to that of halos with the measured clustering strength, we find that our sample is highly complete. Finally, the similar descendant masses derived for our samples at $z=2.4$ and 3.1 assuming that the halo number density remains constant suggest that they represent similar structures observed at different cosmic epochs. As a consequence, any observed differences between the two samples can be understood as redshift evolution. The ODIN protocluster samples will thus provide valuable insights into the cosmic evolution of cluster galaxies.

astro-ph.GA↗

arXiv2024

Emergence of Exotic Spin Texture in Supramolecular Metal Complexes on a 2D Superconductor

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.

cond-mat.supr-con↗

arXiv2024

Inferring Cosmological Parameters on SDSS via Domain-Generalized Neural Networks and Lightcone Simulations

We present a proof-of-concept simulation-based inference on $Ω_{\rm m}$ and $σ_{8}$ 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 $Ω_{\rm m}=0.339 \pm 0.056$ and $σ_{8}=0.801 \pm 0.061$, 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 $Ω_{\rm m}=0.282 \pm 0.014$ and $σ_{8}=0.786 \pm 0.036$. We emphasize that adaptation across multiple domains can enhance the robustness of the neural networks in observational data.

astro-ph.CO↗

arXiv2024

Star-formation Properties of z ~ 1 Galaxy Clusters and Groups from Horizon Run 5

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.

astro-ph.GA↗

arXiv2024

The Environmental Dependence of the Stellar Mass - Gas Metallicity Relation in Horizon Run 5

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, $δZ_{g}$, 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.

astro-ph.GA↗

arXiv2024

Multi-Orbital Interactions and Spin Polarization in Single Rare-Earth Adatoms

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}~$μ_{\rm{B}}$ 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.

cond-mat.mes-hall↗

arXiv2024

Interpreting X-ray absorption spectra of Vanadyl Phthalocyanines Spin Qubit Candidates using a Machine Learning-Assisted Approach

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.

cond-mat.mtrl-sci↗

arXiv2024

Merger Tree-based Galaxy Matching: A Comparative Study Across Different Resolutions

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.

astro-ph.GA↗

arXiv2024

Improving Matrix Completion by Exploiting Rating Ordinality in Graph Neural Networks

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.

cs.AI↗