arXiv subjects

Hyowon Kim

Publications and source records attributed to Hyowon Kim.

At least 19 recordsLinked to original sources

arXiv2026

HI Depletion Begins Well Beyond the Virial Radius: A FAST Stacking Study of 36 Galaxy Clusters to 5R200

We present a stacking study of the neutral atomic hydrogen (HI) content in and around 36 local galaxy clusters at $z<0.07$, using a combination of the FAST all sky HI survey (FASHI) and the extensive spectroscopic catalog mainly from the Dark Energy Spectroscopic Instrument (DESI). We employ spectral stacking techniques to probe the average HI mass and HI-to-stellar mass ratio ($M_{\rm HI}/M_*$) for member galaxies down to stellar masses of $M_*\sim 10^9M_\odot$, spanning a projected cluster-centric distance to $5R_{200}$. Our analysis reveals a pronounced environmental effect: both $M_{\rm HI}$ and $M_{\rm HI}/M_*$ decrease steadily towards the cluster center, dropping by $\sim 0.5$ dex on average from the outskirts to the core. Crucially, we find that $M_{\rm HI}/M_*$ of galaxies remain lower than the field galaxies even at the $5R_{200}$. This provides direct, statistical evidence for substantial gas stripping and pre-processing in the cluster outskirts, likely occurring in infalling groups and large-scale filaments. By further splitting the sample by $g-r$ color, we show that the HI deficiency persists at fixed galaxy color: even the bluest cluster members exhibit $\sim 0.5$~dex lower $M_{\rm HI}/M_*$ than field galaxies of similar color, reflecting environmental effects on the cold gas reservoir prior to full optical transformation. The total HI mass within clusters and their outskirts agrees broadly with predictions from cosmological simulation. Our results underscore the critical role of the extended cluster environment in quenching galaxies by depleting their cold gas reservoirs well before they enter the dense cluster core.

astro-ph.GA↗

arXiv2026

An Extended Object Poisson Multi-Bernoulli Filter with Zero-Inflated Poisson Measurement Model Using Belief Propagation

This paper presents an efficient implementation of the extended object Poisson multi-Bernoulli (PMB) filter under the zero-inflated Poisson (ZIP) object measurement model using particle belief propagation (BP). The ZIP measurement model separates a Bernoulli object detection event from the conditional Poisson generation of object measurements, enabling principled handling of empty measurement sets. Building upon the PMB mixture posterior, we present a factorized joint posterior over set of objects with object detection variables and a dual representation of data association using both object-oriented and measurement-oriented association variables. Notably, this representation replaces the implicit high-order global hypothesis constraint by local consistency factors, yielding a factor graph amenable to BP. In addition, we present a particle-based implementation, where the single object densities of Bernoulli components are represented using particles. Simulation results show that the proposed method achieves filtering performance comparable to a sampling-based PMBM implementation, while having lower runtime. We also validate the efficacy of the proposed method using real-world lidar data for pedestrian tracking.

eess.SP↗

arXiv2026

New classification method for the dynamical state of galaxy clusters with a Gaussian mixture model

Galaxy clusters are the largest gravitationally bound systems, and they continue their growth through mergers in a hierarchical {\Lambda}CDM Universe. Therefore, we can describe the merger stage of a cluster as the dynamical state of clusters. Previous studies have investigated this phenomenon, but several limitations remain, including reliance on dichotomous classifications, constraints on the number of indicators used, absence of reliability, and incompatibility of methods between observation and simulation studies. To overcome this, we developed an enhanced and observation-applicable cluster dynamical state classification method using the Bayesian classifier with the class-conditional Gaussian mixture distribution model using the N-cluster Run simulation data. The Bayesian classifier was designed for two merger stages (merger and relaxed) as well as three merger stages (recent merger, ancient merger, and relaxed) to provide a more detailed interpretation of the merger processes. In the results, using a larger number of indicators yields better results, with their order of importance being: magnitude difference, center offset, sparsity, Kuiper V statistic, and mirror asymmetry. Additionally, our analyses show that a projected classifier (built on the 6D space, but evaluated on lower dimensional projections) consistently produces better outcomes than non-projected classifiers (i.e., classifiers built directly on the corresponding low dimensional spaces), which means limited observation data can be used to classify with enhanced performance. Furthermore, the new classification method outperforms our previous research. This new method can suggest a way of overcoming previous limitations and provides new insights by providing the reliability of dynamical state classification results.

astro-ph.CO↗

arXiv2026

K-DRIFT Science Theme: New Theoretical Framework Using the Galaxy Replacement Technique for LSB studies

Low-surface-brightness (LSB) structures provide critical insights into the hierarchical formation of galaxies and galaxy clusters. The KASI Deep Rolling Imaging Fast Telescope (K-DRIFT) is designed to detect such diffuse features through deep, wide-field optical imaging with a surface brightness reaching $\sim$$30~\rm{mag}~\rm{arcsec}^{-2}$. To interpret the observation data expected from K-DRIFT, we have developed the Galaxy Replacement Technique (GRT), an $N$-body simulation framework optimized for tracing the gravitational evolution of stellar components. The GRT works by inserting high-resolution galaxy models, including a dark matter (DM) halo and stellar disk, in place of multiple low-resolution DM halos in the base $N$-body cosmological simulation. It allows us to achieve very high mass ($m_{star}=5.4\times10^4\msun\ h^{-1}$) and spatial resolution (10~$\rm{pc}~h^{-1}$) with shorter computation time compared to full hydrodynamic cosmological simulations. Therefore, this technique is particularly well-suited for studying LSB structures, with a surface brightness reaching $\sim$$31~\rm{mag}~\rm{arcsec}^{-2}$. In this paper, we present the motivation and methodology of the GRT, summarize key results from previous studies, and highlight its synergy with K-DRIFT observations. We further discuss planned science cases using the GRT, aiming to build a theoretical basis for interpreting LSB features in various environments.

astro-ph.GA↗

arXiv2026

K-DRIFT Science Theme: Galaxies in the Faint Universe

Low-surface-brightness (LSB) structures serve as evidence of the intricate mass assembly of galaxies, and dedicatedly studying them promises to give us profound insights into the evolutionary history of galaxies. Furthermore, delving into the properties of star formation (SF) in the LSB regime can broaden our understanding of SF activity in regions characterized by low surface gas density, thereby shedding light on fundamental cosmic processes. However, systematic uncertainties may hamper the exploration of the LSB universe by limiting detectable SB levels. Indeed, despite dedicated advancements in telescope and observing techniques over decades, achieving ultra-deep photometric depths in optical wavelengths remains a formidable challenge. To overcome this challenge and explore the LSB universe that we have yet to see, we have been developing a novel telescope called K-DRIFT. This paper outlines the telescope's specification and describes various LSB features we aim for, explicitly focusing on nearby individual galaxies. To further advance the capabilities of the K-DRIFT survey, focused on LSB detection, we present several feasible research topics that utilize other survey data together and discuss the role of LSB observation in understanding the evolution of galaxies.

astro-ph.GA↗

arXiv2025

K-DRIFT Science Theme: Illuminating the Next Era of Galaxy Cluster Science

The KASI Deep Rolling Imaging Fast Telescope (K-DRIFT) is a pioneering instrument designed to explore low-surface-brightness (LSB) phenomena. This white paper presents a compelling array of science cases that showcase K-DRIFT's unique capabilities in unraveling the mysteries of intracluster light (ICL) and other LSB components within galaxy clusters. Exploring the origin of ICL in galaxy clusters and comparing the spatial distributions of ICL and dark matter will offer new insights into galaxy cluster dynamics. Moreover, investigating LSB objects in galaxy clusters, such as LSB structures in the brightest cluster galaxy, ultra-diffuse galaxies, and tidal features, will enhance our understanding of galaxy evolution within the cluster environment. We present our strategies for addressing scientific queries, encompassing LSB observation and analysis techniques, specialized simulations, and machine-learning approaches. Additionally, we examine the potential synergies between K-DRIFT and other ongoing or forthcoming multi-wavelength surveys. This white paper advocates for the recognition and support of K-DRIFT as a dedicated tool for advancing our understanding of the universe's subtlest phenomena.

astro-ph.GA↗

arXiv2025

The role of supercluster filaments in shaping galaxy clusters

In a hierarchical $\Lambda$CDM Universe, cosmic filaments serve as the primary channels for matter accretion into galaxy clusters, influencing the shape of their dark matter halos. We investigate whether the elongation of galaxy clusters correlates with the orientation of surrounding filaments, providing the first observational test of this relationship in large supercluster regions. We identified and characterized cosmic filaments in two dimensions within the two superclusters that are part of the low-redshift sub-survey of the Chilean Cluster Galaxy Evolution Survey (CHANCES): the Shapley supercluster and the Horologium-Reticulum supercluster. We analyzed the alignment between filament directions -- traced by galaxy distributions -- and the triaxiality of cluster gravitational potentials -- traced by X-ray emission- using publicly available optical and X-ray data. We have found that most (82%) of the X-ray clusters are associated with and interconnected by the optically detected filaments. The clusters-filaments alignment analysis shows that the elongation of most clusters is well aligned with nearby filaments, providing observational confirmation of theoretical predictions, with the alignment progressively reducing at larger cluster-centric distances ($> 1.6 r_{200}$). Overall, our results support the notion that filaments are the main source of galaxy accretion at redshift below 0.1 and additionally provide evidence that matter accretion through filaments shapes the gravitational potential of galaxy clusters. We propose this measurement as a simple observational proxy to determine the direction of accretion in clusters, which is key to understanding both galaxy evolution and the merger history of galaxy clusters.

astro-ph.CO↗

arXiv2025

Tracing Dark Matter in the Central Regions of Galaxy Clusters Using Galaxies, Gas, and Intracluster Light in TNG300: Connections to Cluster Dynamical State

Recent studies have highlighted the potential of intracluster light (ICL) as a dark matter tracer. Moreover, the ICL co-evolves with the brightest cluster galaxy (BCG) and the host cluster, making it a valuable tool for understanding cluster dynamics. In this study, we utilize 426 galaxy clusters (with total mass $M_{\rm tot}>10^{14} M_{\odot}$ at $z=0$) simulated in the cosmological hydrodynamical simulation Illustris TNG300 to compare the spatial distributions of dark matter, member galaxies, gas, and ICL and assess their effectiveness as dark matter tracers in the central regions of clusters at $R_{\rm vir}<0.3$. We apply the Weighted Overlap Coefficient (WOC), a methodology for quantifying the similarity of two-dimensional spatial distributions, to various components of the galaxy clusters at different dynamical stages. Our findings reveal that the spatial distributions of both ICL combined with the BCG and gas closely resemble the dark matter distribution, with higher fidelity observed in more relaxed galaxy clusters with earlier half-mass epochs. These results demonstrate that the BCG+ICL component serves as an effective tracer of dark matter, consistent with previous observational studies linking cluster light to mass. Moreover, the degree of spatial similarity between the BCG+ICL and dark matter distributions appears to reflect the dynamical state of the cluster.

astro-ph.GA↗

arXiv2025

RIS-Enabled Self-Localization with FMCW Radar

In the upcoming vehicular networks, reconfigurable intelligent surfaces (RISs) are considered as a key enabler of user self-localization without the intervention of the access points (APs). In this paper, we investigate the feasibility of RIS-enabled self-localization with no APs. We first develop a digital signal processing (DSP) unit for estimating the geometric parameters such as the angle, distance, and velocity and for RIS-enabled self-localization. Second, we set up an experimental testbed consisting of a Texas Instrument frequency modulated continuous wave (FMCW) radar for the user and SilversIMA module for the RIS. Our results confirm the validity of the developed DSP unit and demonstrate the feasibility of RIS-enabled self-localization.

eess.SP↗

arXiv2025

Efficient and Accurate Scene Text Recognition with Cascaded-Transformers

In recent years, vision transformers with text decoder have demonstrated remarkable performance on Scene Text Recognition (STR) due to their ability to capture long-range dependencies and contextual relationships with high learning capacity. However, the computational and memory demands of these models are significant, limiting their deployment in resource-constrained applications. To address this challenge, we propose an efficient and accurate STR system. Specifically, we focus on improving the efficiency of encoder models by introducing a cascaded-transformers structure. This structure progressively reduces the vision token size during the encoding step, effectively eliminating redundant tokens and reducing computational cost. Our experimental results confirm that our STR system achieves comparable performance to state-of-the-art baselines while substantially decreasing computational requirements. In particular, for large-models, the accuracy remains same, 92.77 to 92.68, while computational complexity is almost halved with our structure.

cs.CV↗

arXiv2025

Accurate Scene Text Recognition with Efficient Model Scaling and Cloze Self-Distillation

Scaling architectures have been proven effective for improving Scene Text Recognition (STR), but the individual contribution of vision encoder and text decoder scaling remain under-explored. In this work, we present an in-depth empirical analysis and demonstrate that, contrary to previous observations, scaling the decoder yields significant performance gains, always exceeding those achieved by encoder scaling alone. We also identify label noise as a key challenge in STR, particularly in real-world data, which can limit the effectiveness of STR models. To address this, we propose Cloze Self-Distillation (CSD), a method that mitigates label noise by distilling a student model from context-aware soft predictions and pseudolabels generated by a teacher model. Additionally, we enhance the decoder architecture by introducing differential cross-attention for STR. Our methodology achieves state-of-the-art performance on 10 out of 11 benchmarks using only real data, while significantly reducing the parameter size and computational costs.

cs.CV↗

arXiv2025

Intrinsic Cram\'er-Rao Bound based 6D Localization and Tracking for 5G/6G Systems

Localization and tracking are critical components of integrated sensing and communication (ISAC) systems, enhancing resource management, beamforming accuracy, and overall system reliability through precise sensing. Due to the high path loss of the high-frequency systems, antenna arrays are required at the transmitter and receiver sides for beamforming gain. However, beam misalignment may occur, which requires accurate tracking of the six-dimensional (6D) state, namely, 3D position and 3D orientation. In this work, we first address the challenge that the rotation matrix, being part of the Lie group rather than Euclidean space, necessitates the derivation of the ICRB for an intrinsic performance benchmark. Then, leveraging the derived ICRB, we develop two filters-one utilizing pose fusion and the other employing error-state Kalman filter to estimate the UE's 6D state for different computational resource consumption and accuracy requirements. Simulation results validate the ICRB and assess the performance of the proposed filters, demonstrating their effectiveness and improved accuracy in 6D state tracking.

eess.SP↗

arXiv2024

Improving 3D Cellular Positioning Integrity with Bayesian RAIM

Ensuring positioning integrity amid faulty measurements is crucial for safety-critical applications, making receiver autonomous integrity monitoring (RAIM) indispensable. This paper introduces a Bayesian RAIM algorithm with a streamlined architecture for snapshot-type 3D cellular positioning. Unlike traditional frequentist-type RAIM algorithms, it computes the exact posterior probability density function (PDF) of the position vector as a Gaussian mixture (GM) model using efficient message passing along a factor graph. This Bayesian approach retains all crucial information from the measurements, eliminates the need to discard faulty measurements, and results in tighter protection levels (PLs) in 3D space and 1D/2D subspaces that meet target integrity risk (TIR) requirements. Numerical simulations demonstrate that the Bayesian RAIM algorithm significantly outperforms a baseline algorithm, achieving over $50\%$ PL reduction at a comparable computational cost.

eess.SP↗

arXiv2024

Batch SLAM with PMBM Data Association Sampling and Graph-Based Optimization

Simultaneous localization and mapping (SLAM) methods need to both solve the data association (DA) problem and the joint estimation of the sensor trajectory and the map, conditioned on a DA. In this paper, we propose a novel integrated approach to solve both the DA problem and the batch SLAM problem simultaneously, combining random finite set (RFS) theory and the graph-based SLAM approach. A sampling method based on the Poisson multi-Bernoulli mixture (PMBM) density is designed for dealing with the DA uncertainty, and a graph-based SLAM solver is applied for the conditional SLAM problem. In the end, a post-processing approach is applied to merge SLAM results from different iterations. Using synthetic data, it is demonstrated that the proposed SLAM approach achieves performance close to the posterior Cram\'er-Rao bound, and outperforms state-of-the-art RFS-based SLAM filters in high clutter and high process noise scenarios.

eess.SP↗

arXiv2024

RIS-Assisted High Resolution Radar Sensing

This paper analyzes monostatic sensing by a user equipment (UE) for a setting in which the UE is unable to resolve multiple targets due to their interference within a single resolution bin. It is shown how sensing accuracy, in terms of both detection rate and localization accuracy, can be boosted by a reconfigurable intelligent surface (RIS), which can be advantageously used to provide signal diversity and aid in resolving the targets. Specifically, assuming prior information on the presence of a cluster of targets, a RIS beam sweep procedure is used to facilitate the high resolution sensing. We derive the Cram\'er-Rao lower bounds (CRLBs) for channel parameter estimation and sensing and an upper bound on the detection probability. The concept of coherence is defined and analyzed theoretically. Then, we propose an orthogonal matching pursuit (OMP) channel estimation algorithm combined with data association to fuse the information of the non-RIS signal and the RIS signal and perform sensing. Finally, we provide numerical results to verify the potential of RIS for improving sensor resolution, and to demonstrate that the proposed methods can realize this potential for RIS-assisted high resolution sensing.

eess.SP↗

arXiv2024

New observational recipes for measuring dynamical state of galaxy clusters

During cluster assembly, a cluster's virialization process leaves behind signatures that can provide information on its dynamical state. However, no clear consensus yet exists on the best way to achieve this. Therefore, we attempt to derive improved recipes for classifying the dynamical state of clusters in observations using cosmological simulations. Cluster halo mass and their subhalos' mass are used to $ 10^{14}M_{\odot} h^{-1}$ and $10^{10}M_{\odot} h^{-1}$ to calculate five independent dynamical state indicators. We experiment with recipes by combining two to four indicators for detecting specific merger stages like recent and ancient mergers. These recipes are made by plotting merging clusters and a control sample of relaxed clusters in multiple indicators parameter space, and then applying a rotation matrix method to derive the best way to separate mergers from the control sample. The success of the recipe is quantified using the success rate and the overlap percentage of the merger and control histograms along the newly rotated $x$-axis. This provides us with recipes using different numbers of combined indicators and for different merger stage. Among the recipes, the stellar mass gap and center offset are the first and second most dominant of the indicators, and using more indicators improves the effectiveness of the recipe. When applied to observations, our results show good agreement with literature values of cluster dynamical state.

astro-ph.GA↗

arXiv2024

Integrated Communication, Localization, and Sensing in 6G D-MIMO Networks

Future generations of mobile networks call for concurrent sensing and communication functionalities in the same hardware and/or spectrum. Compared to communication, sensing services often suffer from limited coverage, due to the high path loss of the reflected signal and the increased infrastructure requirements. To provide a more uniform quality of service, distributed multiple input multiple output (D-MIMO) systems deploy a large number of distributed nodes and efficiently control them, making distributed integrated sensing and communications (ISAC) possible. In this paper, we investigate ISAC in D-MIMO through the lens of different design architectures and deployments, revealing both conflicts and synergies. In addition, simulation and demonstration results reveal both opportunities and challenges towards the implementation of ISAC in D-MIMO.

cs.IT↗

arXiv2024

Spatial Distribution of Intracluster Light versus Dark Matter in Horizon Run 5

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.

astro-ph.CO↗