arXiv subjects

Jongho Park

Publications and source records attributed to Jongho Park.

At least 37 records · Page 2Linked to original sources

arXiv2025

Probing jet base emission of M87* with the 2021 Event Horizon Telescope observations

We investigate the presence and spatial characteristics of the jet base emission in M87* at 230 GHz, enabled by the enhanced uv coverage in the 2021 Event Horizon Telescope (EHT) observations. The addition of the 12-m Kitt Peak Telescope and NOEMA provides two key intermediate-length baselines to SMT and the IRAM 30-m, giving sensitivity to emission structures at scales of $\sim250~μ$as and $\sim2500~μ$as (0.02 pc and 0.2 pc). Without these baselines, earlier EHT observations lacked the capability to constrain emission on large scales, where a "missing flux" of order $\sim1$ Jy is expected. To probe these scales, we analyzed closure phases, robust against station-based gain errors, and modeled the jet base emission using a simple Gaussian offset from the compact ring emission at separations $>100~μ$as. Our analysis reveals a Gaussian feature centered at ($Δ$RA $\approx320~μ$as, $Δ$Dec $\approx60~μ$as), a projected separation of $\approx5500$ AU, with a flux density of only $\sim60$ mJy, implying that most of the missing flux in previous studies must arise from larger scales. Brighter emission at these scales is ruled out, and the data do not favor more complex models. This component aligns with the inferred direction of the large-scale jet and is consistent with emission from the jet base. While our findings indicate detectable jet base emission at 230 GHz, coverage from only two intermediate baselines limits reconstruction of its morphology. We therefore treat the recovered Gaussian as an upper limit on the jet base flux density. Future EHT observations with expanded intermediate-baseline coverage will be essential to constrain the structure and nature of this component.

astro-ph.HE↗

arXiv2025

Helical Magnetic Field in the Acceleration--Collimation Zone of the M87 Jet

Relativistic jets from supermassive black holes are expected to be magnetically launched and guided, with magnetic energy systematically converted to bulk kinetic energy throughout an extended acceleration-collimation zone (ACZ). A key prediction of magnetohydrodynamic (MHD) models is a transition from poloidally dominated fields near the engine to toroidally dominated fields downstream, yet direct tests within the ACZ are hampered by weak polarization and strong Faraday rotation. We report quasi-simultaneous, high-sensitivity, multifrequency very long baseline interferometric polarimetry of M87 spanning 1.4-24.4GHz. We present high-fidelity, Faraday rotation-corrected maps of intrinsic linear polarization that continuously resolve the ACZ in the de-projected distance range of ~9e3 to ~3.6e5 gravitational radii from the black hole. The maps reveal pronounced north-south asymmetries in fractional linear polarization and electric vector position angle (EVPA), peaking in the inner ACZ at a projected distance of ~20mas along the jet and remaining prominent out to ~100mas. These signatures are best reproduced by models with a large-scale, ordered helical field that retains a substantial poloidal component-contrary to the rapid toroidal dominance expected under steady, ideal MHD. This tension implies ongoing magnetic dissipation that limits toroidal buildup over the ACZ. The handedness of the helix provides an independent constraint on the black hole's spin direction, supporting a spin vector oriented away from the observer, consistent with the orientation inferred from horizon-scale imaging. Farther downstream, the asymmetries diminish, and the EVPA and fractional polarization distributions become more symmetric; we tentatively interpret this as evolution toward a more poloidally dominated configuration, while noting current sensitivity and dynamic-range limits.

astro-ph.HE↗

arXiv2025

Effective Test-Time Scaling of Discrete Diffusion through Iterative Refinement

Test-time scaling through reward-guided generation remains largely unexplored for discrete diffusion models despite its potential as a promising alternative. In this work, we introduce Iterative Reward-Guided Refinement (IterRef), a novel test-time scaling method tailored to discrete diffusion that leverages reward-guided noising-denoising transitions to progressively refine misaligned intermediate states. We formalize this process within a Multiple-Try Metropolis (MTM) framework, proving convergence to the reward-aligned distribution. Unlike prior methods that assume the current state is already aligned with the reward distribution and only guide the subsequent transition, our approach explicitly refines each state in situ, progressively steering it toward the optimal intermediate distribution. Across both text and image domains, we evaluate IterRef on diverse discrete diffusion models and observe consistent improvements in reward-guided generation quality. In particular, IterRef achieves striking gains under low compute budgets, far surpassing prior state-of-the-art baselines.

cs.LG↗

arXiv2025

Lookahead Unmasking Elicits Accurate Decoding in Diffusion Language Models

Masked Diffusion Models (MDMs) as language models generate by iteratively unmasking tokens, yet their performance crucially depends on the inference time order of unmasking. Prevailing heuristics, such as confidence based sampling, are myopic: they optimize locally, fail to leverage extra test-time compute, and let early decoding mistakes cascade. We propose Lookahead Unmasking (LookUM), which addresses these concerns by reformulating sampling as path selection over all possible unmasking orders without the need for an external reward model. Our framework couples (i) a path generator that proposes paths by sampling from pools of unmasking sets with (ii) a verifier that computes the uncertainty of the proposed paths and performs importance sampling to subsequently select the final paths. Empirically, erroneous unmasking measurably inflates sequence level uncertainty, and our method exploits this to avoid error-prone trajectories. We validate our framework across six benchmarks, such as mathematics, planning, and coding, and demonstrate consistent performance improvements. LookUM requires only two to three paths to achieve peak performance, demonstrating remarkably efficient path selection. The consistent improvements on both LLaDA and post-trained LLaDA 1.5 are particularly striking: base LLaDA with LookUM rivals the performance of RL-tuned LLaDA 1.5, while LookUM further enhances LLaDA 1.5 itself showing that uncertainty based verification provides orthogonal benefits to reinforcement learning and underscoring the versatility of our framework. Code will be publicly released.

cs.LG↗

arXiv2025

Not All Bits Are Equal: Scale-Dependent Memory Optimization Strategies for Reasoning Models

While 4-bit quantization has emerged as a memory-optimal choice for non-reasoning models and zero-shot tasks across scales, we show that this universal prescription fails for reasoning models, where the KV cache rather than model size can dominate memory. Through systematic experiments across 1,700 inference scenarios on AIME25 and GPQA-Diamond, we find a scale-dependent trade-off: models with an effective size below 8-bit 4B parameters achieve better accuracy by allocating memory to more weights rather than longer generation, while larger models achieve better accuracy by allocating memory to longer generations. This scale threshold also determines when parallel scaling becomes memory-efficient and whether KV cache eviction outperforms KV quantization. Our findings show that memory optimization for LLMs cannot be scale-agnostic, while providing principled guidelines: for small reasoning models, prioritize model capacity over test-time compute, while for larger ones, maximize test-time compute. Our results suggest that optimizing reasoning models for deployment requires fundamentally different strategies from those established for non-reasoning models.

cs.LG↗

arXiv2025

Monitoring of 3C 286 with ALMA, IRAM, and SMA from 2006 to 2025: Stability, Synchrotron Ages, and Frequency-Dependent Polarization Attributed to Core-Shift

We present the results of multi-frequency monitoring of the radio quasar 3C 286, conducted using three instruments: ALMA at 91.5, 103.5, 233.0, and 343.4 GHz, the IRAM 30-m Telescope at 86 and 229 GHz, and SMA at 225 GHz. The IRAM measurements from 2006 to 2024 show that the total flux of 3C 286 is stable within measurement uncertainties, indicating long-term stability up to 229 GHz, when applying a fixed Kelvin-to-Jansky conversion factor throughout its dataset. ALMA data from 2018 to 2024 exhibit a decrease in flux, which up to 4% could be attributed to an apparent increase in the absolute brightness of Uranus, the primary flux calibrator for ALMA with the ESA4 model. Taken together, these results suggest that the intrinsic total flux of 3C 286 has remained stable up to 229 GHz over the monitoring period. The polarization properties of 3C 286 are stable across all observing frequencies. The electric vector position angle (EVPA) gradually rotates as a function of wavelength squared, which is well described by a single power-law over the full frequency range. We therefore propose using the theoretical EVPA values from this model curve for absolute EVPA calibration between 5 and 343.4 GHz. The Faraday rotation measure increases as a function of frequency up to (3.2+/-1.5)x10^4 rad m^-2, following RM proportional to nu^alpha with alpha = 2.05+/-0.06. This trend is consistent with the core-shift effect expected in a conical jet.

astro-ph.GA↗

arXiv2025

Parallel subspace correction methods for semicoercive and nearly semicoercive convex optimization with applications to nonlinear PDEs

We present new convergence analyses for parallel subspace correction methods for unconstrained semicoercive and nearly semicoercive convex optimization problems, generalizing the theory of singular and nearly singular linear problems to a class of nonlinear problems. Our results demonstrate that the elegant theoretical framework developed for singular and nearly singular linear problems can be extended to unconstrained semicoercive and nearly semicoercive convex optimization problems. For semicoercive problems, we show that the convergence rate can be estimated in terms of a seminorm stable decomposition over the subspaces and the kernel of the problem, aligning with the theory for singular linear problems. For nearly semicoercive problems, we establish a parameter-independent convergence rate, assuming the kernel of the semicoercive part can be decomposed into a sum of local kernels, which aligns with the theory for nearly singular problems. To demonstrate the applicability of our results, we provide convergence analyses of two-level additive Schwarz methods for solving certain nonlinear partial differential equations with Neumann boundary conditions, within the proposed abstract framework.

math.NA↗

arXiv2025

Auxiliary space theory for the analysis of iterative methods for semidefinite linear systems

We present an auxiliary space theory that provides a unified framework for analyzing various iterative methods for solving linear systems that may be semidefinite. By interpreting a given iterative method for the original system as an equivalent, yet more elementary, iterative method for an auxiliary system defined on a larger space, we derive sharp convergence estimates using elementary linear algebra. In particular, we establish identities for the error propagation operator and the condition number associated with iterative methods, which generalize and refine existing results. The proposed auxiliary space theory is applicable to the analysis of numerous advanced numerical methods in scientific computing. To illustrate its utility, we present three examples -- subspace correction methods, Hiptmair--Xu preconditioners, and auxiliary grid methods -- and demonstrate how the proposed theory yields refined analyses for these cases.

math.NA↗

arXiv2025

A Diffusion-Based Framework for Configurable and Realistic Multi-Storage Trace Generation

We propose DiTTO, a novel diffusion-based framework for generating realistic, precisely configurable, and diverse multi-device storage traces. Leveraging advanced diffusion techniques, DiTTO enables the synthesis of high-fidelity continuous traces that capture temporal dynamics and inter-device dependencies with user-defined configurations. Our experimental results demonstrate that DiTTO can generate traces with high fidelity and diversity while aligning closely with guided configurations with only 8% errors.

cs.CV↗

arXiv2025

Can Large Language Models Develop Strategic Reasoning? Post-training Insights from Learning Chess

While reinforcement learning (RL) for large language models (LLMs) has shown promise in mathematical reasoning, strategic reasoning for LLMs using RL remains largely unexplored. We investigate whether LLMs can develop strategic reasoning capabilities through RL in chess. To this end, we leverage a chess-pretrained action-value network to provide dense reward on the LLM's output move quality, which can be seen as a form of knowledge distillation. Our experiments show that our distillation-based dense rewards often outperform sparse binary rewards. However, surprisingly, all models plateau far below expert levels. We provide SFT and RL ablations on chess reasoning training and find evidence that this limitation stems from a deficit in the pretrained models' internal understanding of chess-a deficit which RL alone may not be able to fully overcome. The code is available at https://github.com/krafton-ai/Chess-R1.

cs.AI↗

arXiv2025

Energetically Favored One-Dimensional Moiré Superstructure in the Pseudo-Square Lattice GdTe3

Moiré engineering in layered crystals has recently gained considerable attention due to the discovery of various structural and physical phenomena, including interfacial reconstruction, superconductivity, magnetism, and distinctive optoelectronic properties. Nevertheless, most explored moiré systems have been limited to hexagonal lattices, thereby constraining a comprehensive understanding and technological application of moiré phenomena in general layered crystals. Here, we investigate GdTe3, a pseudo-tetragonal layered crystal, as a platform to explore unconventional moiré phenomena. GdTe3 exhibits a slight in-plane distortion correlated with the direction of charge density wave formation. Through vertical stacking of layers with different distortions-induced via a controlled strain/release process-we realize energetically favorable one-dimensional (1D) moiré superstructures. Using transmission electron microscopy (TEM), including high-resolution scanning TEM imaging, dark-field TEM imaging, and sample tilting experiments, we systematically examine stacking variations across the 1D moiré structure. Additionally, electron energy loss spectroscopy reveals modulations in electronic properties associated with the 1D moiré structure. Our findings expand the scope of moiré systems beyond conventional hexagonal twistronics, enabling exploration of moiré phenomena in low-symmetry van der Waals crystals.

cond-mat.mtrl-sci↗

arXiv2025

Task Diversity Shortens the ICL Plateau

In-context learning (ICL) describes a language model's ability to generate outputs based on a set of input demonstrations and a subsequent query. To understand this remarkable capability, researchers have studied simplified, stylized models. These studies have consistently observed long loss plateaus, during which models exhibit minimal improvement, followed by a sudden, rapid surge of learning. In this work, we reveal that training on multiple diverse ICL tasks simultaneously shortens the loss plateaus, making each task easier to learn. This finding is surprising as it contradicts the natural intuition that the combined complexity of multiple ICL tasks would lengthen the learning process, not shorten it. Our result suggests that the recent success in large-scale training of language models may be attributed not only to the richness of the data at scale but also to the easier optimization (training) induced by the diversity of natural language training data.

cs.LG↗

arXiv2025

Reference compositions for bismuth telluride thermoelectric materials for low-temperature power generation

Thermoelectric (TE) technology enables direct heat-to-electricity conversion and is gaining attention as a clean, fuel-saving, and carbon-neutral solution for industrial, automotive, and marine applications. Despite nearly a century of research, apart from successes in deep-space power sources and solid-state cooling modules, the industrialization and commercialization of TE power generation remain limited. Since the new millennium, nanostructured bulk materials have accelerated the discovery of new TE systems. However, due to limited access to high-temperature heat sources, energy harvesting still relies almost exclusively on BiTe-based alloys, which are the only system operating stably near room temperature. Although many BiTe-based compositions have been proposed, concerns over reproducibility, reliability, and lifetime continue to hinder industrial adoption. Here, we aim to develop reference BiTe-based thermoelectric materials through data-driven analysis of Starrydata2, the world's largest thermoelectric database. We identify Bi0.46Sb1.54Te3 and Bi2Te2.7Se0.3 as the most frequently studied ternary compositions. These were synthesized using hot pressing and spark-plasma sintering. Thermoelectric properties were evaluated with respect to the processing method and measurement direction. The results align closely with the median of reported data, confirming the representativeness of the selected compositions. We propose these as reference BiTe materials, accompanied by transparent data and validated benchmarks. Their use can support the standardization of TE legs and modules while accelerating performance evaluation and industrial integration. We further estimated the performance of a thermoelectric module made from the reference composition, which gives the power output of over 2.51 W and an efficiency of 3.58% at a temperature difference of 120 K.

cond-mat.mtrl-sci↗

arXiv2025

Constraining the Mass of a Hypothetical Secondary Black Hole in M87 with the NANOGrav 15-Year Data Set

Galaxy mergers, each hosting a supermassive black hole (SMBH), are thought to form SMBH binaries. Motivated by recent observations from the East Asian VLBI Network (EAVN) showing periodic behavior in the M87 jet, a precession of about 11 years and a transverse oscillation of about 0.9 years, we constrain the mass of a hypothetical secondary black hole orbiting the primary SMBH in M87. To constrain the mass ratio between the primary SMBH ($M_{1}$) and the secondary black hole ($M_{2}$) defined as $q \equiv M_{2}/M_{1} \leq 1$, and the length of the semimajor axis of the binary system ($a$), we impose the following three constraints: (i) the lower limit of $a$, below which the SMBH binary is expected to merge. (ii) the strain amplitude of the gravitational wave background (GWB) at nanohertz frequencies shown in the NANOGrav 15-year dataset. (iii) a finite length of the semimajor axis of $M_{1}$, that can induce periodic behavior in the jet. By combining these constraints, we obtain the allowed parameter space for $q$ and $a$. If either of the EAVN-detected periods ($T$) corresponds to the binary's orbital period, the allowed range of $q$ is $6.9 \times 10^{-3} \le q \le 4.2 \times 10^{-2}$ for $T \approx 11$ years, and $3.7\times 10^{-2} \le q \le 1$ for $T \approx 0.9$ years. VLBI astrometric monitoring of the jet base of M87 is essential to explore the allowed parameter space for $q$ and $a$.

astro-ph.HE↗

arXiv2025

Enhanced imaging of M87*: Simulations with the EHT and extended-KVN

The Event Horizon Telescope (EHT) has successfully revealed the shadow of the supermassive black hole, M87*, with an unprecedented angular resolution of approximately 20 uas at 230 GHz. However, because of limited short baseline lengths, the EHT has been constrained in its ability to recover larger scale jet structures. The extended Korean VLBI Network (eKVN) is committed to joining the EHT from 2024 that can improve short baseline coverage. This study evaluates the impact of the participation of eKVN in the EHT on the recovery of the M87* jet. Synthetic data, derived from a simulated M87* model, were observed using both the EHT and the combined EHT+eKVN arrays, followed by image reconstructions from both configurations. The results indicate that the inclusion of eKVN significantly improves the recovery of jet structures by reducing residual noise. Furthermore, jackknife tests, in which one or two EHT telescopes were omitted - simulating potential data loss due to poor weather - demonstrate that eKVN effectively compensates for these missing telescopes, particularly in short baseline coverage. Multi-frequency synthesis imaging at 86-230 GHz shows that the EHT+eKVN array enhances the recovered spectral index distribution compared to the EHT alone and improves image reconstruction at each frequency over single-frequency imaging. As the EHT continues to expand its array configuration and observing capabilities to probe black hole physics more in depth, the integration of eKVN into the EHT will significantly enhance the stability of observational results and improve image fidelity. This advancement will be particularly valuable for future regular monitoring observations, where consistent data quality is essential.

astro-ph.IM↗

arXiv2025

Gamma-ray flares from the jet of the blazar CTA 102 in 2016-2018

CTA 102 is a $γ$-ray bright blazar that exhibited multiple flares in observations by the Large Area Telescope on board the Fermi Gamma-Ray Space Telescope during the period of 2016-2018. We present results from the analysis of multi-wavelength light curves aiming at revealing the nature of $γ$-ray flares from the relativistic jet in the blazar. We analyse radio, optical, X-ray, and $γ$-ray data obtained in a period from 2012 September 29 to 2018 October 8. We identify six flares in the $γ$-ray light curve, showing a harder-when-brighter-trend in the $γ$-ray spectra. We perform a cross-correlation analysis of the multi-wavelength light curves. We find nearly zero time lags between the $γ$-ray and optical and X-ray light curves, implying a common spatial origin for the emission in these bands. We find significant correlations between the $γ$-ray and radio light curves as well as negative/positive time lags with the $γ$-ray emission lagging/leading the radio during different flaring periods. The time lags between $γ$-ray and radio emission propose the presence of multiple $γ$-ray emission sites in the source. As seen in 43 GHz images from the Very Long Baseline Array, two moving disturbances (or shocks) were newly ejected from the radio core. The $γ$-ray flares from 2016 to 2017 are temporally coincident with the interaction between a traveling shock and a quasi-stationary one at $\sim$0.1 mas from the core. The other shock is found to emerge from the core nearly simultaneous with the $γ$-ray flare in 2018. Our results suggest that the $γ$-ray flares originated from shock-shock interactions.

astro-ph.HE↗

arXiv2024

Demographics of black holes at $<$100 R$_{\rm g}$ scales: accretion flows, jets, and shadows

Using the Event Horizon Telescope (EHT), the gravitationally lensed rings around the supermassive black holes (SMBHs) in Messier 87 (M87) and Sagittarius A* (Sgr A*) have now been successfully imaged at a resolution under 10 gravitational radii (R$_{\rm g}$ $ = \rm{GM/c^2}$). To expand studies beyond M87 and Sgr A*, we have constructed the Event Horizon and Environs (ETHER) sample, a comprehensive database encompassing approximately 3.15 million SMBH mass estimates, $\sim$ 20,000 Very-Long Baseline Interferometry (VLBI) radio flux densities, and $\sim$ 36,000 hard X-ray flux densities. This database is designed to identify and optimize target selection for the EHT and its upgrades on the ground and in space. We have identified a Gold Sample (GS) of nearby low-luminosity Active Galactic Nuclei (AGNs) within it that are ideal for studying jet bases and potentially imaging black hole shadows. We observed 27 of these AGNs using the EHT from 2022 to 2024, providing an opportunity to resolve and image accretion flows and jets at resolutions of $\leq$ 100 R$_{\rm g}$. Only a few SMBHs have sufficiently high enough flux density to be imaged at scales of $\leq$ 50 R$_{\rm g}$ with the present EHT. Among these are M87, Sgr A*, NGC4594 (Sombrero/M104), NGC4261, and NGC4374 (Messier 84/M84). Of these, NGC4261, Sombrero, and M84 have been observed and/or are scheduled for deep imaging with EHT+ALMA from 2023 to 2025. Sombrero, NGC4261, M84, NGC4278, and NGC5232 are clearly detected in our EHT+ALMA observations in 2022, indicating that the 230 GHz flux density from the accretion flows is significantly high. Ongoing imaging of the ETHER GS will enable measurements of black hole mass and spin, help constrain General Relativity, and enrich our understanding of jet launching and accretion inflows across a broad multi-parameter space, including black hole mass, spin, accretion rate, and orientation.

astro-ph.GA↗

arXiv2024

Lexico: Extreme KV Cache Compression via Sparse Coding over Universal Dictionaries

We introduce Lexico, a novel KV cache compression method that leverages sparse coding with a universal dictionary. Our key finding is that key-value cache in modern LLMs can be accurately approximated using sparse linear combination from a small, input-agnostic dictionary of ~4k atoms, enabling efficient compression across different input prompts, tasks and models. Using orthogonal matching pursuit for sparse approximation, Lexico achieves flexible compression ratios through direct sparsity control. On GSM8K, across multiple model families (Mistral, Llama 3, Qwen2.5), Lexico maintains 90-95% of the original performance while using only 15-25% of the full KV-cache memory, outperforming both quantization and token eviction methods. Notably, Lexico remains effective in low memory regimes where 2-bit quantization fails, achieving up to 1.7x better compression on LongBench and GSM8K while maintaining high accuracy.

cs.LG↗