Korea Institute for Advanced Study

Can one characterize the long-term modus operandi of a complex historical social system that could last several centuries? The primary obstacle would be the availability of data with sufficient richness and scale collected using a consistent methodology. Even if a system of official, authoritative, and consistent record keeping had existed during the historical regime’s existence, complete preservation of the records after many centuries of historical turbulence, either man-made or natural, up until the present day would be exceptionally challenging. If such data were to survive, however, recent rapid developments in our ability in data archival, retrieval, and statistical analysis could open up new avenues for understanding the workings of those historical social systems, enabling us to gain fresh perspectives on long-standing questions, how they evolved, and how they ultimately ceased to exist. The historical Korean kingdom of Joseon is a such rare case, having maintained consistent record-keeping throughout its five-century existence. Since bureaucratic administration was the primary mechanism through which the dynasty maintained its remarkable stability, we analyze the career trajectories of its officials using two comprehensive government records: the Annals of the Joseon Dynasty, which details the kingdom’s affairs, and the Bangmok, which contains personnel information on bureaucrats who passed the civil service examination, the fundamental gateway to governance. Our primary finding from the analysis of the career trajectories of 14 638 bureaucrats is that Joseon’s system maintained a stable behavioral pattern for four centuries represented by a characteristic Gini coefficient of 0.52 of Total Success Index (TSI) of the bureaucrats, then the stability disappeared in the 19th century as it rapidly increased to 0.78, indications of a significantly elevated level of inequality. We also find that it coincided with a 2.02-fold increase in the representation of powerful clans ( Sedoga ) within Joseon’s bureaucracy. These findings provide a quantitative indication of the systemic corruption of Joseon’s long-lasting meritocratic system that preceded the dynasty’s demise shortly after. • The career trajectories of Joseon Dynasty’s 14 638 are analyzed using the Annals (records of the monarch’s words and actions) and the Bangmok (personnel records of Gwageo, the civil service exam). • The bureaucrats career success show statistically significant correlation with family background and geographical origin. • The system showed stability for four centuries with a Gini inequality index of 0.52. • In the 19th century, the Gini index increases rapidly to 0.78, coinciding with the rise of powerful clans ( Sedoga ) and subsequent demise of the dynasty.

Abstract Recent observations from the James Webb Space Telescope have revealed unexpectedly luminous galaxies, exhibiting stellar masses and luminosities significantly higher than predicted by theoretical models at Cosmic Dawn. In this study, we present a suite of cosmological zoomed-in simulations targeting high-redshift ( z ≥ 10) galaxies with dark matter halo masses in the range 10 10 –10 11 M ⊙ at z = 10, using state-of-the-art galaxy formation simulation codes ( Enzo , Ramses , Changa , Gadget-3 , Gadget-4 , and Gizmo ). This study aims to evaluate the convergence of the participating codes and their reproducibility of high-redshift galaxies with the galaxy formation model calibrated at relatively low redshift, without additional physics for high-redshift environments. The subgrid physics follows the AGORA CosmoRun framework, with adjustments to resolution and initial conditions to emulate similar physical environments in the early Universe. The participating codes show consistent results for key galaxy properties (e.g., stellar mass), but also reveal notable differences (e.g., metallicity), indicating that galaxy properties at high redshifts are highly sensitive to the feedback implementation of the simulation. Massive halos ( M halo ≥5 × 10 10 M ⊙ at z = 10) succeed in reproducing observed stellar masses, metallicities, and UV luminosities at 10 ≤ z ≤ 12 without requiring additional subgrid physics, but tend to underpredict those properties at higher redshift. We also find that varying the dust-to-metal ratio modestly affects UV luminosity of simulated galaxies, whereas the absence of dust significantly enhances it. In future work, higher-resolution simulations will be conducted to better understand the formation and evolution of galaxies at Cosmic Dawn.

Abstract Galaxy mergers have long been proposed as a mechanism for funneling gas toward galactic centres, potentially triggering accretion onto supermassive black holes (SMBHs) and igniting active galactic nuclei (AGN). While simulations often support this scenario, observational studies have yielded conflicting results regarding the AGN-merger connection. In this study, we analyze 31 galaxies from cosmological zoom-in simulations spanning redshifts 0.5 < z < 3. We identify mergers using detailed merger trees based on six-dimensional dark matter particle information and identify AGN activity through SMBH accretion histories. To bridge the gap between simulations and observations, we generate mock JWST-like images and extract non-parametric morphological parameters. Employing a k-nearest neighbours (KNN) classifier in a five-dimensional space (four morphological parameters and redshift), we identify mergers in the mock-observed dataset. Our analysis reveals a statistically significant enhancement of AGN activity in merging systems, particularly at lower redshifts (0.5 < z < 0.9), where central gas reservoirs are more depleted. This supports the view that mergers contribute more significantly to AGN triggering in environments with low internal gas reservoirs, while their impact may be less pronounced in gas-rich systems. However, when relying solely on morphological classifications from mock observations, the observed AGN-merger connection weakens, especially at higher redshifts. This underscores the challenges in detecting merger-induced AGN activity observationally and highlights the importance of combining simulations with realistic mock observations to fully understand the AGN-merger relationship.

We show that the first order theory of the homeomorphism group of a compact manifold interprets the full second order theory of countable groups of homeomorphisms of the manifold.The interpretation is uniform across manifolds of bounded dimension.As a consequence, many classical problems in group theory and geometry (e.g., the linearity of mapping classes of compact 2-manifolds) are encoded as elementary properties of homeomorphism groups of manifolds.Furthermore, the homeomorphism group uniformly interprets the Borel and projective hierarchies of the homeomorphism group, which gives a characterization of definable subsets of the homeomorphism group.Finally, we prove analogues of Rice's theorem from computability theory for homeomorphism groups of manifolds.As a consequence, it follows that the collection of sentences that isolate the homeomorphism group of a particular manifold, or that isolate the homeomorphism groups of manifolds in general, is not definable in second order arithmetic, and that membership of particular sentences in these collections cannot be proved in ZFC.

A bstract Orbifold CFTs contain twist operators that can join and split copies of the CFT. In this paper, we study the effects of four twist-2 operators on two copies of a single free boson. A recent study analyzed their effects on the vacuum, finding a nontrivial left-right mixing that arises from the fact that the covering surface is a torus, while the effects of one or two twist-2 operators do not produce such mixing. Here, we extend this analysis to excited states and find a similar left-right mixing. Furthermore, we explore the continuum, or high-energy, limit and show that the left-right mixing becomes negligible in this limit.

Accurate yet transferable machine-learning interatomic potentials are essential for accelerating materials and chemical discovery. However, many existing universal models are overfitted to narrow chemical spaces or computational protocols, limiting their reliability across diverse chemical and functional domains. Here, we introduce a transferable multi-domain training strategy that jointly optimizes parameters through selective regularization, coupled with a domain-bridging set that aligns potential-energy surfaces across datasets. Systematic ablation experiments show that suggested strategies synergistically enhance out-of-distribution generalization while preserving in-domain fidelity. Based on our observation, we train SevenNet-Omni on 15 open datasets spanning molecules, crystals, and surfaces. Our model achieves state-of-the-art accuracy in cross-domain benchmarks, reaching chemical accuracy in various scenarios including adsorption-energy in catalytic surfaces and metal-organic frameworks. SevenNet-Omni also accurately reproduces high-fidelity properties by effectively transferring knowledge learned from larger, lower-accuracy databases. This framework offers a scalable route toward universal, transferable models that bridge quantum-mechanical fidelities and chemical domains.

Background: Obesity is one of the most prevalent metabolic disorders worldwide, and its long-term management remains challenging due to the limited efficacy and adverse effects of current pharmacological treatments. Accordingly, there is growing interest in safe and effective anti-obesity strategies based on natural compounds. This study aimed to evaluate the anti-obesity effects of HT099, an extract derived from Prunus persica (peach blossom), and to investigate molecular changes associated with its metabolic effects in a high-fat diet (HFD)-induced obesity mouse model. Methods: Male C57BL/6N mice were fed an HFD and orally administered HT099 (50 or 100 mg/kg) or the positive control orlistat (40 mg/kg) for 12 weeks. Body weight, adipose tissue accumulation, food efficiency ratio, glucose tolerance, serum lipid profiles, and hepatic gene expression related to lipid metabolism were evaluated. Results: HT099 supplementation significantly attenuated body weight gain and reduced white adipose tissue accumulation while improving food efficiency ratio. HT099 also ameliorated HFD-induced glucose intolerance and favorably modulated serum lipid profiles, including reduced triglyceride levels, increased HDL-cholesterol levels, and improved non-HDL cholesterol indices. At the molecular level, HT099 administration was associated with an increased hepatic AMPKα1 mRNA expression and decreased expression of adipogenic and lipogenic genes, including C/EBPα, PPARγ, FAS, and SREBP-1c. Conclusions: These findings indicate that HT099 exerts anti-obesity effects in HFD-induced obese mice, accompanied by improvements in lipid and glucose metabolism and changes in adipogenesis- and lipogenesis-related gene expression. Collectively, the results support the potential of HT099 as a natural bioactive agent for obesity management.