arXiv subjects

Bomin Kim

Publications and source records attributed to Bomin Kim.

5 recordsLinked to original sources

arXiv2025

Chiral quantum magnets with optically and catalytically active spin ladders

Chiral quantum magnets with spin-states separated by a large energy gap are technologically attractive but difficult to realize. Geometrically frustrated topological states with nanoscale chirality may offer a chemical pathway to such materials. However, room temperature spin misalignment, weakness of Dzyaloshinskii-Moriya interactions, and high energy requirements for lattice distortions set high physicochemical barriers for their realization. Here, we show that layered iron oxyhydroxides (LIOX) address these challenges due to chirality transfer from surface ligands into spin-states of dimerized FeO6 octahedra with zig-zag stacking. The intercalation of chiral amino acids induces angular displacements in the antiferromagnetic spin pairs with a helical coupling of magnetic moments along the screw axis of the zig-zag chains, or helical spin-ladders. Unlike other chiral magnets, the spin states in LIOX are chemically and optically accessible, they display strong optical resonances with helicity-matching photons and enable spin-selective charge transport. The static rather than dynamic polarization of spin ladders in LIOX makes them particularly suitable for catalysis. Room-temperature spin pairing, field-tunability, environmental robustness, and synthetic simplicity make LIOX and its intercalates a uniquely practical family of quantum magnets.

cond-mat.mtrl-sci↗

arXiv2025

Why Fe$_3$GaTe$_2$ has higher Curie temperature than Fe$_3$GeTe$_2$?

Physics of Fe$_3$GaTe$_2$ having higher Curie temperature ($T_C$) than Fe$_3$GeTe$_2$ is explored theoretically in the framework of magnetic exchange interactions. Fe$_3$GaTe$_2$ and Fe$_3$GeTe$_2$ are isostructural, with Fe$_3$GaTe$_2$ having one less valence electron and smaller nearest-neighbor exchange coefficients ($J_1$ and $J_2$), challenging the conventional notion that larger $J_1$ or $J_2$ leads to a higher $T_C$. We show that higher order exchange coefficients, $J_3$ or higher, of Fe$_3$GaTe$_2$ are positive whereas those of Fe$_3$GeTe$_2$ are negative. As a consequence, total sum of all possible exchange coefficients in Fe$_3$GaTe$_2$ are larger than Fe$_3$GeTe$_2$, which accounts for higher $T_C$. To validate these findings, $T_C$ are computed using both mean-field theory and Monte Carlo simulation. Indeed, higher-order exchange interactions, when properly accounting for the number of neighbors, confirm the higher $T_C$ of Fe$_3$GaTe$_2$.

cond-mat.mtrl-sci↗

arXiv2023

A Dynamic Additive and Multiplicative Effects Model with Application to the United Nations Voting Behaviors

Motivated by a study of United Nations voting behaviors, we introduce a regression model for a series of networks that are correlated over time. Our model is a dynamic extension of the additive and multiplicative effects network model (AMEN) of Hoff (2019). In addition to incorporating a temporal structure, the model accommodates two types of missing data thus allows the size of the network to vary over time. We demonstrate via simulations the necessity of various components of the model. We apply the model to the United Nations General Assembly voting data from 1983 to 2014 (Voeten (2013)) to answer interesting research questions regarding international voting behaviors. In addition to finding important factors that could explain the voting behaviors, the model-estimated additive effects, multiplicative effects, and their movements reveal meaningful foreign policy positions and alliances of various countries.

stat.AP↗

arXiv2018

The Hyperedge Event Model

We introduce the hyperedge event model (HEM)---a generative model for events that can be represented as directed edges with one sender and one or more receivers or one receiver and one or more senders. We integrate a dynamic version of the exponential random graph model (ERGM) of edge structure with a survival model for event timing to jointly understand who interacts with whom, and when. The HEM offers three innovations with respect to the literature---first, it extends a growing class of dynamic network models to model hyperedges. The current state-of-the-art approach to dealing with hyperedges is to inappropriately break them into separate edges/events. Second, our model involves a novel receiver selection distribution that is based on established edge formation models, but assures non-empty receiver lists. Third, the HEM integrates separate, but interacting, equations governing edge formation and event timing. We use the HEM to analyze emails sent among department managers in Montgomery County government in North Carolina. Our application demonstrates that the model is effective at predicting and explaining time-stamped network data involving edges with multiple receivers. We present an out-of-sample prediction experiment to illustrate how researchers can select between different specifications of the model.

stat.ME↗

arXiv2018

A Review of Dynamic Network Models with Latent Variables

We present a selective review of statistical modeling of dynamic networks. We focus on models with latent variables, specifically, the latent space models and the latent class models (or stochastic blockmodels), which investigate both the observed features and the unobserved structure of networks. We begin with an overview of the static models, and then we introduce the dynamic extensions. For each dynamic model, we also discuss its applications that have been studied in the literature, with the data source listed in Appendix. Based on the review, we summarize a list of open problems and challenges in dynamic network modeling with latent variables.

stat.ME↗