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Hansol Kim

Publications and source records attributed to Hansol Kim.

At least 19 recordsLinked to original sources
arXiv2026

Uniform bounds on prime levels of abelian division fields of elliptic curves over number fields without rationally defined CM

Enrique Gonz\'alez-Jim\'enez and \'Alvaro Lozano-Robledo proved that there exists a uniform bound on the levels $n$ for which the $n$-division field $\mathbb{Q}\left(E\left[n\right]\right) / \mathbb{Q}$ of an elliptic curve $E/\mathbb{Q}$ defined over $\mathbb{Q}$ is abelian. Assuming GRH (Generalized Riemann Hypothesis), Allen and Genao partially generalized this result by restricting to prime levels while allowing arbitrary number fields without rationally defined CM. In this paper, we remove the GRH assumption and prove that the property established by Allen and Genao is in fact equivalent to the absence of rationally defined CM.

math.NT↗
arXiv2026

Telecom quantum memory over one microsecond in nanophotonic lithium niobate

Nanophotonic quantum memory is a vital component for scalable quantum information processing for quantum computing, networking, and sensing applications. We store single-photon-level telecom-band optical pulses for more than a microsecond using an atomic frequency comb in erbium-doped thin-film lithium niobate, well beyond what is practically feasible via propagation in even the best nanophotonic devices due to propagation losses. We verify the quantum nature of this storage by demonstrating the phase coherence and sub-single-photon noise upon retrieval. We also show the flexibility of our platform by storing up to 20 temporal modes and demonstrating an acceptance bandwidth up to 2.2 GHz. These results establish erbium-doped thin-film lithium niobate as a practical platform for on-chip quantum memory at telecom wavelengths, a key missing element for photonic quantum computing and quantum networking.

quant-ph↗
arXiv2026

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview

The 4th Workshop on Maritime Computer Vision (MaCVi) is organized as part of CVPR 2026. This edition features five benchmark challenges with emphasis on both predictive accuracy and embedded real-time feasibility. This report summarizes the MaCVi 2026 challenge setup, evaluation protocols, datasets, and benchmark tracks, and presents quantitative results, qualitative comparisons, and cross-challenge analyses of emerging method trends. We also include technical reports from top-performing teams to highlight practical design choices and lessons learned across the benchmark suite. Datasets, leaderboards, and challenge resources are available at https://macvi.org/workshop/cvpr26.

cs.CV↗
arXiv2026

Nonlinear Electro-Optic Visible Photonic Circuits for Solid-State Quantum Defects

Integrated visible photonic engines for solid-state quantum defects provide a foundation for scalable quantum networks. While miniaturization is advancing, active manipulation remains limited by the difficulty of achieving simultaneous milliwatt-scale visible light generation and high-contrast modulation. Despite extensive efforts, the concurrent chip-scale realization of nonlinear frequency conversion and fast temporal gating for high-fidelity quantum control has remained elusive. Here, we demonstrate a monolithic thin-film lithium niobate (TFLN) platform integrating periodically poled frequency conversion with GHz-bandwidth electro-optic (EO) switching. The device delivers off-chip green-light power exceeding 1 mW with an extinction ratio (ER) of 42.2 dB, enabling coherent spin control and time-resolved lifetime measurements of individual nitrogen-vacancy (NV) centers in diamond through nanosecond gating. System performance is validated through pulsed optically detected magnetic resonance (ODMR), Rabi oscillations, and Ramsey interference, supported by time-tagged photon counting with nanosecond resolution. By unifying sufficient nonlinear light generation with high-speed active manipulation, this platform establishes a scalable framework for the realization of high-rate quantum communication nodes.

physics.optics↗
arXiv2025

Stability of torsion subgroups of elliptic curves over non-Galois extensions of odd prime degree

Let $K$ be a field of characteristic $0$ and $E/K$ an elliptic curve over $K$. For a finite extension $L/K$ and a prime~$\ell$, we provide Galois-theoretic sufficient conditions on $L/K$ under which $E\left(L\right)\left[\ell^{\infty}\right] = E\left(K\right)\left[\ell^{\infty}\right]$. For a non-Galois extension $L/K$ of prime degree, we relate the growth of the $\ell^{\infty}$-torsion subgroup of $E$ under the base change $L/K$ to the image of the mod-$\ell$ cyclotomic character. In particular, In particular, we refine Gonz{\'a}lez-Jim{\'e}nez's result by ruling out certain torsion structures for quintic non-Galois extensions $L/\mathbb{Q}$.

math.NT↗
arXiv2025

Persode: Personalized Visual Journaling with Episodic Memory-Aware AI Agent

Reflective journaling often lacks personalization and fails to engage Generation Alpha and Z, who prefer visually immersive and fast-paced interactions over traditional text-heavy methods. Visual storytelling enhances emotional recall and offers an engaging way to process personal expe- riences. Designed with these digital-native generations in mind, this paper introduces Persode, a journaling system that integrates personalized onboarding, memory-aware conversational agents, and automated visual storytelling. Persode captures user demographics and stylistic preferences through a tailored onboarding process, ensuring outputs resonate with individual identities. Using a Retrieval-Augmented Generation (RAG) framework, it prioritizes emotionally significant memories to provide meaningful, context-rich interactions. Additionally, Persode dynamically transforms user experiences into visually engaging narratives by generating prompts for advanced text-to-image models, adapting characters, backgrounds, and styles to user preferences. By addressing the need for personalization, visual engagement, and responsiveness, Persode bridges the gap between traditional journaling and the evolving preferences of Gen Alpha and Z.

cs.HC↗
arXiv2025

Integrated bright source of polarization-entangled photons using lithium niobate photonic chips

Quantum photonics has rapidly advanced as a key area for developing quantum technologies by harnessing photons' inherent quantum characteristics, particularly entanglement. Generation of entangled photon pairs, known as Bell states, is crucial for quantum communications, precision sensing, and quantum computing. While bulk quantum optical setups have provided foundational progress, integrated quantum photonic platforms now offer superior scalability, efficiency, and integrative potential. In this study, we demonstrate a compact and bright source of polarization-entangled Bell state utilizing continuous-wave pumping on thin film lithium niobate (TFLN) integrated photonics. Our periodically poled lithium niobate device achieves on-chip brightness of photon pair generation rate of 508.5 MHz/mW, surpassing other integrated platforms including silicon photonics. This demonstration marks the first realization of polarization entanglement on TFLN platforms. Experimentally measured metrics confirm high-quality entangled photon pairs with a purity of 0.901, a concurrence of 0.9, and a fidelity of 0.944. We expect our compact quantum devices to have great potential for advancing quantum communication systems and photonic quantum technologies.

physics.optics↗
arXiv2025

The automorphism group of torsion points of an elliptic curve over a field of characteristic $\ge 5$

For a field $\mathbb{K}$ of characteristic $p\ge5$ containing $\mathbb{F}_{p}^{\operatorname{alg}}$ and the elliptic curve $E_{s,t}: y^{2} = x^{3} + sx + t$ defined over the function field $\mathbb{K}\left(s,t\right)$ of two variables $s$ and $t$, we prove that for a non-negative positive integer $e$ and a positive integer $N$ which is not divisible by $p$, the automorphism group of the normal extension $\mathbb{K}\left(s,t\right)\left(E_{s,t}\left[p^{e} N\right]\right)$ over $\mathbb{K}\left(s,t\right)$ is isomorphic to $\left(\mathbb{Z}/p^{e}\mathbb{Z}\right)^{\times} \times \operatorname{SL}_{2} \left(\mathbb{Z}/N\mathbb{Z}\right)$.

math.NT↗
arXiv2025

Photoinduced dc Hall current in few-layer black phosphorus with a gate-tunable Floquet gap

We theoretically explore Floquet engineering in few-layer black phosphorus (fBP) under time-periodic driving. Motivated by the ability of circularly polarized light to induce nontrivial topological states at Dirac nodes, we investigate the emergence of a photoinduced dc Hall effect in the Dirac semimetal phase of fBP. Starting from a low-energy continuum model, we derive the effective Floquet Hamiltonian and analytically calculate the Berry curvature, demonstrating the opening of a topological gap. We also perform lattice-model calculations incorporating a self-consistent Hartree method to compute Floquet band structures and dc Hall conductivity under a perpendicular electric field. Our results reveal that the dc Hall current in fBP can be effectively tuned via a periodic driving field and electrostatic gating.

cond-mat.mes-hall↗
arXiv2024

Implementation of Magic State Injection within Heavy-Hexagon Architecture

The magic state injection process is a critical component of fault-tolerant quantum computing, and numerous studies have been conducted on this topic. Many existing studies have focused on square-lattice structures, where each qubit connects directly to four other qubits via two-qubit gates. However, hardware that does not follow a lattice structure, such as IBM's heavy-hexagon structure, is also under development. In these non-lattice structures, many quantum error correction (QEC) codes designed for lattice-based system cannot be directly applied. Adapting these codes often requires incorporating additional qubits, such as flag qubits. This alters the properties of the QEC code and introduces new variables into the magic state injection process. In this study, we implemented and compared the magic state injection process on a heavy-hexagon structure with flag qubits and a lattice structure without flag qubits. Additionally, we considered biased errors in superconducting hardware and investigated the impact of flag qubits under these conditions. Our analysis reveals that the inclusion of flag qubits introduces distinct characteristics into the magic state injection process, which are absent in systems without flag qubits. Based on these findings, we identify several critical considerations for performing magic state injection on heavy-hexagon systems incorporating flag qubits. Furthermore, we propose an optimized approach to maximize the efficacy of this process in such systems.

quant-ph↗
arXiv2024

The automorphism group of the $p^{n}$-torsion points of an elliptic curve over a field of characteristic $p \ge 5$

For a field $K$ of characteristic $p\ge5$ and the elliptic curve $E_{s,t}: y^{2} = x^{3} + sx + t$ defined over the function field $K\left(s,t\right)$ of two variables $s$ and $t$, we prove that for a positive integer $n$, the automorphism group of the normal extension $K\left(s,t\right)\left(E_{s,t}\left[p^{n}\right]\right)/K\left(s,t\right)$ is isomorphic to $\left(\mathbb{Z}/p^{n}\mathbb{Z}\right)^{\times}$, and its inseparable degree is $p^{n}$.

math.NT↗
arXiv2024

Federated Learning for Face Recognition via Intra-subject Self-supervised Learning

Federated Learning (FL) for face recognition aggregates locally optimized models from individual clients to construct a generalized face recognition model. However, previous studies present two major challenges: insufficient incorporation of self-supervised learning and the necessity for clients to accommodate multiple subjects. To tackle these limitations, we propose FedFS (Federated Learning for personalized Face recognition via intra-subject Self-supervised learning framework), a novel federated learning architecture tailored to train personalized face recognition models without imposing subjects. Our proposed FedFS comprises two crucial components that leverage aggregated features of the local and global models to cooperate with representations of an off-the-shelf model. These components are (1) adaptive soft label construction, utilizing dot product operations to reformat labels within intra-instances, and (2) intra-subject self-supervised learning, employing cosine similarity operations to strengthen robust intra-subject representations. Additionally, we introduce a regularization loss to prevent overfitting and ensure the stability of the optimized model. To assess the effectiveness of FedFS, we conduct comprehensive experiments on the DigiFace-1M and VGGFace datasets, demonstrating superior performance compared to previous methods.

cs.CV↗
arXiv2024

Effectiveness of the syndrome extraction circuit with flag qubits on IBM quantum hardware

Large scale quantum circuits are required to exploit the advantages of quantum computers. Despite significant advancements in quantum hardware, scalability remains a challenge, with errors accumulating as more qubits and gates are added. To overcome this limitation, quantum error-correction codes have been introduced. Although the success of quantum error correction codes has been demonstrated on superconducting quantum processors and neutral atom-based systems, there have been no experimental reports of error suppression using flag qubits on a quantum processor. IBM's quantum hardware features a non-topological coupling map, and past developments of quantum error correction codes on this platform have primarily explored the use of flag qubits. Here, we report the successful implementation of a syndrome extraction circuit with flag qubits on IBM quantum computers. Moreover, we demonstrate its effectiveness by considering the repetition code as a test code among the quantum error-correcting codes. Even though the data qubit is not adjacent to the syndrome qubit, logical error rates diminish as the distance of the repetition code increases from three to nine. Even when two flag qubits exist between the data and syndrome qubits, the logical error rates decrease as the distance increases similarly. This confirms the successful implementation of the syndrome extraction circuit with flag qubits on the IBM quantum computer.

quant-ph↗
arXiv2023

Growth of Torsion Groups of Elliptic Curves Over Number Fields without Rationally Defined CM

For a quadratic field $\mathcal{K}$ without rationally defined CM, we prove that there exists of a prime $p_{\mathcal{K}}$ depending only on $\mathcal{K}$ such that if $d$ is a positive integer whose minimal prime divisor is greater than $p_{\mathcal{K}}$, then for any extension $L/\mathcal{K}$ of degree d and any elliptic curve $E/\mathcal{K}$, we have $E\left(L\right)_{\operatorname{tors}} = E\left(\mathcal{K}\right)_{\operatorname{tors}}$. By not assuming the GRH, this is a generalization of the results by Genao, and Gonález-Jiménez and Najman.

math.NT↗
arXiv2023

ProtoFL: Unsupervised Federated Learning via Prototypical Distillation

Federated learning (FL) is a promising approach for enhancing data privacy preservation, particularly for authentication systems. However, limited round communications, scarce representation, and scalability pose significant challenges to its deployment, hindering its full potential. In this paper, we propose 'ProtoFL', Prototypical Representation Distillation based unsupervised Federated Learning to enhance the representation power of a global model and reduce round communication costs. Additionally, we introduce a local one-class classifier based on normalizing flows to improve performance with limited data. Our study represents the first investigation of using FL to improve one-class classification performance. We conduct extensive experiments on five widely used benchmarks, namely MNIST, CIFAR-10, CIFAR-100, ImageNet-30, and Keystroke-Dynamics, to demonstrate the superior performance of our proposed framework over previous methods in the literature.

cs.CV↗
arXiv2022

Over-the-Air Consensus for Distributed Vehicle Platooning Control (Extended version)

A distributed control of vehicle platooning is referred to as distributed consensus (DC) since many autonomous vehicles (AVs) reach a consensus to move as one body with the same velocity and inter-distance. For DC control to be stable, other AVs' real-time position information should be inputted to each AV's controller via vehicle-to-vehicle (V2V) communications. On the other hand, too many V2V links should be simultaneously established and frequently retrained, causing frequent packet loss and longer communication latency. We propose a novel DC algorithm called over-the-air consensus (AirCons), a joint communication-and-control design with two key features to overcome the above limitations. First, exploiting a wireless signal's superposition and broadcasting properties renders all AVs' signals to converge to a specific value proportional to participating AVs' average position without individual V2V channel information. Second, the estimated average position is used to control each AV's dynamics instead of each AV's individual position. Through analytic and numerical studies, the effectiveness of the proposed AirCons designed on the state-of-the-art New Radio architecture is verified by showing a $14.22\%$ control gain compared to the benchmark without the average position.

cs.IT↗
arXiv2022

Density of Elliptic Curves over Number Fields with Prescribed Torsion Subgroups

Let $K$ be a number field. For positive integers $m$ and $n$ such that $m\mid n$, we let $\mathscr{S}_{m,n}$ be the set of elliptic curves $E/K$ defined over $K$ such that $E(K)_{\operatorname{tors}}\supseteq \mathscr{T}\cong \mathbb{Z}/m\mathbb{Z}\times \mathbb{Z}/n\mathbb{Z}$. We prove that if the genus of the modular curve $X_{1}(m,n)$ is $0$, then `almost all' $E\in \mathscr{S}_{m,n}$ satisfy that $E(K)_{\operatorname{tors}}= \mathscr{T}$, i.e., not larger than $\mathscr{T}$. In particular, if $m=n=1$, this result generalizes Duke's theorem over $\mathbb{Q}$ to arbitrary number fields $K$ for the trivial torsion subgroup.

math.NT↗