Tae-Geun Kim
Postdoctoral Researcher
Key Laboratory of Nuclear Physics and Ion-beam Application (MOE), Fudan University
RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS)
Dark matter phenomenology, AI for Science, and Science of AI
GitHub Scholar ORCID CV LinkedIn Email
6
Publications
27
Software
4
Posts
Recent Publications
Primordial Black Holes as a Factory of Axions: Extragalactic Photons from Axions
2026
Prog. Theor. Exp. Phys.
Tae-Geun Kim, Jong-Chul Park, Seong Chan Park, Yeji Park
Dark MatterPBHAxion
Abstract: We investigate the extragalactic photon signals produced by axion-like particles emitted from primordial black holes via Hawking radiation.
@article{kim2023primordial, title={Primordial Black Holes as a Factory of Axions: Extragalactic Photons from Axions}, author={Kim, Tae-Geun and Park, Jong-Chul and Park, Seong Chan and Park, Yeji}, journal={Progress of Theoretical and Experimental Physics}, pages={ptag011}, year={2026}, doi={10.1093/ptep/ptag011} }
DOI arXiv
Learning Hamiltonian Dynamics with Bayesian Data Assimilation
2025
arXiv preprint
Taehyeun Kim, Tae-Geun Kim, Anouk Girard, Ilya Kolmanovsky
Machine LearningHamiltonianBayesian
Abstract: We propose a framework combining Hamiltonian neural networks with Bayesian data assimilation for learning dynamical systems.
@article{kim2025learning, title={Learning Hamiltonian Dynamics with Bayesian Data Assimilation}, author={Kim, Taehyeun and Kim, Tae-Geun and Girard, Anouk and Kolmanovsky, Ilya}, journal={arXiv preprint arXiv:2501.18808}, year={2025} }
arXiv
Neural Hamilton: Can A.I. Understand Hamiltonian Mechanics?
2024
arXiv preprint
Tae-Geun Kim, Seong Chan Park
Machine LearningOperator LearningHamiltonian
Abstract: We investigate whether neural network architectures can learn Hamiltonian dynamics directly from the Hamiltonian function using operator learning.
@article{kim2024neural, title={Neural Hamilton: Can A.I. Understand Hamiltonian Mechanics?}, author={Kim, Tae-Geun and Park, Seong Chan}, journal={arXiv preprint arXiv:2410.20951}, year={2024} }
arXiv Code
Featured Software
Peroxide
Comprehensive Rust numerical computing library
Rust ★ 681 ↧ 1.1M
NumericLinear AlgebraStatisticsODE
Comprehensive numerical computing library for Rust, providing functionality comparable to NumPy/SciPy. Core infrastructure for scientific computing research.
  • Linear algebra with BLAS/LAPACK integration
  • Optimization algorithms (Gradient Descent, Levenberg-Marquardt)
  • Numerical integration & ODE/PDE solvers
  • Statistical distributions & special functions
  • DataFrame with multiple I/O formats
GitHub Docs
Neural Hamilton
Operator learning for Hamiltonian mechanics
Python ★ 14
Operator LearningHamiltonianNeural ODE
Official implementation of operator learning for Hamiltonian mechanics. Explores whether AI can truly understand physical dynamics.
  • Four neural architectures (DeepONet, TraONet, VaRONet, MambONet)
  • Novel potential generation via Gaussian Random Fields
  • Multi-language (Python, Rust, Julia)
GitHub
Puruspe
Pure Rust special functions library
Rust ★ 26 ↧ 1.0M
Special FunctionsMathematics
Pure Rust implementation of mathematical special functions for scientific computing.
  • Gamma, Beta, Error functions
  • Regularized and inverse variants
  • No external dependencies
GitHub Docs