Particle Physics, Quantum Information And Machine Learning

13 Jul 2026, 09:00 → 17 Jul 2026, 18:15 Asia/Seoul

IBS Theory Building 4th floor, CTPU common seminar room

PARTIQAL 2026 brings together researchers working at the intersection of particle physics, quantum information science, and machine learning.

The goal is to explore how emerging quantum technologies and AI methods can advance both theoretical and experimental high-energy physics.

The workshop will focus on the following topics:

• Recent developments in Machine Learning 

• Quantum algorithms and Quantum Computation

• Quantum machine learning
  

• Quantum Information, especially Quantum observables.

• Quantum sensing and quantum-enhanced measurements
  
  

The workshop will be organized in two parts: the first focusing on machine learning and quantum machine learning for particle physics, and the second exploring quantum observables and quantum sensing as emerging tools for fundamental physics.

Invited speakers:

• Jack Y. Araz (City St. George’s, University of London)
• Joonwoo Bae (KAIST)
• Jeongho Bang (Yonsei U.)
• Jae Hyeok Chang (SNU)
• Hajime Fukuda (U. Tokyo)
• Dongwook Ghim (IBS)
• Aishik Ghosh (Georgia Tech) 
• Dorival Gonçalves (Oklahoma U.)

• Ahmed Hammad (KIAS AI)

• Tae-Geun Kim (RIKEN and Fudan U.)
• Yeoneung Kim (SeoulTech)
• Changhyoup Lee (Hanyang U.)
• Paul Junghyun Lee (KIST)
• Ying-Ying Li (IHEP)
• Yung-Kyun Noh (Hanyang U.)
• Bin Xu (KIAS)
• Shinjae Yoo  (BNL) : ONLINE
• Sangwoong Yoon (UNIST)
• Sungwoo Youn (IBS DMAG)
• Kwangmin Yu (BNL)

 

Organizers:
KC Kong (University of Kansas) 
Myeonghun Park (SeoulTech)

This workshop is supported by SeoulTech and  APCTP. The venue is hosted by IBS.

The APCTP is supported by the Korean Government through the Science and Technology Promotion Fund and Lottery Fund and strives to maximize public value through its various activities.

Monday 13 July

10:30 → 10:40 Coffee and Registration

10:40 → 10:50 Opening

Speaker: Myeonghun Park

welcome.pdf

10:50 → 11:50 Unlocking Physics in High Dimensions from Small-Sample Data (chair: Myeonghun Park)

Speaker: Aishik Ghosh (Georgia Institute of Technology)

PARTIQAL_13July2026.pdf

11:50 → 14:00 Lunch and Discussion

14:00 → 15:00 Transformers for collider analyses (chair: Yung-Kyun Noh)

Speaker: Ahmed Hammad (KEK, Japan)

Transformers_Hammad.pdf

15:00 → 15:30 Evaluator-guided routing mechanics in modular neural networks (chair: Yung-Kyun Noh)

Speaker: Mr Sungjung Kim (SNU)

15:30 → 16:00 Coffee and Discussion

16:00 → 17:00 A physics-informed, global-in-time neural particle method for the spatially homogeneous Landau equation (chair: Aishik Ghosh)

We propose a physics-informed neural particle method (PINN-PM) for the spatially homogeneous Landau equation. The method adopts a Lagrangian interacting-particle formulation and jointly parameterizes the time-dependent score and the characteristic flow map with neural networks. Instead of advancing particles through explicit time stepping, the Landau dynamics is enforced via a continuous-time residual defined along particle trajectories, yielding a mesh-free solver that can be queried at arbitrary times. We establish a deterministic, global-in-time stability analysis in an $L^2_v$ framework. The deviation between learned and exact characteristics is controlled by three interpretable sources: the score approximation error, the particle approximation error, and the physics residual of the neural flow. This trajectory estimate is then lifted to Wasserstein stability and density reconstruction error via kernel density estimation, resulting in a complete error propagation chain from particle dynamics to macroscopic quantities. At the oracle level, the score error is characterized through the implicit score matching functional via Hyv\"arinen's identity. In practice, the empirical ISM objective provides a computable surrogate for monitoring score accuracy during training. Numerical experiments on analytical benchmarks, including the two- and three-dimensional BKW solutions, as well as reference-free configurations, demonstrate stable transport, preservation of macroscopic invariants, and competitive or improved accuracy compared with time-stepping particle methods while using significantly fewer particles.

Speaker: Prof. Yeoneung Kim (SeoulTech)

yeoneung_slide.pdf

17:00 → 18:00 Diffusion Models and Thermodynamic Singularity (chair: Aishik Ghosh)

Speaker: Yung-Kyun Noh (Hanyang University / KIAS)

2026_07_Diffusion_PARTIQAL_noh.pdf

Tuesday 14 July

09:30 → 10:30 FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics (chair: Ahmed Hammad)

Speaker: Shinjae Yoo (Brookhaven National Laboratory)

SYoo_PARTIQAL_60min_FM4NPP_v1.pdf

10:30 → 10:50 Coffee and Discussion

10:50 → 11:50 Neural Inverse Problems and Degeneracy: SMEFT and Primordial Black Holes (chair: Ahmed Hammad)

Speaker: Tae-Geun Kim (Fudan U. / RIKEN)

PARTIQAL_tgkim.pdf

11:50 → 14:00 Lunch and Discussion

14:00 → 15:00 Distribution-free uncertainty quantification for ML in HEP (chair: Sunghoon Jung)

Speaker: Jack Araz

jackaraz_ibs_ai.pdf

15:00 → 15:30 DLScanner and LeStrat-Net: Machine learning for improved Monte Carlo exploration (chair: Sunghoon Jung)

Speaker: Raymundo Ramos (Korea Institute for Advanced Study)

Ramos_PARTIQAL2026.pdf

15:30 → 16:00 Coffee and Discussion

16:00 → 17:00 Value Gradient Sampler: Learning Invariant Value Functions for Equivariant Diffusion Sampling (chair: Yeoneung Kim)

Speaker: Sangwoong Yoon (Ulsan National Institute of Science and Technology)

윤상웅_genreative_model_reinforcement_learning_pdf.pdf

17:00 → 17:30 Patching solutions with machine learning (chair: Yeoneung Kim)

Speaker: Dr Jiheon Lee (KIAS)

partiqal_JL.pdf

Wednesday 15 July

09:30 → 10:30 Practical and Efficient Verification of Entanglement with Incomplete Measurement Settings (chair: Dong Woo Kang)

Speaker: Joonwoo Bae (KAIST)

202607 PARTICAL rev.pdf

10:30 → 10:50 Coffee and Discussion

10:50 → 11:50 Neural Causal Information: A Capacity Principle for Query-Separated Representations (chair: Dong Woo Kang)

Speaker: Prof. Jeongho Bang (Yonsei University)

11:50 → 14:00 Lunch and Discussion

14:00 → 14:30 Tripartite Entanglement in e+e- -> t t Z (chair: Joonwoo Bae)

Speaker: Alberto Navarro (Seoultech)

PARTIQAL_Alberto.pdf

14:30 → 15:00 Spin density matrix and Quantum Observables of a two-qubit system at Colliders (chair: Joonwoo Bae)

Speaker: Dong Woo Kang (Jeonbuk National University)

PARTIQAL_DWK.pdf

15:00 → 18:00 Coffee and Discussion

18:00 → 21:00 Workshop Banquet

Thursday 16 July

09:30 → 10:30 Data-Driven Quantum State Tomography: A Diffusion Model Approach for Noisy Quantum Hardware (chair: Jack Araz)

Speaker: Prof. Changhyoup Lee (Hanyang University)

10:30 → 10:50 Coffee and Discussion

10:50 → 11:50 Quantum Information Meets Collider Physics (chair: Jack Araz)

Speaker: Dorival Goncalves (Oklahoma State University)

Dorival_IBS_2026.pdf

11:50 → 13:30 Lunch and Discussion

13:30 → 14:30 Exponentially improved quantum simulation of scalar QFT (chair: Myeonghun Park)

Speaker: Prof. Yingying Li (IHEP)

14:30 → 15:30 Digital Quantum Simulation for the Spectroscopy of Schwinger Model (chair: Myeonghun Park)

Speaker: Dongwook Ghim (IBS CTPU-PTC)

2026.07.16.IBS_PARTIQAL_Schwinger-edit.pdf

15:30 → 16:00 Coffee and Discussion

16:00 → 17:00 Leveraging Quantum hardware for Fundamental Physics (chair: Yingying Li)

Speaker: Jack Araz (UCL & City St George's, UoL)

jackaraz_ibs_quantum.pdf

17:00 → 18:00 Quantum Utility on Noisy Near-Term Quantum Computers (chair: Yingying Li)

Speaker: Kwangmin Yu (Brookhaven National Laboratory)

QU_NTQC_PARTIQAL_20260716.pdf

Friday 17 July

09:30 → 10:30 Theory Targets for Dark Matter Experiments: The Case of Magnetic Dipole Dark Matter (chair: Dorival Goncalves)

Speaker: Jae Hyeok Chang

10:30 → 10:50 Coffee and Break

10:50 → 11:50 Quantum Error Correction for Noise Mitigation in Wave-like Dark Matter Search (chair: Dorival Goncalves)

Speaker: Hajime Fukuda (University of Tokyo)

11:50 → 13:30 Lunch and Discussion

13:30 → 14:30 Solid-state defect based quantum sensing : from basics to dark matter detection (chair: Myeonghun Park)

Quantum metrology based on solid-state color centers has advanced significantly through the development of robust sensing protocols, including Ramsey interferometry, Hahn echo, and dynamical decoupling sequences. Color center qubits are particularly promising platforms for quantum sensing due to their ability to operate under a wide range of conditions, from vacuum to ambient environments and from cryogenic to room temperatures, depending on the application. In this talk, I will introduce the fundamental principles of quantum metrology using solid-state color centers, with a particular focus on defect qubits in diamond. I will then discuss recent efforts to achieve quantum-enhanced sensing by exploiting quantum correlations among defect qubits. Finally, I will highlight emerging applications of color center qubits in particle physics, including the search for axion dark matter, and present ongoing experimental efforts in this direction.

Speaker: Dr Paul Junghyun Lee (KIST)

14:30 → 15:30 Quantum Probes of Axion Dark Matter (chair: Myeonghun Park)

Speaker: SungWoo Youn (IBS-DMAG)

15:30 → 16:00 Coffee and Break

16:00 → 17:00 Quantum metrology for wavelike dark matter (chair: Hajime Fukuda)

Speaker: Bin Xu (Korea Institute for Advanced Study)

17:00 → 17:30 Quantum Sensing for High-Frequency Gravitational Wave (chair: Hajime Fukuda)

Speaker: Mr Heechan Yi (Yonsei University)

17:30 → 17:40 Closing

Speaker: Myeonghun Park