A3D3 Affiliates Present at the 22nd International Workshop on Advanced Computing and Analysis Techniques in Physics Research

By: Yuan-Tang Chou

Grace Williams

April 2, 2024

The 22nd International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2024) is an exciting workshop held every 18 months. It brings together computational experts from around the world who work in diverse fields of physics, like particle and astrophysics, to discuss advanced technology with the potential to enhance research in physics.. 

This year’s theme is “Foundation Models for Physics—Nexus of Computation and Physics through Embracing the Era of Foundation Models.” Our researchers, Vladimir Loncar and Javier Duarte, chaired two of the exciting sessions. 

Below, we highlight some of the many of the exciting contributions from A3D3 members that were presented during the week-long workshop.


On Monday afternoon, Zihan Zhao (A3D3 Grad student) presented his work on Self-supervised Learning for Jet Tagging,”  demonstrating the potential of self-supervised learning to utilize real, unlabeled data for more efficient and accurate jet classification. 

Zihan Zhao presenting at ACAT 2024


Researcher Javier Duarte and steering board member Nhan Tran (Fermilab Wilson Fellow) chaired Tracks Two: Data Analysis – Algorithms and Tools which discussed advanced ML algorithms for physics object reconstruction in the particle experiment. 

Nhan also gave a plenary on Tuesday about “AI and Microelectronics for Science.”

Wahid Bhimji, A3D3 steering board, presented “Fair Universe: HiggsML Uncertainty Challenge” which brings FAIRness to the ML community, and also convened the plenary on Thursday. 

Pic: Wahid Bhimji Convened plenary 

In the afternoon session at the “Towards the Construction of Foundational Models at the LHC” talk given by Phil Harris (A3D3 deputy director), he presented recent work that proposed novel Self-Supervised Learning Strategies. The method constructs a space that preserves discrimination power and reduces the impact of systematic uncertainties. 

Xiangyang Ju (LBNL computing system engineer, A3D3 affiliated member) talked about a novel idea to use a large language model to perform particle tracking in his “Leveraging Language Models for Particle Reconstruction.”   

Xiangyang Ju presents on the use of large language models in particle tracking


On Thursday morning, Aobo Li (UCSD Professor) gave a plenary talk about “Detecting Rare Events Using Artificial Intelligence.” He proposed a unified multimodal foundation model for all rare event search experiments.

 “This could forge the experiments like a union,” Aobo said.

Aobo Li gives his presentation on “Detecting Rare Events Using Artificial Intelligence”

In the afternoon, Yuan-Tang Chou (A3D3 Postdoc) presented “ACTS as a Service” and demonstrated how to utilize heterogeneous computing resources better to accelerate track reconstruction using the Triton GPU Inferences server.

“We’re proposing this idea to better utilized heterogeneous computing systems to accelerate the track reconstructions in ACTS. I think people are quite interested in how this can actually apply in the current production framework.”

-Yuan-Tang Chou