9 papers
Agent-E2MD: Autonomous Translation of Interatomic Potential Equations into Physically Validated Pair Styles for Molecular Dynamics in LAMMPS
Bilvin Varughese, Orcun Yildiz, Aditya Koneru +3
Interatomic potentials underpin MD and govern predictive atomistic-model fidelity for metals, semiconductors, oxides, liquids, and reactive systems. A potential has limited practic…
Symbolic Ensemble Learning Enables Discovery of Fast Accurate Physics-Based Interatomic Potentials
Bilvin Varughese, Aditya Koneru, Adil Muhammad +6
Machine learning has transformed materials simulation by delivering force fields with ab initio accuracy, yet bridging the gap between high-dimensional regression and physical inte…
COMPASS: Steering Distributed Vector Search with Scientific Knowledge Graphs
Song Young Oh, Amal Gueroudji, Seth Ockerman +5
Vector databases use hashing to partition data across "shards," logical units for distributed execution. This placement, however, destroys semantic locality, forcing each query int…
Physics-Informed Tree Search for High-Dimensional Computational Design
Suvo Banik, Troy D. Loeffler, Henry Chan +4
High-dimensional design spaces underpin a wide range of physics-based modeling and computational design tasks in science and engineering. These problems are commonly formulated as…
Physically Interpretable Interatomic Potentials via Symbolic Regression and Reinforcement Learning
Bilvin Varughese, Troy D. Loeffler, Suvo Banik +9
The development of next-generation molecular simulation models requires moving beyond pre-defined functional forms toward machine learning (ML) techniques that directly capture mul…
ChatVis: Large Language Model Agent for Generating Scientific Visualizations
Tom Peterka, Tanwi Mallick, Orcun Yildiz +3
Large language models (LLMs) are rapidly increasing in capability, but they still struggle with highly specialized programming tasks such as scientific visualization. We present an…
Do Large Language Models Speak Scientific Workflows?
Orcun Yildiz, Tom Peterka
With the advent of large language models (LLMs), there is a growing interest in applying LLMs to scientific tasks. In this work, we conduct an experimental study to explore applica…
ChatVis: Automating Scientific Visualization with a Large Language Model
Tanwi Mallick, Orcun Yildiz, David Lenz +1
We develop an iterative assistant we call ChatVis that can synthetically generate Python scripts for data analysis and visualization using a large language model (LLM). The assista…
Wilkins: HPC In Situ Workflows Made Easy
Orcun Yildiz, Dmitriy Morozov, Arnur Nigmetov +2
In situ approaches can accelerate the pace of scientific discoveries by allowing scientists to perform data analysis at simulation time. Current in situ workflow systems, however,…