[2602.00185] QUASAR: A Universal Autonomous System for Atomistic Simulation and a Benchmark of Its Capabilities

Condensed Matter > Materials Science arXiv:2602.00185 (cond-mat) [Submitted on 30 Jan 2026 (v1), last revised 7 Apr 2026 (this version, v2)] Title:QUASAR: A Universal Autonomous System for Atomistic Simulation and a Benchmark of Its Capabilities Authors:Fengxu Yang, Jack D. Evans View a PDF of the paper titled QUASAR: A Universal Autonomous System for Atomistic Simulation and a Benchmark of Its Capabilities, by Fengxu Yang and Jack D. Evans View PDF HTML (experimental) Abstract:The integration of large language models (LLMs) into materials science offers a transformative opportunity to streamline computational workflows, yet current agentic systems remain constrained by rigid, carefully crafted domain-specific tool-calling paradigms and narrowly scoped agents. In this work, we introduce QUASAR, a universal autonomous system for atomistic simulation designed to facilitate production-grade scientific discovery. QUASAR autonomously orchestrates complex multi-scale workflows across diverse methods, including density functional theory, machine learning potentials, molecular dynamics, and Monte Carlo simulations. The system incorporates robust mechanisms for adaptive planning, context-efficient memory management, and hybrid knowledge retrieval to navigate real-world research scenarios without human intervention. We benchmark QUASAR against a series of three-tiered tasks, progressing from routine tasks to frontier research challenges such as photocatalyst screening and novel mate...