arXiv:2512.03476v3 Announce Type: replace 
Abstract: Progress in computational science depends on complex numerical workflows that must faithfully encode physical laws, yet translating conceptual insight into reliable code remains a major bottleneck. Although large language models can generate isolated code fragments, they lack the structured reasoning required to design, verify, and iteratively refine complete scientific pipelines. Here we introduce ATHENA, an agentic framework explicitly designed to emulate scientific research modeled as a knowledge-driven contextual bandit process. Its core loop separates conceptual policy from numerical realization through expert-derived conceptual scaffolding, enabling principled diagnosis, reformulation, and repair of computational strategies. Across scientific computing and scientific machine learning tasks, ATHENA autonomously derives and correctly applies exact analytical solutions, constructs stable numerical solvers, diagnoses ill-posed formulations, and orchestrates hybrid symbolic-numeric workflows. Quantitatively, ATHENA matches and frequently surpasses the accuracy of expert-authored reference solutions reported in the literature on canonical benchmarks. By reframing computation as an object of agentic reasoning, our framework enables autonomous orchestration of heterogeneous algorithms across scientific domains.

تم تقديم ATHENA، وهو إطار عمل وكيل مبتكر، لتحسين العلوم الحاسوبية من خلال محاكاة البحث العلمي كعملية لصوص سياقية مدفوعة بالمعرفة. يهدف هذا الإطار إلى معالجة التحديات المتعلقة بترجمة الأفكار المفاهيمية إلى كود موثوق، وهو ما كان عقبة رئيسية في هذا المجال.

ATHENA, un innovador marco agentico, ha sido presentado para mejorar la ciencia computacional al emular la investigación científica como un proceso de bandido contextual impulsado por el conocimiento. Este marco busca abordar los desafíos de traducir ideas conceptuales en código confiable, que ha sido un importante obstáculo en el campo.

ATHENA, un cadre agentique innovant, a été introduit pour améliorer la science computationnelle en imitant la recherche scientifique comme un processus de bandit contextuel guidé par les connaissances. Ce cadre vise à résoudre les défis de la traduction des idées conceptuelles en code fiable, ce qui a été un goulot d'étranglement majeur dans le domaine.

ATHENA, an innovative agentic framework, has been introduced to enhance computational science by emulating scientific research as a knowledge-driven contextual bandit process. This framework aims to address the challenges of translating conceptual insights into reliable code, which has been a significant bottleneck in the field.