标题： 缩放粒子碰撞数据分析 显示英文标题

标题： Scaling Particle Collision Data Analysis

摘要： 几十年来，研究人员已经开发了任务特定的模型，以解决跨不同学科的科学挑战。 最近，大型语言模型（LLMs）在处理通用任务方面表现出巨大的能力；然而，这些模型在解决现实世界的科学问题时遇到了困难，特别是在涉及大规模数值数据分析的领域，如实验高能物理。 这种限制主要是由于BPE分词方法在数值数据上的无效性。 在本文中，我们提出了一种任务无关的架构BBT-Neutron，该架构采用二进制分词方法，以促进在文本和大规模数值实验数据混合数据上的预训练。 我们展示了BBT-Neutron在喷注起源识别（JoI）中的应用，这是高能物理中一个关键的分类挑战，用于区分来自不同夸克或胶子的喷注。 我们的结果表明，BBT-Neutron的性能与最先进的任务特定JoI模型相当。 此外，我们研究了BBT-Neutron性能随着数据量增加的扩展行为，表明BBT-Neutron有可能作为粒子物理数据分析的基础模型，并可能扩展到广泛科学计算应用，包括大科学实验、工业制造和空间计算。 该项目代码可在https://github.com/supersymmetry-technologies/bbt-neutron获取。 显示英文摘要

摘要： For decades, researchers have developed task-specific models to address scientific challenges across diverse disciplines. Recently, large language models (LLMs) have shown enormous capabilities in handling general tasks; however, these models encounter difficulties in addressing real-world scientific problems, particularly in domains involving large-scale numerical data analysis, such as experimental high energy physics. This limitation is primarily due to BPE tokenization's inefficacy with numerical data. In this paper, we propose a task-agnostic architecture, BBT-Neutron, which employs a binary tokenization method to facilitate pretraining on a mixture of textual and large-scale numerical experimental data. We demonstrate the application of BBT-Neutron to Jet Origin Identification (JoI), a critical categorization challenge in high-energy physics that distinguishes jets originating from various quarks or gluons. Our results indicate that BBT-Neutron achieves comparable performance to state-of-the-art task-specific JoI models. Furthermore, we examine the scaling behavior of BBT-Neutron's performance with increasing data volume, suggesting the potential for BBT-Neutron to serve as a foundational model for particle physics data analysis, with possible extensions to a broad spectrum of scientific computing applications for Big Science experiments, industrial manufacturing and spacial computing. The project code is available at https://github.com/supersymmetry-technologies/bbt-neutron.