The Role of Artificial Intelligence in Modern Experimental Physics

Abstract

Artificial Intelligence (AI) can ease the analysis of complex experimental data, automate routine tasks, enhance data-driven decision-making, and support the design of new experiments. Recent large-language models exhibit capabilities and potential that researchers begin to investigate, while AI augments and assists rather than replaces human ingenuity and scientific expertise (Behandish et al., 2022).

AI encompasses both theoretical explanations and automatisms that use algorithms, data, and computer power to extract pertinent information from diverse data types (Carini et al., 2022). With new instruments and evolving research avenues, scientists increasingly acquire and examine data from sensors, simulations, or other sources with heterogeneous and complex formats. Individuals lack time or expertise to comprehend all resulting datasets, obtain relevant data from petabytes, or make rapid and informed choices regarding data acquisition or experimental alterations at every stage. Consequently, even straightforward decisions on the angle, focus, frame rate, temperature, or other parameters may lag significantly behind technological or scientific advances. AI systems can assist in determining these quantities, thereby enlarging the parameter space within which human judgment can concentrate. From a physics viewpoint, consideration of simpler, more concise solutions requires insight into the experiment and data acquisition strategy.

Keywords: AI-Assisted Data Acquisition, Intelligent Experimental Optimization, High-Dimensional Scientific Data Analysis, Human–AI Collaboration in Physics, Computational Intelligence in Physical Sciences.