In his new Opinion piece in APS News, Ben Nachman – a staff scientist in Berkeley Lab’s Physics Division, where he leads the Machine Learning for Fundamental Physics group – describes a new kind of scientist that is bridging the gap between theory and experiment to search for new physics.
Modern particle physics experiments produce more data than traditional tools can analyze. To navigate this vast expanse of raw data, modern physicists now use cutting-edge data science tools like machine learning for complex analysis. “After the machines run, the data people step in,” says Nachman, but although these people may be neither traditional theorists nor traditional experimentalists, “they’re here already, straddling different camps and fields, proving themselves invaluable to physics.”
Nachman proposes that these new data physicists – specialists who have the ability to understand and interrogate data using a strong foundation in data science, statistics, and machine learning; as well as the computational and theoretical background to relate data to underlying physical properties – should be recognized and named, both for clout and legitimacy, and in order to facilitate broader employment opportunities, educational pathways, and funding resources: “As available data grows, so does our need for data physicists. Let’s start by calling them what they are. But then let’s do the hard work: educating, training, and funding this brilliant new generation.”
Read the full article:
The Rise of the Data Physicist
October 13, 2023 / Benjamin Nachman / APS News