Ideas

Motivated by the growing interest in using artificial intelligence for teaching purposes, IAS scholars from the Schools of Mathematics and Natural Sciences have conducted an innovative study to assess the correctness and helpfulness of large language models in STEM education. Their research yielded surprising results, including highlighting the importance of training models on pedagogical conversations rather than textbooks.

Scholars from the School of Natural Sciences are leading investigations into the sources of gravitational wave signals, the unexpectedly high frequency of detections, and—extending beyond these direct questions—establishing innovative and unexpected connections between gravitational wave research and particle collider physics. These contributions are redefining our understanding of the field.

Building on analogs with plasma physics, John N. Bahcall Fellow Chris Hamilton (2021–26), visiting graduate student Shaunak Modak (2023–26), and Professor Emeritus Scott Tremaine have developed a new theoretical framework for understanding galactic disks. 

Sihao Cheng, Martin A. and Helen Chooljian Member in the Institute for Advanced Study’s School of Natural Sciences (2022–25), describes how he is mining a previously overlooked dataset in his ongoing search for a possible ninth planet in our solar system.

Meet Beatrix Muehlmann, Member in the School of Natural Sciences, who is curious about the origin and fate of the universe. In this Q&A, she details her efforts to describe gravity through the principles of quantum mechanics, her admiration for mathematical physicist Emmy Noether, and the joy of being a part of a group of scientists interested in fundamental questions.

Digvijay Wadekar, Member in the School of Natural Sciences (2021–24), reflects on the evolving nature of problem-solving in modern physics and how the Institute for Advanced Study supports both interdisciplinary collaboration and individual inquiry.

Lia Medeiros, Visitor in the Institute for Advanced Study's School of Natural Sciences (2023–24), describes how she created a machine learning algorithm to produce new images of the black hole at the center of our galaxy, and how such images can be used to test Albert Einstein's theory of gravity.

Why does the immune system target one particular molecular feature over another, and how does that selection affect the evolution of cancer and viruses? Benjamin Greenbaum, Long-term Member (2008–13) in the School of Natural Sciences, highlights his work on the theory of self versus non-self discrimination.

The work of plasma fusion physicists may seem completely divorced from the realm of theoretical astrophysics, but, as Chris Hamilton, John N. Bahcall Fellow in the School of Natural Sciences, explains, the mathematical methods developed to exploit the power of the electrons, ions, and magnetic fields in fusion plasmas are precisely the same as those needed to describe the dynamics of stars, spiral arms, and dark matter in galaxies like the Milky Way. 

Weishun Zhong, Member in the School of Natural Sciences, uses tools from statistical physics to study the brain and AI. "Although these two might appear very different at first glance," he states, "when zoomed out and abstracted away, they are both just networks of basic units called neurons."