Workshop III: Response Functions, Time-Dependent Properties and Parameterizations
This workshop explores advanced algebraic, computational, and machine learning methods for modeling electronic structure and molecular properties in chemistry and physics.
Funder: Institute for Pure and Applied Mathematics
Due Dates: March 3, 2027 (Application deadline; fullest consideration)
Funding Amounts: Travel support available; registration fees range from $10 (remote) to $100 (industry); typical support prioritizes early-career researchers.
Summary: Workshop focused on advanced algebraic, computational, and machine learning approaches to electronic structure and molecular property modeling.
Key Information: Funding priority for recent PhDs, graduate students, and early-career researchers; all career stages welcome.
Description
This workshop is part of the long program "Numerical Algebraic Geometry and Correlated Electrons: Generalized Grassmannians, Response Functions and Excited States" at the Institute for Pure and Applied Mathematics (IPAM). It explores advanced methods for simultaneously describing related electronic structure results, with a focus on algebraic approaches to excited states, response functions, and parameterizations of gas-phase molecular properties. Key topics include conical intersections in excited states, higher order response functions for ground states, parametric homotopy continuation, and the integration of machine learning techniques—such as operator learning and gradient-based learning—for surrogate modeling in electronic structure problems. The workshop will feature talks, a poster session, and opportunities for interdisciplinary collaboration.
