Emergent Quantum Matter Across Scales: From Moiré Platforms and Quantum Simulation to AI-Driven Theory

Organizers:

Charlotte Bøettcher, Stanford University
Debanjan Chowdhury, Cornell University 
Dahlia Klein, University of Chicago
Yahui Zhang, Johns Hopkins University

Modern quantum matter is witnessing a convergence of three communities that have largely advanced in parallel. One studies tunable synthetic systems such as moiré materials, cold atoms, and Rydberg arrays. A second probes complex bulk materials including cuprates, nickelates, and heavy fermion materials. A third is building novel computational frameworks like tensor networks and neural-network quantum states. These platforms differ by orders of magnitude in energy and length scale, yet they are governed by the same underlying Hamiltonians and exhibit the same universal phenomena: topological phases, superconductivity, and fractionalization. Moiré materials and quantum simulators offer pristine, tunable playgrounds in which individual interaction terms can be isolated, while bulk materials force us to confront the messier multi-orbital reality of quantum matter. At the same time, the rise of artificial intelligence for science provides a new language for the many-body problem where traditional methods fail. This conference brings together experts from solid-state experiment, AMO physics, and computational theory to uncover universal principles governing correlated matter across disparate platforms, and to test whether a unified framework can emerge.

Learn more at the conference website: https://quantum-matter-aspen-winter-2027.netlify.app/