ATL 3100A and Virtual Via Zoom: https://umd.zoom.us/j/5871875361?omn=98612137949
Description
Title: From Preparing Quantum Spin Lakes to Measuring Chaos with Hamiltonian Learning: Quantum Simulation Beyond the Ground State Speaker:  Nik Gjonbalaj (Harvard University) Date & Time:  June 4, 2026, 10:00am Where to Attend:  ATL 3100A and Virtual Via Zoom: https://umd.zoom.us/j/5871875361?omn=98612137949
Quantum simulators provide a wide array of tools for studying physics both in and out of equilibrium. In this talk, I will highlight two ways that equilibrium physics can provide novel tools and understanding away from the ground state by 1) accelerating the preparation of quantum spin lakes and 2) measuring chaos using tools from Hamiltonian learning.
In the first part of the talk, I will focus on the dynamical preparation of quantum spin liquids in analog simulators. Recently, it was shown that fast, non-adiabatic Hamiltonian parameter sweeps can create finite-size ``lakes'' of quantum order in certain settings, independent of what is present in the ground state phase diagram. Here, we show that going further out of equilibrium via external driving can substantially accelerate the preparation of these quantum lakes. Concretely, when lakes can be prepared, existing counterdiabatic driving techniques -- originally designed to target the ground state -- instead naturally target the lakes state. We demonstrate this for a model of a Z2 Rydberg quantum spin liquid and construct experimental drive sequences that accelerate preparation by almost an order of magnitude at fixed laser power. We conclude by using a Landau-Ginzburg model to provide a semi-classical picture for how our method accelerates state preparation.
In the second part of the talk, I will present metrics for quantum ergodicity and chaos based on Hamiltonian learning that unify multiple advantages of existing metrics. In particular, we show how ergodicity and chaos improve the robustness of Hamiltonian learning to small errors and furthermore demonstrate that this robustness can be used as a metric for such phenomena. Using intuition from gapless phases of matter, we analytically and numerically show that our metrics distinguish between integrable and ergodic regimes. Furthermore, our metrics are able to quantify chaos and ergodicity, allowing us to locate regions of parameter space displaying maximal ergodicity and maximal sensitivity to local perturbations. Our approach not only provides conceptual ways to study quantum chaos and ergodicity but also presents viable experimental methods for quantum simulators.
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