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arXiv · 2510.15030

Adiabatic transport of neural network quantum states

Matija Medvidović·Alev Orfi·Juan Carrasquilla·Dries Sels
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Abstract

Variational methods have offered controllable and powerful tools for capturing many-body quantum physics for decades. The recent introduction of expressive neural network quantum states has enabled the accurate representation of a broad class of complex wavefunctions for many Hamiltonians of interest. We introduce a first-principles method for building neural network representations of many-body excited states by adiabatically continuing eigenstates of simple Hamiltonians into the strongly correlated regime. With controlled access to the full many-body gap, we obtain accurate estimates of critical exponents. Successive eigenstate estimates can be run entirely in parallel, enabling precise targeting of excited-state properties without reference to the rest of the spectrum, opening the door to large-scale numerical investigations of universal properties of entire phases of matter.

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Matija Medvidović, Alev Orfi, Juan Carrasquilla, Dries Sels. 2025-10-16. Adiabatic transport of neural network quantum states. https://arxiv.org/abs/2510.15030

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