Adiabatic transport of neural network quantum states

• URL: http://arxiv.org/abs/2510.15030v1
• Date: Thu, 16 Oct 2025 18:00:01 GMT
• Title: Adiabatic transport of neural network quantum states
• Authors: Matija Medvidović, Alev Orfi, Juan Carrasquilla, Dries Sels,
• Abstract summary: We introduce a first-principles method for building neural network representations of many-body excited states.<n>With controlled access to the full many-body gap, we obtain accurate estimates of critical exponents.<n>Successive eigenstate estimates can be run entirely in parallel, enabling precise targeting of excited-state properties.
• Score: 0.39998518782208786
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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