Reconstructing effective Hamiltonians from nonequilibrium (pre-)thermal
steady states
- URL: http://arxiv.org/abs/2308.08608v1
- Date: Wed, 16 Aug 2023 18:02:15 GMT
- Title: Reconstructing effective Hamiltonians from nonequilibrium (pre-)thermal
steady states
- Authors: Sourav Nandy, Markus Schmitt, Marin Bukov, Zala Lenar\v{c}i\v{c}
- Abstract summary: We propose a deep-learning-assisted variational algorithm for Hamiltonian reconstruction.
We demonstrate the efficient and precise reconstruction of local Hamiltonians.
We also reconstruct the effective Hamiltonian widely used for Floquet engineering of metastable steady states.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Reconstructing Hamiltonians from local measurements is key to enabling
reliable quantum simulation: both validating the implemented model, and
identifying any left-over terms with sufficient precision is a problem of
increasing importance. Here we propose a deep-learning-assisted variational
algorithm for Hamiltonian reconstruction by pre-processing a dataset that is
diagnosed to contain thermal measurements of local operators. We demonstrate
the efficient and precise reconstruction of local Hamiltonians, while
long-range interacting Hamiltonians are reconstructed approximately. Away from
equilibrium, for periodically and random multipolar driven systems, we
reconstruct the effective Hamiltonian widely used for Floquet engineering of
metastable steady states. Moreover, our approach allows us to reconstruct an
effective quasilocal Hamiltonian even in the heating regime beyond the validity
of the prethermal plateau, where perturbative expansions fail.
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