A real-time extension of density matrix embedding theory for non-equilibrium electron dynamics
- Creators
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Kretchmer, Joshua S.
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Chan, Garnet Kin-Lic
Abstract
We introduce real-time density matrix embedding theory (DMET), a dynamical quantum embedding theory for computing non-equilibrium electron dynamics in strongly correlated systems. As in the previously developed static DMET, real-time DMET partitions the system into an impurity corresponding to the region of interest coupled to the surrounding environment, which is efficiently represented by a quantum bath of the same size as the impurity. In this work, we focus on a simplified single-impurity time-dependent formulation as a first step toward a multi-impurity theory. The equations of motion of the coupled impurity and bath embedding problem are derived using the time-dependent variational principle. The accuracy of real-time DMET is compared to that of time-dependent complete active space self-consistent field (TD-CASSCF) theory and time-dependent Hartree-Fock (TDHF) theory for a variety of quantum quenches in the single impurity Anderson model (SIAM), in which the Hamiltonian is suddenly changed (quenched) to induce a non-equilibrium state. Real-time DMET shows a marked improvement over the mean-field TDHF, converging to the exact answer even in the non-trivial Kondo regime of the SIAM. However, as expected from analogous behavior in static DMET, the constrained structure of the real-time DMET wavefunction leads to a slower convergence with respect to active space size, in the single-impurity formulation, relative to TD-CASSCF. Our initial results suggest that real-time DMET provides a promising framework to simulate non-equilibrium electron dynamics in which strong electron correlation plays an important role, and lays the groundwork for future multi-impurity formulations.
Additional Information
© 2017 Published by AIP Publishing. Received 7 November 2017; accepted 14 January 2018; published online 7 February 2018. This work was supported by the US National Science Foundation, through Nos. CHE-1265277 and CHE-1665333. We thank Miles Stoudenmire for help with ITensor. The PySCF modules used in this work were developed with support from the US National Science Foundation, through No. OAC-1657286.Attached Files
Published - 1.5012766.pdf
Submitted - 1609.07678.pdf
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Additional details
- Eprint ID
- 71987
- Resolver ID
- CaltechAUTHORS:20161114-104327735
- NSF
- CHE-1265277
- NSF
- CHE-1665333
- NSF
- OAC-1657286
- Created
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2016-11-15Created from EPrint's datestamp field
- Updated
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2021-11-11Created from EPrint's last_modified field