AI Article Synopsis

  • Many-body localized Hamiltonians display area law entanglement, allowing efficient representation of low entanglement states using matrix product states (MPS), which is critical for algorithms like density matrix renormalization group (DMRG).
  • Two new algorithms, shift-and-invert MPS (SIMPS) and excited state DMRG, are proposed for finding highly excited eigenstates of many-body localized systems, using unique techniques like modified sweeping and Hamiltonian inversion.
  • The effectiveness of these methods is confirmed by analyzing the eigenstate thermalization hypothesis breakdown, observing entanglement saturation, and creating local excitations in the random field Heisenberg model.

Article Abstract

A key property of many-body localized Hamiltonians is the area law entanglement of even highly excited eigenstates. Matrix product states (MPS) can be used to efficiently represent low entanglement (area law) wave functions in one dimension. An important application of MPS is the widely used density matrix renormalization group (DMRG) algorithm for finding ground states of one-dimensional Hamiltonians. Here, we develop two algorithms, the shift-and-invert MPS (SIMPS) and excited state DMRG which find highly excited eigenstates of many-body localized Hamiltonians. Excited state DMRG uses a modified sweeping procedure to identify eigenstates, whereas SIMPS applies the inverse of the shifted Hamiltonian to a MPS multiple times to project out the targeted eigenstate. To demonstrate the power of these methods, we verify the breakdown of the eigenstate thermalization hypothesis in the many-body localized phase of the random field Heisenberg model, show the saturation of entanglement in the many-body localized phase, and generate local excitations.

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http://dx.doi.org/10.1103/PhysRevLett.118.017201DOI Listing

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