Publication | Open Access
Ground State Fidelity from Tensor Network Representations
171
Citations
33
References
2008
Year
Geometric LearningQuantum Lattice SystemEngineeringMachine LearningMany-body Quantum PhysicQuantum ComputingSparse Neural NetworkRobot LearningQuantum EntanglementQuantum SciencePhysicsQuantum Field TheoryComputer ScienceTensor Network AlgorithmsDeep LearningGround State FidelityPhase DiagramComputational NeuroscienceNatural SciencesLattice SiteDisordered Quantum SystemLattice Field Theory
For any D-dimensional quantum lattice system, the fidelity between two ground state many-body wave functions is mapped onto the partition function of a D-dimensional classical statistical vertex lattice model with the same lattice geometry. The fidelity per lattice site, analogous to the free energy per site, is well defined in the thermodynamic limit and can be used to characterize the phase diagram of the model. We explain how to compute the fidelity per site in the context of tensor network algorithms, and demonstrate the approach by analyzing the two-dimensional quantum Ising model with transverse and parallel magnetic fields.
| Year | Citations | |
|---|---|---|
Page 1
Page 1