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Light cone tensor network and time evolution

Miguel Frías-Pérez, Mari Carmen Bañuls

2022Physical review. B./Physical review. B34 citationsDOIOpen Access PDF

Abstract

The transverse folding algorithm [M. C. Ba\~nuls et al., Phys. Rev. Lett. 102, 240603 (2009)] is a tensor network method to compute time-dependent local observables in out-of-equilibrium quantum spin chains that can overcome the limitations of matrix product states when entanglement grows slower in the time than in the space direction. We present a contraction strategy that makes use of the exact light cone structure of the tensor network representing the observables. The strategy can be combined with the hybrid truncation proposed for global quenches by Hastings and Mahajan Phys. Rev. A 91, 032306 (2015), which significantly improves the efficiency of the method. We demonstrate the performance of this transverse light cone contraction also for transport coefficients, and discuss how it can be extended to other dynamical quantities.

Topics & Concepts

Light conePhysicsQuantum entanglementObservableCone (formal languages)Tensor (intrinsic definition)Transverse planeQuantumTensor productTime evolutionSpin networkContraction (grammar)Matrix product stateStatistical physicsQuantum mechanicsComputer scienceMathematicsQuantum gravityAlgorithmGeometryStructural engineeringLoop quantum gravityEngineeringPure mathematicsMedicineInternal medicineQuantum many-body systemsPhysics of Superconductivity and MagnetismModel Reduction and Neural Networks
Light cone tensor network and time evolution | Litcius