Decoherence in the quantum Ising model with transverse dissipative interaction in the strong coupling regime

Abstract

We study the decoherence dynamics of a quantum Ising lattice of finite size with a transverse dissipative interaction, namely the coupling with the bath is assumed perpendicular to the direction of the spins interaction and parallel to the external transverse magnetic field. In the limit of small transverse field, the eigenstates and spectrum are obtained by a strong coupling expansion, from which we derive the Lindblad equation in the Markovian limit. At temperature lower than the energy gap and for weak dissipation, the decoherence dynamics can be restricted to take only the two degenerate ground states and the first excited subspace into account. The latter is formed by pairs of topological excitations (domain walls or kinks), which are quantum delocalized along the chain due to the small magnetic field. We find that some of these excited states form a relaxation-free subspace, i.e. they do not decay to the ground states. We also discuss the decoherence dynamics for an initial state formed by a quantum superposition of the two degenerate ground states corresponding to the orthogonal classical, ferromagnetic states.

References in corpus (28)

• Quantum Simulation of Antiferromagnetic Spin Chains in an Optical Lattice
• Dynamics of a Quantum Phase Transition
• Realizing quantum Ising models in tunable two-dimensional arrays of single Rydberg atoms
• Quantum Quench in the Transverse Field Ising Chain
• Dynamics of quantum phase transition: exact solution in quantum Ising model
• Time evolution of local observables after quenching to an integrable model
• Direct observation of dynamical quantum phase transitions in an interacting many-body system
• Digitized adiabatic quantum computing with a superconducting circuit
• Onset of a Quantum Phase Transition with a Trapped Ion Quantum Simulator
• Reducing decoherence in quantum computer memory with all quantum bits coupling to the same environment
• Digital quantum simulation of spin models with circuit quantum electrodynamics
• Algebraic versus exponential decoherence in dissipative many-particle systems
• Low temperature relaxational dynamics of the Ising chain in a transverse field
• Phase diagram and critical exponents of a dissipative Ising spin chain in a transverse magnetic field
• Adiabatic dynamics in open quantum critical many-body systems
• Nonequilibrium quantum criticality in open systems: The dissipation rate as an additional indispensable scaling variable
• Multicritical behavior in dissipative Ising models
• Quantum Kibble-Zurek physics in the presence of spatially-correlated dissipation
• Universal, finite temperature, crossover functions of the quantum transition in the Ising chain in a transverse field
• Quantum spin chains with site dissipation
• Topological Schrödinger cats: Non-local quantum superpositions of topological defects
• Quantum phase transition in the multi-mode Dicke model
• Decoherence in the dynamical quantum phase transition of the transverse Ising chain
• Quantum annealing via environment-mediated quantum diffusion
• Criticality in transport through the quantum Ising chain
• Dissipation effects in random transverse-field Ising chains
• Monte Carlo simulations of dissipative quantum Ising models
• Generation and protection of Maximally Entangled State between many modes in an optical network with dissipation

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