Abstract

The characterization of open quantum systems is a central and recurring problem for the development of quantum technologies. For time-independent systems, an (often unique) steady state describes the average physics once all the transient processes have faded out, but interesting quantum properties can emerge at intermediate timescales. Given a Lindblad master equation, these properties are encoded in the spectrum of the Liouvillian whose diagonalization, however, is a challenge even for small-size quantum systems. Here, we propose a new method to efficiently provide the Liouvillian spectral decomposition. We call this method an Arnoldi-Lindblad time evolution, because it exploits the algebraic properties of the Liouvillian superoperator to efficiently construct a basis for the Arnoldi iteration problem. The advantage of our method is double: (i) It provides a faster-than-the-clock method to efficiently obtain the steady state, meaning that it produces the steady state through time evolution shorter than needed for the system to reach stationarity. (ii) It retrieves the low-lying spectral properties of the Liouvillian with a minimal overhead, allowing to determine both which quantum properties emerge and for how long they can be observed in a system. This method is general and model-independent, and lends itself to the study of large systems where the determination of the Liouvillian spectrum can be numerically demanding but the time evolution of the density matrix is still doable. Our results can be extended to time evolution with a time-dependent Liouvillian. In particular, our method works for Floquet (i.e., periodically driven) systems, where it allows not only to construct the Floquet map for the slow-decaying processes, but also to retrieve the stroboscopic steady state and the eigenspectrum of the Floquet map. Although the method can be applied to any Lindbladian evolution (spin, fermions, bosons, …), for the sake of simplicity we demonstrate the efficiency of our method on several examples of coupled bosonic resonators (as a particular example). Our method outperforms other diagonalization techniques and retrieves the Liouvillian low-lying spectrum even for system sizes for which it would be impossible to perform exact diagonalization.

Highlights

  • The high-degree of controllability of photonic platforms, such as superconducting circuits [1,2,3,4,5], Rydberg atoms [6, 7], and optomechanical resonators [8,9,10,11], makes them ideal candidates for the realization of quantum simulators and quantum computers [12,13,14]

  • In open quantum systems the interplay between classical and quantum fluctuations induced by the competition between Hamiltonian dynamics, pumping, and dissipation results in a nonequilibrium stationary state whose properties cannot be determined by a free energy analysis [25,26,27]

  • We have introduced a method to efficiently determine the steady state and the low-lying eigenvalues and eigenmatrices of the evolution operator of an open quantum system governed by a Lindblad master equation for (i) A time-independent Liouvillian; (ii) A Floquet Liouvillian

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Summary

Introduction

The high-degree of controllability of photonic platforms, such as superconducting circuits [1,2,3,4,5], Rydberg atoms [6, 7], and optomechanical resonators [8,9,10,11], makes them ideal candidates for the realization of quantum simulators and quantum computers [12,13,14]. One can determine the steady state and all the dynamical features of an open quantum system by diagonalizing the so-called Liouvillian superoperator, that is, the linear function which induces the time evolution of a system’s density matrix via the Lindblad master equation [59]. We will introduce a new method capable of combining the exactness of the Liouvillian and Floquet map diagonalization with the efficiency of time evolution of ρ(t) to retrieve extremely precise estimations of the (stroboscopic) steady state and of the long-lived dynamical processes from relatively short time evolution of the density matrix.

Time-independent Lindblad master equation
Liouvillian spectrum
Arnoldi time evolution
General idea behind the algorithm and its physical meaning
Arnoldi iteration and the evolution operator
Krylov subspaces and Arnoldi iteration
The exponential map as an alternative operator
Krylov space of the time evolution and the Arnoldi-Lindblad algorithm
The time-independent drivendissipative Bose-Hubbard model
Uniform drive
The dimer
The trimer
Asymmetric drive and time crystal in a dimer
Floquet-Liouvillian systems
Computing the Floquet map
Using Arnoldi-Lindblad time evolution
Time-dependent Bose-Hubbard dimer
Analysis of the Floquet map
Conclusions and Perspectives
A Pseudo-codes
B Iterative methods for the Liouvillian and their problems
Shifted Arnoldi
Shifted-inverted Arnoldi
13: Convergence is reached
Full Text
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