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arXiv:1205.2178 · Physical Review Letters

Reduced Equations of Motion for Quantum Systems Driven by Diffusive Markov Processes

Mohan Sarovar, Matthew Grace

Published Sep 24, 2012• 11 citations
arXivHTMLPDF

Abstract

The expansion of a stochastic Liouville equation for the coupled evolution of a quantum system and an Ornstein-Uhlenbeck process into a hierarchy of coupled differential equations is a useful technique that simplifies the simulation of stochastically driven quantum systems. We expand the applicability of this technique by completely characterizing the class of diffusive Markov processes for which a useful hierarchy of equations can be derived. The expansion of this technique enables the examination of quantum systems driven by non-Gaussian stochastic processes with bounded range. We present an application of this extended technique by simulating Stark-tuned Förster resonance transfer in Rydberg atoms with nonperturbative position fluctuations.

DOI
10.1103/physrevlett.109.130401

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The expansion of a stochastic Liouville equation for the coupled evolution of a quantum system and an Ornstein-Uhlenbeck process into a hierarchy of coupled differential equations is a useful technique that simplifies the simulation of stochastically driven quantum systems. We expand the applicability of this technique by completely characterizing the class of diffusive Markov processes for which a useful hierarchy of equations can be derived. The expansion of this technique enables the examination of quantum systems driven by non-Gaussian stochastic processes with bounded range. We present an application of this extended technique by simulating Stark-tuned Förster resonance transfer in Rydberg atoms with nonperturbative position fluctuations.
We extend a standard stochastic theory to study open quantum systems coupled to a generic quantum environment. We exemplify the general framework by studying a two-level quantum system coupled bilinearly to the three fundamental classes of non-interacting particles: bosons, fermions, and spins. In this unified stochastic approach, the generalized stochastic Liouville equation (SLE) formally captures the exact quantum dissipations when noise variables with appropriate statistics for different bath models are applied. Anharmonic effects of a non-Gaussian bath are precisely encoded in the bath multi-time correlation functions that noise variables have to satisfy. Starting from the SLE, we devise a family of generalized hierarchical equations by averaging out the noise variables and expand bath multi-time correlation functions in a complete basis of orthonormal functions. The general hierarchical equations constitute systems of linear equations that provide numerically exact simulations of quantum dynamics. For bosonic bath models, our general hierarchical equation of motion reduces exactly to an extended version of hierarchical equation of motion which allows efficient simulation for arbitrary spectral densities and temperature regimes. Similar efficiency and flexibility can be achieved for the fermionic bath models within our formalism. The spin bath models can be simulated with two complementary approaches in the present formalism. (I) They can be viewed as an example of non-Gaussian bath models and be directly handled with the general hierarchical equation approach given their multi-time correlation functions. (II) Alternatively, each bath spin can be first mapped onto a pair of fermions and be treated as fermionic environments within the present formalism.
A method is presented by which the stochastic Schrodinger equation can be derived for systems coupled to a reservoir in cases in which the system-reservoir interaction is non-Markovian, and under the condition that the initial system reservoir state is decorrelated. The method is based on a Heisenberg equation of motion approach applied in conjunction with a technique of dealing with system-reservoir interactions introduced by Mollow in his treatment of the AC Stark effect. The general Diosi-Strunz stochastic Schrodinger equation is regained, but the method developed here offers a different perspective on obtaining the final form of this equation for specific applications. The method is illustrated for a damped two level atom, a driven damped harmonic oscillator, and quantum Brownian motion.
Firstly, the Markovian stochastic Schrödinger equations are presented, together with their connections with the theory of measurements in continuous time. Moreover, the stochastic evolution equations are translated into a simulation algorithm, which is illustrated by two concrete examples — the damped harmonic oscillator and a two-level atom with homodyne photodetection. We then consider how to introduce memory effects in the stochastic Schrödinger equation via coloured noise. Specifically, the approach by using the Ornstein-Uhlenbeck process is illustrated and a simulation for the non-Markovian process proposed. Finally, an analytical approximation technique is tested with the help of the stochastic simulation in a model of a dissipative qubit.
The hierarchy equations of motion provide an elegant formalism for the description of non-Markovian quantum dynamics, which has successfully been applied to a broad variety of physical problems ranging from light-harvesting complexes to resonant tunnelling junctions. When these equations are derived from microscopic models of system and environment, then they typically expand to an infinite series of coupled differential equations. The truncation of this series is accompanied by an approximation of the dynamics and can give rise to a violation of complete positivity. The goal of this thesis is to investigate under what conditions a set of hierarchy equations of motion induces completely positive dynamics. Such conditions are in particular crucial for a phenomenological understanding of the equations of motion. Several approaches to this problem are proposed and compared for classical systems before a generalisation to quantum mechanical problems is carried out. The main result is a concise set of operator inequalities that are sufficient for complete positivity and that can be implemented efficiently in terms of a semi-definite program. The applicability of this technique is demonstrated by various explicit examples. For truncated hierarchy equations for which a violation of complete positivity is inevitable the framework is extended such that the degree of this violation can be estimated and the validity of the truncation can be gauged. In particular in the presence of initial system-environment correlations a dynamical process can also be considered physically reasonable, when the time evolution is not completely positive and it is shown how hierarchy equations that describe such scenarios can be identified. Eventually, the framework is altered such that it gives rise to conditions on hierarchy equations that are sufficient not only for completely positive but even Markovian dynamics.
The dynamics of an open quantum system coupled to an external reservoir is studied on the basis of a recently proposed formulation of quantum statistical ensembles in terms of probability distributions on projective Hilbert space. The previous result is generalized to include interaction Hamiltonians of the form tsumi{\mathit{tsum}}_{\mathit{i}}tsumi​Ai{\mathit{A}}_{\mathit{i}}Ai​\ensuremath{\bigotimes}Bi{\mathit{B}}_{\mathit{i}}Bi​, where Ai{\mathit{A}}_{\mathit{i}}Ai​ and Bi{\mathit{B}}_{\mathit{i}}Bi​ are operators acting on the Hilbert space of the reduced system and of the reservoir, respectively. The differential Chapman-Kolmogorov equation governing the dynamics of the conditional transition probability of the reduced system is derived from the underlying microscopic theory based on the Schr\"odinger equation for the total system. The stochastic process turns out to be a piecewise deterministic Markovian jump process in the projective Hilbert space of the reduced system. The sample paths are derived and shown to be similar to those of the Monte Carlo wave function simulation methods proposed in the literature. Finally, a diffusion-noise expansion of the Liouville master equation is performed and demonstrated to yield a stochastic differential equation for the state vector of the open system.
We present an approach to the simulation of quantum systems driven by classical stochastic processes that is based on the polynomial chaos expansion, a well-known technique in the field of uncertainty quantification. The polynomial chaos technique represents the density matrix as an expansion in orthogonal polynomials over the principle components of the stochastic process and yields a sparsely coupled hierarchy of linear differential equations. We provide practical heuristics for truncating this expansion based on results from time-dependent perturbation theory and demonstrate, via an experimentally relevant one-qubit numerical example, that our technique can be significantly more computationally efficient than Monte Carlo simulation.