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arXiv:2205.06521 · Physical Review A

Reconstructing non-Markovian open quantum evolution from multiple time measurements

Chu Guo

Published Aug 15, 2022• 7 citations
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Abstract

For a quantum system undergoing non-Markovian open quantum dynamics, we demonstrate a tomography algorithm based on multitime measurements of the system, which reconstructs a minimal environment coupled to the system, such that the system plus environment undergoes unitary evolution and that the reduced dynamics of the system is identical to the observed dynamics of it. The reconstructed open quantum evolution model can be used to predict any future dynamics of the system when it is further assumed to be time-independent. We define the memory size and memory complexity for the non-Markovian open quantum dynamics which characterize the complexity of the reconstruction algorithm.

DOI
10.1103/physreva.106.022411

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For a quantum system undergoing non-Markovian open quantum dynamics, we demonstrate a tomography algorithm based on multitime measurements of the system, which reconstructs a minimal environment coupled to the system, such that the system plus environment undergoes unitary evolution and that the reduced dynamics of the system is identical to the observed dynamics of it. The reconstructed open quantum evolution model can be used to predict any future dynamics of the system when it is further assumed to be time-independent. We define the memory size and memory complexity for the non-Markovian open quantum dynamics which characterize the complexity of the reconstruction algorithm.
Describing dynamics of a quantum system coupled to a complex many-body environment is a ubiquitous problem in quantum science. General non-Markovian environments are characterized by their influence matrix~(IM) -- a multi-time tensor arising from repeated interactions between the system and environment. While complexity of the most generic IM grows exponentially with the evolution time, recent works argued that for many instances of physical many-body environments, the IM is significantly less complex. This is thanks to area-law scaling of temporal entanglement, which quantifies the correlations between the past and the future states of the system. However, efficient classical algorithms for computing IM are only available for non-interacting environments or certain interacting 1D environments. Here, we study a learning algorithm for reconstructing IMs of large many-body environments simulated on a quantum processor. This hybrid algorithm involves experimentally collecting quantum measurement results of auxiliary qubits which are repeatedly coupled to the many-body environment, followed by a classical machine-learning construction of a matrix-product (MPS) representation of the IM. Using the example of 1D spin-chain environments, with a classically generated training dataset, we demonstrate that the algorithm allows scalable reconstruction of IMs for long evolution times. The reconstructed IM can be used to efficiently model quantum transport through an impurity, including cases with multiple leads and time-dependent controls. These results indicate the feasibility of characterizing long-time dynamics of complex environments using a limited number of measurements, under the assumption of a moderate temporal entanglement.
Generic open quantum dynamics can be described by two seemingly very distinct approaches: a top down approach by considering an (unknown) environment coupled to the system and affects the observed dynamics of the system; or a bottom up approach which tries to build an open quantum evolution model from the observed data. The process tensor framework describes all the possible observations one could possibly make on a quantum system, however it is computationally inefficient and not predictive. Here we define the purified process tensor which 1) allows efficient tomography as well as prediction for future process and 2) naturally defines a stationary quantum process as well as a quantitative and easy-to-evaluate definition of the memory complexity, or the degree of non-Markovianity, for it. As such it allows to uncover the minimal open quantum evolution model hidden in the observed data, completing the second approach for understanding open quantum dynamics. The intimate connection between quantum processes and classical stochastic processes is drawn in the end.
Experiments performed on quantum systems often measure multitime correlation functions. When quantum systems are weakly coupled to their environment, the time evolution of such correlation functions can be reduced to that of the reduced density matrix by the quantum regression theorem (QRT). While no QRT is available for general non-Markovian open quantum systems, we show that for time-independent Hamiltonians and finite memory times τcτ_cτc​, an exact factorization rule exists that relates higher-order multitime correlations to products of lower-order correlations. Consequently, all information needed to reconstruct nnn-time correlations is contained in a temporal volume of O(τcn)\mathcal{O}(τ_c^n)O(τcn​). On the example of quantum dots coupled to phonons, we demonstrate that this factorization makes numerical calculations of multitime correlations extremely efficient and even enables semianalytical solutions in systems where the standard QRT breaks down.
Characterization of non-Markovian open quantum dynamics is both of theoretical and practical relevance. In a seminal work [Phys. Rev. Lett. 120, 040405 (2018)], a necessary and sufficient quantum Markov condition is proposed, with a clear operational interpretation and correspondence with the classical limit. Here we propose two non-Markovianity measures for general open quantum dynamics, which are fully reconciled with the Markovian limit and can be efficiently calculated based on the multi-time quantum measurements of the system. A heuristic algorithm for reconstructing the underlying open quantum dynamics is proposed, whose complexity is directly related to the proposed non-Markovianity measures. The non-Markovianity measures and the reconstruction algorithm are demonstrated with numerical examples, together with a careful reexamination of the non-Markovianity in quantum dephasing dynamics.
We investigate the presence of memory in the sequential measurement statistics of an open quantum system, as witnessed by the departure from the quantum regression theorem (QRT), that is, the possibility to predict multitime probabilities from the one-time reduced dynamical map. For factorized initial states, we identify an exact decomposition of the two-time propagator into a QRT-like contribution, fully determined by the reduced dynamical map, and a memory term encoding system--environment correlations across the intervention; in the weak-coupling regime, the memory term yields an explicit second-order correction expressed in terms of the reduced map and bath correlation functions. Furthermore, we introduce an operational quantifier of QRT violations based on the distance between exact and QRT-predicted joint probabilities. Benchmarking the framework on a spin--boson model and using a pseudomode embedding as nonperturbative reference, we comprehensively analyze the impact of spectral-density parameters, environmental temperature, and measurement protocols on the non-Markovianity of the multitime statistics. Comparison with a one-time quantifier shows that reduced-state non-Markovianity and multitime memory are related but inequivalent: the latter, as probed through sequential statistics, is intrinsically protocol dependent and can become visible at higher temporal order even when two-time statistics remain compatible with QRT predictions.
We identify the conditions that guarantee equivalence of the reduced dynamics of an open quantum system (OQS) for two different types of environments-one a continuous bosonic environment leading to a unitary system-environment evolution and the other a discrete-mode bosonic environment resulting in a system-mode (nonunitary) Lindbladian evolution. Assuming initial Gaussian states for the environments, we prove that the two OQS dynamics are equivalent if both the expectation values and two-time correlation functions of the environmental interaction operators are the same at all times for the two configurations. Since the numerical and analytical description of a discrete-mode environment undergoing a Lindbladian evolution is significantly more efficient than that of a continuous bosonic environment in a unitary evolution, our result represents a powerful, nonperturbative tool to describe complex and possibly highly non-Markovian dynamics. As a special application, we recover and generalize the well-known pseudomodes approach to open-system dynamics.