Quick Navigation

Overview Topics Abstract Importance Paper Tools References Reactions Discussion Publication

Topics

Open Quantum Systems Decoherence

Optimal identification of non-Markovian environments for spin chains

arXiv
Authors: Shibei Xue, Jun Zhang, Ian R. Petersen

Year

2018

Paper ID

23754

Status

Preprint

Abstract Read

~2 min

Abstract Words

104

Citations

N/A

Abstract

Correlations of an environment are crucial for the dynamics of non-Markovian quantum systems, which may not be known in advance. In this paper, we propose a gradient algorithm for identifying the correlations in terms of time-varying damping rate functions in a time-convolution-less master equation for spin chains. By measuring time trace observables of the system, the identification procedure can be formulated as an optimization problem. The gradient algorithm is designed based on a calculation of the derivative of an objective function with respect to the damping rate functions, whose effectiveness is shown in a comparison to a differential approach for a two-qubit spin chain.

Why This Paper Matters

  • This paper contributes to the Open Quantum Systems & Decoherence research area in the Quantum Articles archive.
  • It adds a 2018 reference point for readers tracking recent quantum research.
  • Correlations of an environment are crucial for the dynamics of non-Markovian quantum systems, which may not be known in advance.

Paper Tools

Become a member to use research tools

Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.

Become a member Sign in
Show Paper arXiv Publisher Share Cite This Paper Copy URL Compare Copy DOI Add to Reading List Category Correction Request

References & Citation Signals

[1] DOI https://doi.org/arXiv:1810.11923 [2] arXiv https://arxiv.org/abs/1810.11923 [3] Publisher https://arxiv.org/abs/1810.11923

Local Citation Graph (Related-Paper Links)

Current Paper #23754

External citation index: OpenAlex citation signal

Community Reactions

Quick sentiment from readers on this paper.

Score: 0
Likes: 0 Dislikes: 0

Sign in to react to this paper.

Discussion & Reviews (Moderated)

Average Rating: 0.0 / 5 (0 ratings)

No written reviews yet.