Quick Navigation

Topics

Open Quantum Systems Decoherence Quantum Machine Learning

Optimal identification of Hamiltonian information by closed-loop laser control of quantum systems.

PubMed
Authors: Geremia JM, Rabitz H

Year

2002

Paper ID

13079

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

71

Citations

70

Abstract

A closed loop learning control concept is introduced for teaching lasers to manipulate quantum systems for the purpose of optimally identifying Hamiltonian information. The closed loop optimal identification algorithm operates by revealing the distribution of Hamiltonians consistent with the data. The control laser is guided to perform additional experiments, based on minimizing the dispersion of the distribution. Operation of such an apparatus is simulated for two model finite dimensional quantum systems.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2002 reference point for readers tracking recent quantum research.
  • A closed loop learning control concept is introduced for teaching lasers to manipulate quantum systems for the purpose of optimally identifying Hamiltonian information.

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.

Publisher Share Cite This Paper Copy URL Compare Copy DOI Add to Reading List Category Correction Request

References & Citation Signals

Local Citation Graph (Related-Paper Links)

Current Paper #13079 #68474 Concentration-Free Quantum Kern... #68473 Reformulating Neural Operators ... #68469 Pitfalls when tackling the expo... #68466 Uncloneable Encryption from Dec...

External citation index: OpenAlex citation signal • updated 2026-06-13 03:47:17

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.