dorsal/arxiv
View SchemaEfficient extraction of quantum Hamiltonians from optimal laboratory data
| Authors | JM Geremia, Herschel A. Rabitz |
|---|---|
| Categories | |
| ArXiv ID | quant-ph/0312212 |
| URL | https://arxiv.org/abs/quant-ph/0312212 |
| DOI | 10.1103/PhysRevA.70.023804 |
Abstract
Optimal Identification (OI) is a recently developed procedure for extracting optimal information about quantum Hamiltonians from experimental data using shaped control fields to drive the system in such a manner that dynamical measurements provide maximal information about its Hamiltonian. However, while optimal, OI is computationally expensive as initially presented. Here, we describe the unification of OI with highly efficient global, nonlinear map-facilitated data inversion procedures. This combination is expected to make OI techniques more suitable for laboratory implementation. A simulation of map-facilitated OI is performed demonstrating that the input-output maps can greatly accelerate the inversion process.
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"abstract": "Optimal Identification (OI) is a recently developed procedure for extracting\noptimal information about quantum Hamiltonians from experimental data using\nshaped control fields to drive the system in such a manner that dynamical\nmeasurements provide maximal information about its Hamiltonian. However, while\noptimal, OI is computationally expensive as initially presented. Here, we\ndescribe the unification of OI with highly efficient global, nonlinear\nmap-facilitated data inversion procedures. This combination is expected to make\nOI techniques more suitable for laboratory implementation. A simulation of\nmap-facilitated OI is performed demonstrating that the input-output maps can\ngreatly accelerate the inversion process.",
"arxiv_id": "quant-ph/0312212",
"authors": [
"JM Geremia",
"Herschel A. Rabitz"
],
"categories": [
"quant-ph"
],
"doi": "10.1103/PhysRevA.70.023804",
"title": "Efficient extraction of quantum Hamiltonians from optimal laboratory data",
"url": "https://arxiv.org/abs/quant-ph/0312212"
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