Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 226

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Efficient Measurement of Quantum Dynamics via Compressive Sensing

Open access
Shabani, A., Kosut, R. L., Mohseni, M., Rabitz, H., Broome, M. A., Almeida, M. P., Fedrizzi, A., White, A. G.·2011·Physical Review Letters

Abstract

The resources required to characterize the dynamics of engineered quantum systems--such as quantum computers and quantum sensors--grow exponentially with system size. Here we adapt techniques from compressive sensing to exponentially reduce the experimental configurations required for quantum process tomography. Our method is applicable to processes that are nearly sparse in a certain basis and can be implemented using only single-body preparations and measurements. We perform efficient, high-fidelity estimation of process matrices of a photonic two-qubit logic gate. The database is obtained under various decoherence strengths. Our technique is both accurate and noise robust, thus removing a key roadblock to the development and scaling of quantum technologies.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1103/physrevlett.106.100401

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 6 references

Cited by

See all 226

Metadata

Authors
Shabani, A., Kosut, R. L., Mohseni, M., Rabitz, H., Broome, M. A., Almeida, M. P., Fedrizzi, A., & White, A. G.
Venue
Physical Review Letters
Published
2011-03-07
Volume
106
Issue
10
Pages
100401-100401
ISSN
  • 0031-9007 (ISSN-L)
  • 1079-7114
OpenAlex
W2051669075
Cited by
226
References
6
FWCI
22.47
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Efficient Measurement of Quantum Dynamics via Compressive Sensing. https://app.cochat.ai/papers/10.1103/physrevlett.106.100401
The paper
Shabani, A., Kosut, R. L., Mohseni, M., Rabitz, H., Broome, M. A., Almeida, M. P., Fedrizzi, A., & White, A. G. (2011). Efficient Measurement of Quantum Dynamics via Compressive Sensing. Physical Review Letters. https://doi.org/10.1103/physrevlett.106.100401

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.