Cited by 573Quantum Mechanics and ApplicationsQuantum Information and CryptographyAdvanced Thermodynamics and Statistical Mechanics

Quantum Darwinism

Open access
Zurek, Wojciech Hubert·2009·Nature Physics

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 · 10.1038/nphys1202

Cites

35 of 35 references verified0 citation errors · 0 not checkable

Statistics

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

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • QCNNs and QNNs with tree tensor network architectures do not exhibit barren plateaus, potentially making them a generically trainable architecture for large-scale implementations.

    “Moreover, it has been shown that QCNNs and QNNs with tree tensor network architectures do not exhibit barren plateaus [179, 180] (which will be discussed later), potentially making them a generically trainable architecture for large-scale implementations.”

    From Variational quantum algorithms (2021) · cites this paper as [179]

    Section III, “From Copying to Quantum Jumps,” discusses copying quantum-state information, while Section V discusses quantum Darwinism. Searches for barren plateaus, QCNNs, tree tensor networks, and neural-network trainability found no passage addressing the attributed claim. (LLM, conf=0.78)

    Experimental — accuracy not yet measured
  • Certain quantum neural network architectures are trainable even for large problems.

    “An exciting prospect for using quantum neural networks is that certain architectures are immune to barren plateaus, and hence are trainable even for large problems [179, 180].”

    From Variational quantum algorithms (2021) · cites this paper as [179]

    The opening passage describes quantum Darwinism, and Section V discusses decoherence and the measurement problem. Searches for quantum neural networks, barren plateaus, and trainability returned no passage addressing whether any architecture is trainable for large problems. (LLM, conf=0.78)

    Experimental — accuracy not yet measured
  • Certain quantum neural network architectures are immune to barren plateaus.

    “An exciting prospect for using quantum neural networks is that certain architectures are immune to barren plateaus, and hence are trainable even for large problems [179, 180].”

    From Variational quantum algorithms (2021) · cites this paper as [179]

    The opening passage and Section V (Discussion) address quantum Darwinism and the quantum measurement problem, not neural-network training. Searches for barren plateaus and for vanishing gradients or trainability in large quantum circuits found no passage addressing the claim. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

Self-check

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

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

Cites

Flagged first, then by citations

Research works printed but not linked: 5

  1. [22]Dirac, P. A. M., Quantum Mechanics (Clarendon Press, Oxford, 1958).
  2. A 76, 052110 (2007).
  3. [27]Everett III, H., 1957b, Ph. D. Dissertation, Princeton University.
  4. [28]DeWitt, B. S., and Graham, N., eds., The Many - Worlds Interpretation of Quantum Mechanics (Princeton Univer- sity Press, Princeton, 1973).
  5. Lett. 90, 120404 (2003).

Cited by

Sorted by citations

Authors
Zurek, W. H.
Affiliations
Los Alamos National Laboratory (US)
Corresponding author
Zurek, Wojciech Hubert
Venue
Nature Physics
Published
2009-03
Volume
5
Issue
3
Pages
181-188
ISSN
  • 1745-2473 (ISSN-L)
  • 1745-2481
OpenAlex
W3037859133
Cited by
564
References
33
Citations by year
2026: 77 · 2025: 44 · 2024: 40 · 2023: 37 · 2022: 41 · 2021: 36 · 2020: 31 · 2019: 37 · 2018: 48 · 2017: 24 · 2016: 28 · 2015: 25 · 2014: 18 · 2013: 24 · 2012: 22
FWCI
10.04
Type
journal article
Language
en
Open access
Locations
  • Nature Physics (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University) (public-domain)
Topics
  • Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum Mechanics and Applications
  • Physical Sciences › Computer Science › Artificial Intelligence › Quantum Information and Cryptography
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Advanced Thermodynamics and Statistical Mechanics
Keywords
quantum Darwinism, measurement problem, wave packet collapse, Born rule, environmental records, decoherence, quantum-to-classical transition

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