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Record W2013429239 · doi:10.1103/physreva.82.062310

Identifying the quantum correlations in light-harvesting complexes

2010· article· en· W2013429239 on OpenAlexaff
Kamil Brádler, Mark M. Wilde, Sai Vinjanampathy, D. B. Uskov

Bibliographic record

VenuePhysical Review A · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsQuantum entanglementQuantum discordQuantum correlationQuantum mechanicsQuantumExcitationPhysicsStatistical physicsEntropy (arrow of time)Quantum decoherence

Abstract

fetched live from OpenAlex

One of the major efforts in the quantum biological program is to subject biological systems to standard tests or measures of quantumness. These tests and measures should elucidate whether nontrivial quantum effects may be present in biological systems. Two such measures of quantum correlations are the quantum discord and the relative entropy of entanglement. Here, we show that the relative entropy of entanglement admits a simple analytic form when dynamics and accessible degrees of freedom are restricted to a zero- and single-excitation subspace. We also simulate and calculate the amount of quantum discord that is present in the Fenna-Matthews-Olson protein complex during the transfer of an excitation from a chlorosome antenna to a reaction center. We find that the single-excitation quantum discord and single-excitation relative entropy of entanglement are equal for all of our numerical simulations, but a proof of their general equality for this setting evades us for now. Also, some of our simulations demonstrate that the relative entropy of entanglement without the single-excitation restriction is much lower than the quantum discord. The first picosecond of dynamics is the relevant time scale for the transfer of the excitation, according to some sources in the literature. Our simulation results indicate that quantum correlations contribute a significant fraction of the total correlation during this first picosecond in many cases, at both cryogenic and physiological temperatures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.343
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations60
Published2010
Admission routes1
Has abstractyes

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