Quantum coherent dynamics in photosynthetic protein complexes
Bibliographic record
Abstract
Since the birth of quantum mechanics, there has been a long fascination of the role of quantum effects in the evolution of biological systems, which has inspired decoding quantum coherence effects in photosynthetic systems. In photosynthetic complexes, the pigments do not exist in isolation; they interact with their surrounding protein environment. However, the strength of this system-bath coupling can vary, and one must be careful in characterizing it (with many complexes actually in an intermediate coupling regime). This review will summarize the studies toward unraveling excitonic energy transfer in photosynthetic systems, examining the influence of electronic and vibronic coherence and system-bath interactions on transfer efficiency in photosynthetic protein complexes. The review first examines the absorption properties of chlorophylls and the structural organization of protein complexes, highlighting their role in facilitating ultrafast-energy and charge-transfer processes. It also introduces the principles of multidimensional coherent spectroscopy (a nonlinear four-wave-mixing technique) and related ultrafast spectroscopic methods, which provide key insights into these processes. We also discuss theoretical approaches and models (quantum master equations and other quantum dissipative models) used to simulate the evolution of electronic coherence in photosynthetic systems. Additionally, the review considers recent advancements in both natural and artificial photosynthetic systems, focusing on the critical role of system-bath interactions and dissipation in protein environments. These dynamics are shown to direct energy transfer effectively, overcoming the fragility of quantum coherence under physiological conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".