Environment-Assisted Quantum Transport in Open Quantum Chains

Noise helps. Disorder helps more. And it works almost universally.

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The idea

In quantum systems, environmental noise is usually the enemy — it destroys coherence and scrambles information. But in the right conditions, noise does something counterintuitive: it helps excitation get from A to B.

This is Environment-Assisted Quantum Transport (ENAQT). It was proposed in 2009 to explain how photosynthesis achieves near-perfect efficiency despite operating in a warm, wet, noisy cell. Too little noise → quantum interference traps the excitation. Too much → the system freezes (quantum Zeno effect). At just the right level, noise opens transport channels that pure quantum mechanics closes.

This repository documents a systematic computational study of that effect.

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What we found

1. The framework is exact. We validated an analytical Lindblad model against 1,000 numerically exact simulations from the QD3SET-1 database. Agreement is at machine precision (error < 10⁻¹⁵). The math is right.

2. The sink is what makes it real. Without an irreversible "reaction center" that permanently captures arriving excitation, ENAQT is a subtle 1.27× effect. Add the sink and it jumps to 7.20× — the same physics, but now you're measuring actual transfer efficiency instead of just thermalization rate.

3. Longer chains are better, in a specific way. In a linear energy funnel, enhancement grows almost linearly with chain length (~2.12× per site added) up to about N = 15. But longer chains also need gentler noise — the optimal dephasing rate falls as N⁻¹·²⁴. The actual FMO-7 photosynthetic complex achieves 32.1× at a dephasing rate that falls squarely within the biological room-temperature window. Evolution found the sweet spot.

4. Disorder makes it stronger — not weaker. This one surprised us. We ran 100 random disorder configurations for each chain length. ENAQT appeared in 95–100% of all of them. And at large N, random disorder outperforms the carefully designed energy funnel:

Chain length	Ordered funnel	Disordered median	Disordered mean
N = 7	22.8×	8.9×	97×
N = 10	32.4×	35.7×	595×
N = 15	37.9×	244×	6,916×

The reason: disorder creates Anderson localization — it traps excitation in the coherent limit — making the noise-assisted route look even more miraculous by comparison. The mean grows as σ⁵⁻⁶ with disorder strength. Structural heterogeneity isn't the enemy of quantum transport. It's a resource.

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What's in this repo

File	What it does
enaqt_sb_analysis.py	Loads 1,000 HEOM trajectories, validates the Lindblad model
enaqt_sb_sink.py	Adds the reaction center sink, sweeps energy bias and sink rate
enaqt_nsite_chain.py	Scales to N = 2–20 sites, fits scaling laws, benchmarks FMO-7
enaqt_disorder_ensemble.py	100-seed disorder ensemble + disorder strength sweep (~60s)
PAPER_ENAQT_DRAFT.md	Full paper draft (submission-ready)
main.tex + references.bib	LaTeX source for journal/preprint submission

Each script is self-contained and writes figures + a JSON results file when run.

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Quick start

pip install numpy scipy matplotlib
python enaqt_sb_sink.py        # no external data needed
python enaqt_nsite_chain.py    # no external data needed
python enaqt_disorder_ensemble.py  # no external data needed, ~60s

The first script (enaqt_sb_analysis.py) requires the QD3SET-1 spin-boson dataset — download from figshare and place the .npy files in ../SB/data/.

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Reproducing the paper figures

Figure	Script	Output file
HEOM bell curves	enaqt_sb_analysis.py	enaqt_sb_analysis.png
Sink vs. no-sink	enaqt_sb_sink.py	enaqt_sink_vs_nosink.png
N-site scaling	enaqt_nsite_chain.py	enaqt_nsite_scaling.png
Disorder ensemble	enaqt_disorder_ensemble.py	enaqt_disorder_paper_figure.png

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Citation

Preprint available on bioRxiv (link forthcoming).

@article{smith2026enaqt,
  author  = {Smith, Alexander},
  title   = {Environment-Assisted Quantum Transport in Open Quantum Chains:
             Validation, Scaling Laws, and Disorder Universality},
  year    = {2026},
  note    = {bioRxiv preprint}
}

This work uses the QD3SET-1 database:

Ullah et al. (2023). Frontiers in Physics 11, 1223973. https://doi.org/10.3389/fphy.2023.1223973

And builds on the original ENAQT theory:

Rebentrost et al. (2009). New Journal of Physics 11, 033003. https://doi.org/10.1088/1367-2630/11/3/033003