Status: Active · Ongoing citizen science research
Started: May 2026
Maintainer: @berniepng
This repository documents a long-term independent research programme exploring a central question:
Can quantum computing help us decode the quantum mechanics of photosynthesis — and use those principles to engineer artificial systems that convert greenhouse gases into useful molecules?
This sits at the intersection of quantum biology, quantum chemistry simulation, and climate technology. The research is conducted as a citizen scientist — no institutional affiliation, no lab access — using open datasets, open-source tools, and publicly available quantum hardware.
This README is a living document. It will evolve as new findings, papers, companies, and experiments are added.
- Problem Statement
- Current Landscape
- How Quantum Computing Can Help
- Prototype: Citizen Science Simulation
- Repo Structure
- Roadmap
- Contributing & Notes
- Learning Log
Global warming is driven by the accumulation of greenhouse gases — primarily CO₂ — in the atmosphere. Nature already has a near-perfect solution: photosynthesis, a process that has been converting CO₂ and sunlight into useful organic molecules for approximately 3.5 billion years.
What makes photosynthesis remarkable is not just its chemistry — it's the efficiency of its energy transfer. Light-harvesting complexes in plants and bacteria transfer absorbed solar energy to reaction centres with near-100% quantum yield. Emerging evidence suggests this isn't classical physics at work. Quantum mechanical effects — coherence, superposition, and possibly entanglement — appear to play a functional role in making this energy transfer so efficient.
The central hypothesis of this research programme:
If we can decode the quantum mechanical principles behind photosynthetic energy transfer, and simulate those principles using quantum computers, we can design artificial molecular systems that replicate and exceed nature's efficiency — and use them to upcycle CO₂ and other greenhouse gases into valuable molecules (fuels, plastics, chemicals).
This is not a single solved problem. It is three interconnected frontiers:
| Layer | Question | Status |
|---|---|---|
| Quantum Biology | Do quantum effects meaningfully drive photosynthesis efficiency? | Confirmed experimentally; functional significance debated |
| Quantum Simulation | Can quantum computers model these molecular dynamics? | Demonstrated at small scale (IBM Q, 2020) |
| Artificial Photosynthesis | Can we engineer CO₂ → useful molecules systems? | Commercially operational (no quantum design layer yet) |
The gap this research explores: using quantum computing to close the loop between biological insight and engineered CO₂ conversion.
| Paper | Authors | Year | Significance | Link |
|---|---|---|---|---|
| Evidence for wavelike energy transfer through quantum coherence in photosynthetic systems | Engel, Fleming et al. | 2007 | First experimental evidence of quantum coherence in FMO complex at 77K | Nature 446, 782–786 |
| Long-lived quantum coherence in photosynthetic complexes at physiological temperature | Panitchayangkoon, Engel et al. | 2010 | Extended quantum coherence observed at room temperature | PNAS 107, 12766 |
| Environment-assisted quantum transport | Rebentrost, Mohseni, Lloyd, Aspuru-Guzik | 2009 | Showed environmental noise assists rather than disrupts quantum transport | New J. Phys. 11, 033003 |
| Quantum biology revisited | Cao, Cogdell, Engel, Scholes et al. | 2020 | Critical reassessment of the field; honest review of what is/isn't proven | Science Advances |
| Simulation of non-radiative energy transfer in photosynthetic systems using a quantum computer | Guimarães, Tavares, Vasilevskiy | 2020 | Key paper: FMO energy transfer simulated on IBM Q 5-qubit computer | arXiv:2009.01283 |
| Reassessing the role and lifetime of Qx in chlorophyll a energy transfer | Keil, Hauer et al. | 2024 | Quantum superposition shown as first stage of energy transfer in chlorophyll | Chemical Science, RSC |
| Full microscopic simulations uncover persistent quantum effects in primary photosynthesis | — | 2025 | Most recent confirmation of persistent quantum effects | Science Advances |
| Artificial photosynthetic processes using CO₂, water and sunlight | — | 2025 | Comprehensive review of solar-driven CO₂ reduction | RSC Chemical Science |
| Artificial photosynthesis catalyst converts CO₂ to methane | In, Powar et al. | 2025 | Photocatalyst converting CO₂ → methane at atomic-level detail, quantum mechanical calculations | ACS Catalysis |
| Recent Progress in Designing Nanomaterial Biohybrids for Artificial Photosynthesis | Jeevanandham et al. | 2025 | Nanomaterial hybrids combining photocatalysts with biological enzymes; quantum efficiency exceeding 20% | NCBI / Nanomaterials |
| Resource | Use | Link |
|---|---|---|
| RCSB Protein Data Bank | FMO complex structure (PDB: 3ENI), chlorophyll proteins |
rcsb.org |
| PubChem | Molecular data for photocatalysts, chlorophyll, CO₂ reduction catalysts | pubchem.ncbi.nlm.nih.gov |
| ChEMBL | Bioactive molecule and catalyst screening | ebi.ac.uk/chembl |
| NIST Chemistry WebBook | Molecular spectroscopy and thermochemical data | webbook.nist.gov |
| IBM Quantum Network | Free access to real quantum hardware for simulation experiments | quantum.ibm.com |
| Company | Focus | Stage | Notable | Link |
|---|---|---|---|---|
| Twelve (formerly Opus 12) | Industrial photosynthesis: CO₂ + water + renewable electricity → hydrocarbons, jet fuel, polymers | Commercial | $187M raised; backed by DCVC, Chan Zuckerberg Initiative; working with Mercedes-Benz, aviation sector | twelve.co |
| Quantinuum | Quantum computing + quantum chemistry simulation | Commercial | Helios platform; active chemistry simulation programs | quantinuum.com |
| IBM Quantum | Quantum hardware + open access platform | Commercial | Free tier available; FMO simulation already demonstrated on IBM Q | quantum.ibm.com |
| Google Quantum AI | Quantum hardware, quantum chemistry | Research/Commercial | Cirq open source framework; collaborations with quantum chemistry groups | quantumai.google |
| PsiQuantum | Photonic quantum computing | Pre-commercial | $1B raised (2025); photon-based qubits relevant to photosynthesis-inspired architectures | psiquantum.com |
| Panasonic / Toyota R&D / Mitsubishi Chemical / Fujitsu / Toshiba | Artificial photosynthesis R&D | Corporate R&D | Major players in the $109M (2026) and growing artificial photosynthesis market | Various |
| Institution | Programme | Link |
|---|---|---|
| Joint Center for Artificial Photosynthesis (JCAP) | Lawrence Berkeley National Lab / Caltech — largest US government-funded artificial photosynthesis programme | solarfuelshub.org |
| Cyclotron Road / Activate | Lawrence Berkeley National Lab fellowship that incubated Twelve (formerly Opus 12) | activate.org |
| University of Toronto | Aspuru-Guzik lab — quantum computing + quantum chemistry, molecular machine learning | matter.toronto.edu |
| University of Chicago | Engel lab — 2D electronic spectroscopy of photosynthetic systems | chemistry.uchicago.edu |
| UC Berkeley | Fleming lab — quantum biology, ultrafast spectroscopy | lb.berkeley.edu |
| MIT | Seth Lloyd group — quantum transport theory | mit.edu |
| TU Munich | Hauer lab — quantum mechanics in photosynthesis (2024 Chemical Science paper) | tum.de |
| University of Gothenburg | Westenhoff group — critical analysis of quantum coherence claims | gu.se |
| Name | Institution | Contribution | Notable Work |
|---|---|---|---|
| Graham Fleming | UC Berkeley | Godfather of quantum photosynthesis; led 2007 Nature paper establishing quantum coherence in FMO | Scholar |
| Gregory Engel | University of Chicago | Extended coherence to room temperature; 2D electronic spectroscopy methods | Lab |
| Alán Aspuru-Guzik | University of Toronto | Bridge between quantum biology and quantum computing; molecular ML; computational coherence modeling | Lab |
| Seth Lloyd | MIT | Quantum transport theory; environment-assisted quantum walks; coined "quantum hanky-panky" | MIT |
| Gregory Scholes | Princeton | Observed quantum coherence in cryptophyte algae at ambient conditions | Scholar |
| Jürgen Hauer | TU Munich | 2024 discovery of quantum superposition as first stage of chlorophyll energy transfer | TUM |
| Etosha Cave | Twelve (co-founder) | Stanford PhD; developed photosynthesis-mimicking CO₂ reduction catalysts, co-founded Twelve | Twelve |
| Kendra Kuhl | Twelve (co-founder, CTO) | Stanford PhD; core catalyst engineering behind Twelve's CO₂ electrolyser technology | Twelve |
| Sebastian Westenhoff | University of Gothenburg | Critical perspective: argues quantum coherence in natural photosynthesis may be misinterpreted — essential counterbalance | Scholar |
Classical computers struggle to simulate quantum mechanical systems because the state space grows exponentially with the number of interacting particles. A system of N quantum particles requires 2^N classical bits to represent — which becomes intractable fast.
Photosynthetic systems are exactly this kind of problem. The Fenna-Matthews-Olson (FMO) complex — the most studied quantum photosynthetic structure — involves 7–8 coupled chlorophyll molecules whose excitation dynamics are governed by quantum mechanics. To understand why nature achieves near-100% energy transfer efficiency, you need to simulate these quantum dynamics accurately.
Quantum computers can simulate quantum systems natively — using qubits to directly represent quantum states, reducing exponential classical cost to polynomial quantum cost.
- The Haken-Ströbl model of FMO energy transfer has been simulated on IBM Q (5 qubits), validating quantum coherence dynamics against analytical results (Guimarães et al., 2020)
- Variational Quantum Eigensolver (VQE) algorithms have been applied to molecular ground-state problems relevant to photocatalyst design
- Aspuru-Guzik's group has pioneered quantum algorithms for simulating vibronic spectra and molecular energy landscapes
- Scale up FMO simulation — current 5-qubit demos are proof-of-concept; full FMO requires ~50+ logical qubits
- Design new photocatalysts — use quantum chemistry simulation to screen novel molecular configurations for CO₂ reduction efficiency
- Optimize reaction pathways — quantum ML to predict which CO₂ → molecule conversion pathways are most energetically favourable
- Close the loop — feed quantum simulation insights back into materials synthesis guidance
| Algorithm | Application |
|---|---|
| VQE (Variational Quantum Eigensolver) | Ground state energy of photocatalyst molecules |
| QAOA (Quantum Approximate Optimisation) | Reaction pathway optimisation |
| Quantum Walks | Energy transfer simulation in FMO |
| Lindblad Master Equation (open quantum systems) | Simulating decoherence effects in biological environments |
No lab. No institutional access. No experimental equipment. But the mathematics of quantum photosynthesis is open, documented, and runnable on free platforms — including real quantum hardware.
The goal of this prototype track is:
- Reproduce published results (credibility baseline)
- Explore parameter space computationally (hypothesis generation)
- Visualise findings to build intuition (communication)
- Identify anomalies or questions worth investigating further
| Layer | Tool | Purpose | Cost |
|---|---|---|---|
| Quantum simulation | QuTiP | Open quantum systems, Lindblad dynamics, FMO model | Free |
| Quantum hardware | IBM Quantum | Run circuits on real quantum computers | Free tier |
| Quantum circuits | Qiskit | Build and simulate quantum algorithms | Free |
| Molecular data | RDKit | Cheminformatics, molecular fingerprinting | Free |
| Protein structure | RCSB PDB + PyMol | Visualise FMO complex structure | Free |
| ML on molecules | DeepChem / ChemBERTa | Predict catalyst properties from molecular structure | Free |
| Visualisation | Streamlit + Plotly | Interactive dashboards for simulation results | Free |
| Environment | Jupyter / Google Colab | Notebooks, free GPU | Free |
Milestone 1 — Reproduce FMO energy transfer (QuTiP, Haken-Ströbl model)
↓
Milestone 2 — Run FMO simulation on IBM Q (Qiskit, replicate Guimarães 2020)
↓
Milestone 3 — Fetch FMO structure from PDB, visualise with PyMol / 3Dmol.js
↓
Milestone 4 — Screen CO₂ reduction catalysts using RDKit + DeepChem ML
↓
Milestone 5 — Build Streamlit dashboard connecting simulations + visualisations
↓
Milestone 6 — Run VQE on a small photocatalyst molecule (H₂O, CO₂ fragments)
↓
Milestone 7 — Publish findings and open hypothesis log
# Clone this repo
git clone https://github.com/berniepng/decoding-photosynthesis.git
cd decoding-photosynthesis
# Install core dependencies
pip install qutip qiskit qiskit-ibm-runtime rdkit deepchem streamlit plotly numpy matplotlib
# Run first experiment: FMO Haken-Ströbl simulation
jupyter notebook notebooks/01_fmo_haken_strobl.ipynbIBM Quantum free account: quantum.ibm.com
Google Colab (no install needed): colab.research.google.com
decoding-photosynthesis/
│
├── README.md ← This file (living document)
│
├── notebooks/ ← Jupyter notebooks, numbered by milestone
│ ├── 01_fmo_haken_strobl.ipynb ← Milestone 1: Classical quantum sim of FMO
│ ├── 02_ibmq_fmo_circuit.ipynb ← Milestone 2: IBM Q circuit implementation
│ ├── 03_pdb_structure_viz.ipynb ← Milestone 3: FMO protein structure
│ └── 04_catalyst_screening.ipynb ← Milestone 4: ML catalyst screening
│
├── src/
│ ├── models/ ← Quantum system models (Hamiltonians, Lindbladians)
│ ├── utils/ ← Data loaders, PDB parsers, molecule utilities
│ └── visualization/ ← Reusable plot and dashboard components
│
├── experiments/
│ ├── fmo_simulation/ ← FMO energy transfer experiments
│ ├── co2_catalysts/ ← CO₂ catalyst screening experiments
│ └── quantum_circuits/ ← Qiskit circuit experiments
│
├── data/
│ ├── raw/ ← Downloaded PDB files, molecular datasets
│ ├── processed/ ← Cleaned, transformed data
│ └── references/ ← Downloaded papers (PDFs), notes
│
├── results/
│ └── figures/ ← Output plots and visualisations
│
├── docs/
│ ├── hypothesis_log.md ← Running log of hypotheses and questions
│ ├── reading_list.md ← Papers read, annotated
│ └── glossary.md ← Key terms and definitions
│
├── requirements.txt ← Python dependencies
├── environment.yml ← Conda environment spec
└── .gitignore
- Milestone 1 — Reproduce Haken-Ströbl FMO energy transfer in QuTiP
- Milestone 2 — Run FMO quantum circuit on IBM Q (replicate Guimarães 2020)
- Milestone 3 — Visualise FMO protein structure from PDB
- Milestone 4 — Screen CO₂ catalysts with RDKit + ML
- Milestone 5 — Streamlit dashboard: energy transfer + molecule viewer
- Milestone 6 — VQE experiment on CO₂ / H₂O molecular fragments
- Milestone 7 — Publish hypothesis log and invite collaboration
- (Future) — Connect quantum simulation outputs to catalyst design suggestions
- (Future) — Benchmark artificial photosynthesis efficiency vs. natural FMO
This is an independent, open research log. If you're a researcher, student, or fellow citizen scientist working in quantum biology, artificial photosynthesis, or quantum chemistry simulation — feel free to open an issue, submit a PR, or reach out.
Ethos: Rigorous curiosity. No institutional gatekeeping. Open science.
Last updated: May 2026