Quantum technology with Cirq
Hybrid quantum–classical experiments built on Google's open-source Cirq framework: noise-aware circuits, QAOA optimisation, and chemistry simulations run on qsim today and ready for real quantum hardware tomorrow.
Cirq, Python, qsim, OpenFermion, Quantum computing
Practical quantum experiments built on Cirq, Google Quantum AI’s open-source Python framework for writing, simulating, and running circuits on today’s noisy intermediate-scale quantum (NISQ) processors. The goal is not quantum hype: it is a hybrid quantum–classical toolkit that shows, with honest benchmarks, where a quantum routine helps and where a classical solver still wins.
What I’ll build
- Typed circuit library: parameterised ansätze, moments, and device-aware gate sets.
- Noise-aware simulation with realistic depolarising and readout-error models.
- QAOA optimiser for scheduling, routing, and portfolio-style combinatorial problems.
- VQE chemistry runs via OpenFermion for small-molecule ground-state energies.
- Classical baselines (exact and heuristic) reported side by side with every quantum result.
- Error-mitigation passes (readout correction, zero-noise extrapolation) behind one interface.
- Hardware-ready transpilation so the same circuits can target real quantum processors when access is available.
Architecture
A Python service owns problem encoding, the classical optimiser loop, and result storage. Circuits are composed in Cirq, compiled to a device gate set, then executed on qsim, Google’s high-performance C++ state-vector simulator, through qsimcirq. A thin API lets product teams or AI agents submit an optimisation job and receive both the quantum and classical answers with cost and fidelity metadata.
Stack: Python 3.12 · Cirq · qsim / qsimcirq · OpenFermion · NumPy · SciPy · FastAPI · Postgres
Roadmap
- Circuit library, noise models, and qsim benchmarks published as notebooks.
- QAOA on real scheduling and routing datasets, with classical baselines.
- VQE chemistry examples with OpenFermion and error mitigation.
- Job API so agents and backends can call quantum routines like any other service.
- Runs on real quantum hardware through partner or cloud access programmes.
Interested? Research teams, logistics or materials companies, and quantum-curious founders — email contact@imaddhin.com.