Learn STRAWBERRY-FIELDS with Real Code Examples
Updated Nov 25, 2025
Practical Examples
Simulate single-mode squeezing
Construct and run a Gaussian boson sampling circuit
Implement a variational quantum circuit for machine learning
Perform CV quantum teleportation simulation
Analyze quantum state statistics and measurement outcomes
Troubleshooting
Verify correct number of modes matches gate definitions
Ensure backend dependencies are installed
Check integration with PennyLane or ML libraries
Debug with simple Gaussian circuits first
Validate measurement results against expected theory
Testing Guide
Simulate circuits with small number of modes first
Validate gate sequences and measurement results
Compare Gaussian vs Fock simulations
Visualize state distributions and probabilities
Check reproducibility with fixed random seeds
Deployment Options
Run experiments locally using Fock or Gaussian simulators
Use TensorFlow backend for differentiable quantum programming
Integrate with PennyLane for hybrid ML pipelines
Deploy variational circuits on photonic hardware backends
Automate experiments using Python scripts
Tools Ecosystem
Strawberry Fields Core - circuit construction and execution
Simulators - Fock, Gaussian, and TensorFlow backends
PennyLane Integration - hybrid quantum-classical ML
Quantum state analysis and visualization tools
Resource estimation modules for large photonic circuits
Integrations
Python scientific libraries (NumPy, SciPy, Matplotlib)
TensorFlow and PyTorch for automatic differentiation
PennyLane for hybrid quantum-classical workflows
Integration with Jupyter notebooks for interactive experimentation
Classical optimization frameworks for variational algorithms
Productivity Tips
Start with Gaussian circuits before non-Gaussian
Use Jupyter notebooks for interactive testing
Cache simulation results for large circuits
Leverage PennyLane for hybrid ML workflows
Visualize quantum states for debugging and analysis
Challenges
Understanding continuous-variable quantum mechanics
Optimizing simulation for large mode numbers
Integrating classical machine learning with quantum circuits
Analyzing non-Gaussian quantum states
Bridging theory and experimental photonic hardware