Learn STRAWBERRY-FIELDS with Real Code Examples

Python-based SDK for CV quantum circuits

Backends for Fock, Gaussian, and TensorFlow simulations

Integration with PennyLane for hybrid algorithms

Modular design for gate operations and measurements

Tools for visualization and analysis of quantum states

Python-based high-level circuit API

Backends for Fock, Gaussian, and TensorFlow simulation

Visualization of quantum states and measurement outcomes

Integration with classical ML workflows

Cloud and hardware backend execution support

Separation of circuit definition and execution

Modular design for gates and measurements

Backend-agnostic simulation and hardware execution

Integration with hybrid quantum-classical pipelines

Extensible for photonic quantum algorithm research

Gaussian boson sampling experiments

Variational quantum algorithms for ML

Photonic quantum teleportation protocols

Hybrid quantum-classical optimization pipelines

Quantum state tomography and analysis

Enable photonic continuous-variable quantum programming

Support hybrid quantum-classical workflows

Provide flexible, modular Python API

Facilitate research in quantum algorithms and ML

Abstract hardware complexity while supporting backend execution

Use Gaussian backends for large-scale circuits

Limit Fock cutoff dimensions for efficient simulation

Batch execution for hybrid classical-quantum experiments

Optimize gate sequences to reduce resource consumption

Monitor backend performance and execution time

Update Strawberry Fields via pip

Check API changes for backends and gate definitions

Update example scripts and notebooks as needed

Validate circuits on simulator before hardware execution

Ensure reproducible results after upgrade