Strawberry Fields is a full-stack Python library for designing, simulating, and optimizing continuous-variable quantum optical circuits.
Strawberry Fields has following features:
- Execute photonic quantum algorithms directly on Xanadu’s next-generation quantum hardware
- High-level functions for solving practical problems including graph and network optimization, machine learning, and chemistry
- Includes a suite of world-class simulators—based on cutting-edge algorithms—to compile and simulate photonic algorithms
- Train and optimize your quantum programs with our end-to-end differentiable TensorFlow backend
- Powers the Strawberry Fields Interactive web app, which allows anyone to run a quantum computing simulation via drag and drop
Strawberry Fields is ideal for studying existing algorithms, or quickly prototyping new ideas and breakthroughs. It is also used for exploration and design of novel quantum circuits. Built-in Tensorflow support and deep learning allows to design and optimize circuits.
Strawberry Fields is available through Interactive web application. You can prepare initial states, drag and drop gates, and watch your simulation run in real time right in your web browser. To take full advantage of Strawberry Fields, however, it is required to install Python library. Built in Python, Strawberry Fields is a full-stack library for design, simulation, optimization, and quantum machine learning of continuous-variable circuits.
The platform consists of three main components: (i) an API for quantum programming based on an easy-to-use language named Blackbird; (ii) a suite of three virtual quantum computer backends, built in NumPy and TensorFlow, each targeting specialized uses; and (iii) an engine which can compile Blackbird programs on various backends, including the three built-in simulators, and photonic quantum information processors.
The library also contains examples of several paradigmatic algorithms, including teleportation, (Gaussian) boson sampling, instantaneous quantum polynomial, Hamiltonian simulation, and variational quantum circuit optimization.