Strawberry Fields: A Software Platform for Photonic Quantum Computing

TL;DR

Strawberry Fields is an open-source Python-based platform for designing, simulating, and optimizing photonic quantum circuits, supporting quantum machine learning and various algorithms with multiple backends.

Contribution

It introduces a comprehensive software platform for photonic quantum computing, integrating programming, simulation, and optimization tools in a unified framework.

Findings

Supports multiple specialized virtual backends

Includes implementations of key photonic quantum algorithms

Provides an accessible API for quantum programming

Abstract

We introduce Strawberry Fields, an open-source quantum programming architecture for light-based quantum computers, and detail its key features. 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 -- in the near future -- 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.