QuantumBFS/Yao.jl

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1040 stars · 131 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Yao is an extensible, efficient open-source framework for quantum algorithm design and quantum circuit simulation written in Julia. It provides composable quantum blocks, built-in automatic differentiation, and CUDA-accelerated batched simulation for quantum information research and education.

Use cases

• simulate quantum circuits in Julia
• design and prototype quantum algorithms
• compute gradients of quantum circuits for variational algorithms
• build a quantum Fourier transform circuit
• teach quantum computing with hands-on notebooks
• run GPU-accelerated quantum circuit simulation

When to choose

• you work in Julia and need high-performance quantum circuit simulation
• you need differentiable quantum circuits for quantum machine learning research
• you want an extensible framework to define custom quantum circuit abstractions
• you are teaching or learning quantum computing with runnable examples

When to avoid

• you need to program an actual quantum computer rather than simulate one
• you prefer Python-based tools like Qiskit or Cirq
• you need large-scale tensor network simulation without the Julia ecosystem
• you require a production-stable release, as the project describes itself as early-release beta

Facets

library · maturity active

simulation machine-learning sdk quantum-computing education cross-platform quantum-circuits quantum-algorithms automatic-differentiation cuda quantum-simulation algorithms julia gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="QuantumBFS/Yao.jl")