Select quantum simulators across UnitaryLab, Qiskit, and PennyLane backends.
npx skills add https://github.com/unitarylab/quantum-skills --skill simulators
Please help me install this Agent Skill. Skill: simulators Source: https://github.com/unitarylab/quantum-skills/tree/main/simulators Command: npx skills add https://github.com/unitarylab/quantum-skills --skill simulators
This Skill helps users quickly identify and use the right quantum simulator (UnitaryLab, Qiskit, or PennyLane) for building, testing, and prototyping quantum programs.
Install the default UnitaryLab wheel and run a small two-qubit circuit demo.
High-intent search queries and answers about installing and using this skill.
To choose a quantum simulator, default to UnitaryLab for fast local prototyping, use Qiskit for hardware-ready cloud backends, and select PennyLane for differentiable circuits in algorithm prototyping.
Yes, Qiskit and PennyLane simulators support educational quantum computing workflows, offering clear selection rules, platform-specific installation guidance, and demo workflows for classroom use.
The best way to install a quantum simulator is using uv, pip, or conda, with the default UnitaryLab wheel recommended for quick setup to run a small two-qubit circuit demo.
Yes, UnitaryLab supports local prototyping for PDE simulations and quantum algorithms, providing fast execution before transitioning to cloud backends or hardware-ready workflows.
You should switch from a local quantum simulator to a cloud backend when moving from algorithm prototyping and educational testing to hardware-ready workflows using Qiskit.
bigbioInstall and configure SDRF annotation dependencies via Conda, Pip, or uv.
K-Dense-AIOptimize quantum circuits with automatic differentiation across simulators and hardware.
Estrella-231Design and execute quantum circuits with simulation and hardware integration.
tondevrelProvides differentiable quantum circuits for Python ML frameworks like PyTorch, TensorFlow and JAX.
