pennylane-lightning
PennyLane-Lightning plugin
Decision gist · record as of 2026-08-14
Yes. PennyLane-Lightning is a mature, actively maintained plugin with low install friction, no security vulnerabilities, and permissive licensing. Install it if you use PennyLane and need faster simulation than the default backend, especially for GPU-accelerated or distributed workloads. The CPU-only lightning.qubit backend is available on all major platforms via pip; GPU backends require appropriate hardware and drivers but are well-documented.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.11 or above.
- GPU backends (lightning.gpu, lightning.amdgpu, lightning.kokkos with CUDA/HIP) require corresponding GPU drivers and toolkits; most are available via pip for common platforms, but some require source builds.
- Low installation friction with a pure-wheel distribution.
License · maintenance · safety
Apache-2.0 (permissive) — Released under Apache License 2.0 (permissive), allowing commercial use and modification. GPU backends use NVIDIA cuQuantum SDK headers under their own respective licenses.
last release 2026-05-12 (94 days) · last repo commit 2026-08-14 · 144 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 749,420 downloads/mo, #5,161 on PyPI
Alternatives
Verify before relying
pip install pennylane-lightning
import pennylane as pnl
dev = pnl.device('lightning.qubit', wires=2)
@pnl.qnode(dev)
def circuit():
pnl.PauliX(wires=0)
return pnl.expval(pnl.PauliZ(0))
print(circuit())- Performance benchmarks comparing lightning.qubit, lightning.gpu, and lightning.tensor backends on typical workloads.
- Whether scipy-openblas32 is automatically installed or must be explicitly configured for optimal performance.
- Compatibility and performance characteristics of MPI-enabled backends on specific HPC clusters.
What it is and what it does
PennyLane-Lightning is a plugin that extends PennyLane with fast quantum simulators written in C++. It provides multiple backends: lightning.qubit for CPU-based state-vector simulation with optional OpenMP parallelization, lightning.kokkos for multi-platform parallelism (OpenMP, CUDA, HIP, MPI), lightning.gpu for NVIDIA GPU acceleration via cuQuantum SDK, lightning.amdgpu for AMD GPUs, and lightning.tensor for tensor-network simulation. The package depends on PennyLane and scipy-openblas32, and is designed to accelerate hybrid quantum-classical computations on modern hardware from laptops to HPC clusters.
You install it as a PennyLane device plugin and select a backend (e.g., 'lightning.qubit' or 'lightning.gpu') when creating a device. Most backends are available via pip for Linux x86, Linux ARM, macOS ARM, and Windows; GPU and MPI variants may require source builds on some platforms. The plugin is actively maintained, supports Python 3.11 and above, and has no known security vulnerabilities.
Use it for
- Accelerate quantum machine learning training by using GPU-backed simulation instead of CPU-only backends.
- Run large-scale quantum circuit simulations on HPC clusters using MPI-distributed state-vector backends.
- Prototype quantum algorithms with fast state-vector simulation on consumer hardware before deploying to quantum hardware.
- Simulate tensor-network quantum circuits using Matrix Product State or Exact Tensor Network methods for structured problems.
- Develop hybrid quantum-classical optimization loops where the simulator is the bottleneck and GPU acceleration is needed.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
PennyLane-Lightning is a mature, actively maintained plugin with low install friction, no security vulnerabilities, and permissive licensing. Install it if you use PennyLane and need faster simulation than the default backend, especially for GPU-accelerated or distributed workloads. The CPU-only lightning.qubit backend is available on all major platforms via pip; GPU backends require appropriate hardware and drivers but are well-documented.
Install
pennylane-lightning on PyPI
Before you install
Low installation friction with a pure-wheel distribution. Actively maintained with recent commits and a stable release cadence; supports current Python versions (3.11+).
Requires Python 3.11 or above. GPU backends (lightning.gpu, lightning.amdgpu, lightning.kokkos with CUDA/HIP) require corresponding GPU drivers and toolkits; most are available via pip for common platforms, but some require source builds.
License in practice
Released under Apache License 2.0 (permissive), allowing commercial use and modification. GPU backends use NVIDIA cuQuantum SDK headers under their own respective licenses.
Quickstart
pip install pennylane-lightning
import pennylane as pnl
dev = pnl.device('lightning.qubit', wires=2)
@pnl.qnode(dev)
def circuit():
pnl.PauliX(wires=0)
return pnl.expval(pnl.PauliZ(0))
print(circuit())Verify before relying
- Performance benchmarks comparing lightning.qubit, lightning.gpu, and lightning.tensor backends on typical workloads.
- Whether scipy-openblas32 is automatically installed or must be explicitly configured for optimal performance.
- Compatibility and performance characteristics of MPI-enabled backends on specific HPC clusters.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagespennylanescipy-openblas32 |
| Maintenance | Actively maintained 94 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 749,420 / month, #5,161 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaEnvironment :: ConsoleIntended Audience :: Science/ResearchNatural Language :: EnglishOperating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsOperating System :: POSIXOperating System :: POSIX :: LinuxProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering :: Physics |
Evidence: pennylane_lightning-0.45.0-py3-none-any.whl
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See also pennylane · custatevec-cu12 · quimb · custatevec-cu13 · cudensitymat-cu13 · cutensornet-cu13 · amazon-braket-default-simulator · cirq-core · tensorrt-cu12-libs · qiskit-aer