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OpenQML

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OpenQML is a Python library for hybrid quantum-classical learning and quantum circuit interoperability.

Features

  • Trainable quantum layers for PyTorch and JAX, with native automatic differentiation.
  • Circuit conversion across Qiskit, PennyLane, Cirq and OpenQASM, with explicit semantic verification.
  • Resource-aware execution, sparse Pauli propagation, quantum geometry and measurement estimation.

Installation

Requires Python 3.10 or later.

python -m pip install openqml
import openqml as oq

The core depends on NumPy, packaging and psutil. Optional framework integrations are available through extras such as openqml[torch], openqml[jax] and openqml[all].

Documentation

Architecture · Semantic verification · Scalable execution · Research methods

There is no fixed total circuit-width ceiling. Execution remains subject to representation, memory and work budgets. Approximation is opt-in and reports its bounds.

License

Apache License 2.0.

Metadata

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