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style: apply challenger ordering and entry format to Quantum Computing

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Per ADR-0001, maintainer-adjudicated at the Data & Science preview
review (2026-08-15). No removals — all four entries keep: qiskit and
qutip as Obvious Choices (circuit SDK and quantum physics simulation,
distinct jobs), cirq and pennylane as Challengers, ordered per the
Challenger-ordering rule. Format fixes bundled per the Key Rules
bundling exception: three em-dash separators normalized to hyphens,
Cirq lowercased to its PyPI name.

Co-Authored-By: Claude <noreply@anthropic.com>
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Vinta Chen
2026-08-15 23:59:21 +08:00
co-authored by Claude
parent 0c1409dea8
commit c9abd51467
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README.md
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@@ -566,10 +566,10 @@ _Libraries for scientific computing. Also see [Python-for-Scientists](https://gi
_Libraries for quantum computing._ _Libraries for quantum computing._
- [Cirq](https://github.com/quantumlib/Cirq) — A Google-developed framework focused on hardware-aware quantum circuit design for NISQ devices. - [qiskit](https://github.com/Qiskit/qiskit) - An IBM-backed quantum SDK for building, simulating, and running circuits on real quantum hardware.
- [pennylane](https://github.com/PennyLaneAI/pennylane) — A hybrid quantum-classical machine learning library with automatic differentiation support.
- [qiskit](https://github.com/Qiskit/qiskit) — An IBM-backed quantum SDK for building, simulating, and running circuits on real quantum hardware.
- [qutip](https://github.com/qutip/qutip) - Quantum Toolbox in Python. - [qutip](https://github.com/qutip/qutip) - Quantum Toolbox in Python.
- [cirq](https://github.com/quantumlib/Cirq) - A Google-developed framework focused on hardware-aware quantum circuit design for NISQ devices.
- [pennylane](https://github.com/PennyLaneAI/pennylane) - A hybrid quantum-classical machine learning library with automatic differentiation support.
**Developer Tools** **Developer Tools**