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0108860bff
Create comprehensive research-lab pack structure with mathematical and quantum computing modules from blackroad-prism-console: Math Modules: - hilbert_core.py: Hilbert space symbolic reasoning - collatz/: Distributed Collatz conjecture verification - linmath/: Linear mathematics C library - lucidia_math_forge/: Symbolic proof engine - lucidia_math_lab/: Experimental mathematics Quantum Modules: - lucidia_quantum/: Quantum core - quantum_engine/: Circuit simulation Experiments: - br_math/: Gödel gap, quantum experiments Includes pack.yaml manifest and comprehensive README. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
27 lines
750 B
Python
27 lines
750 B
Python
"""Quantum kernel utilities."""
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from __future__ import annotations
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from typing import Any, Optional
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import numpy as np
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from qiskit_machine_learning.algorithms import PegasosQSVC
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from qiskit_machine_learning.kernels import QuantumKernel
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from .backends import AerCPUBackend, QuantumBackend
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def fit_qsvc(
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x: np.ndarray,
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y: np.ndarray,
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kernel_opts: Optional[dict[str, Any]] = None,
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backend: Optional[QuantumBackend] = None,
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) -> PegasosQSVC:
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"""Train a PegasosQSVC on the given data using a local quantum kernel."""
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backend = backend or AerCPUBackend()
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kernel = QuantumKernel(quantum_instance=backend.simulator, **(kernel_opts or {}))
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model = PegasosQSVC(quantum_kernel=kernel)
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model.fit(x, y)
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return model
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