quantum-kernel-estimator

Development

Quantum kernel computation skill for quantum machine learning

QUICK START

How to use this skill

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Source SKILL.md: https://github.com/a5c-ai/babysitter/blob/HEAD/library/specializations/domains/science/quantum-computing/skills/quantum-kernel-estimator/SKILL.md

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Quantum Kernel Estimator

Purpose

Provides expert guidance on quantum kernel methods for machine learning, enabling kernel-based classifiers and regressors with quantum feature maps.

Capabilities

Fidelity quantum kernel
Projected quantum kernel
Kernel alignment optimization
Feature map design
SVM integration with quantum kernels
Kernel matrix visualization
Bandwidth tuning
Trainable kernel circuits

Usage Guidelines

Feature Map Selection: Design quantum feature map for data encoding
Kernel Computation: Calculate kernel matrix entries via circuit execution
Alignment Optimization: Tune kernel for target classification task
SVM Training: Use quantum kernel with classical SVM solvers
Performance Evaluation: Assess classification accuracy and quantum advantage

Tools/Libraries

Qiskit Machine Learning
PennyLane
scikit-learn
CVXPY
NumPy