How does this skill assist with circuit optimization?

It guides you through the transpilation process, helping you select the right optimization levels (0-3) to reduce two-qubit gate counts and improve fidelity on noisy hardware.

What is the difference between Sampler and Estimator primitives?

The Sampler is used to obtain bitstrings and probability distributions, while the Estimator is designed to compute the expectation values of observables, which is essential for algorithms like VQE.

Can this skill help me run circuits on real quantum hardware?

Yes, it provides specific implementation patterns for IBM Quantum Runtime, including session management, backend selection, and hardware-aware transpilation.

Does it support quantum machine learning applications?

Absolutely. It covers Qiskit Machine Learning libraries for creating quantum kernels, variational classifiers (VQC), and quantum neural networks (QNN).

Qiskit Quantum Computing

Name: Qiskit Quantum Computing
Author: BbgnsurfTech

byBbgnsurfTech

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데이터 과학 및 ML

Builds, optimizes, and executes quantum circuits and algorithms across various hardware providers and simulators.

The Qiskit skill empowers Claude to serve as an expert assistant for quantum information science, providing deep integration with the world's most popular open-source quantum SDK. It enables the design of complex quantum circuits, implementation of variational algorithms like VQE and QAOA, and advanced hardware-specific transpilation to minimize gate errors. Whether you are conducting quantum chemistry research, developing quantum machine learning models, or executing jobs on IBM Quantum hardware, this skill provides the patterns and best practices necessary to bridge abstract quantum theory with physical execution.

주요 기능

01Rich visualization for circuits, Bloch spheres, and result histograms

02Hardware-specific transpilation and multi-level circuit optimization

03Circuit design with comprehensive single and multi-qubit gate support

04Implementation of VQE, QAOA, and Grover's quantum algorithms

05Execution on IBM Quantum Runtime, IonQ, and Amazon Braket

063 GitHub stars

사용 사례

01Developing and training quantum neural networks for machine learning

02Solving complex combinatorial optimization problems using variational algorithms

03Simulating molecular ground states and Hamiltonians for quantum chemistry

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add bbgnsurftech/claude-skills-collection qiskit

For use in Claude.ai and ChatGPT

Download Skill