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qiskit

Build, optimize, and execute quantum circuits with Qiskit.

Updated Dec 17, 2025
Search Tags:#quantum circuits#quantum computing#qiskit#quantum algorithms#hardware execution
One-click install
npx skills add https://github.com/robotlearning123/claude-scientific-skills --skill qiskit-robotlearning123
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: qiskit
Source: https://github.com/robotlearning123/claude-scientific-skills/tree/main/scientific-skills/qiskit
Command: npx skills add https://github.com/robotlearning123/claude-scientific-skills --skill qiskit-robotlearning123

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires qiskit, numpy, scipy, matplotlib, qiskit-aer, qiskit-ibm-runtime, qiskit-nature, qiskit-machine-learning, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a comprehensive toolkit for quantum computing, enabling users to build, optimize, and execute quantum circuits, run quantum algorithms, and leverage quantum hardware for various scientific and computational tasks.

Core Features & Use Cases

  • Quantum Circuit Construction: Build quantum circuits with gates and measurements.
  • Algorithm Execution: Run quantum algorithms like VQE, QAOA, and Grover's algorithm.
  • Transpilation and Optimization: Optimize circuits for hardware execution.
  • Hardware Execution: Execute circuits on IBM Quantum or other quantum hardware providers.
  • Quantum Chemistry and Materials Science: Perform quantum chemistry and materials science computations.
  • Quantum Machine Learning: Implement quantum machine learning algorithms.
  • Visualization: Visualize circuits and results.
  • Use Case: A materials scientist can use this Skill to simulate molecular properties and optimize materials for specific applications.

Quick Start

Use the qiskit skill to run a VQE algorithm on a hydrogen molecule using the provided Hamiltonian and ansatz.

Frequently Asked Questions about qiskit

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build and optimize quantum circuits for hardware execution?▼

You can build quantum circuits using gates and measurements, then apply transpilation and optimization to prepare them for hardware execution on IBM Quantum or other quantum hardware providers.

Can I run quantum algorithms like VQE and QAOA using this framework?▼

Yes, you can execute quantum algorithms like VQE, QAOA, and Grover's algorithm using the provided algorithm execution and simulation capabilities within the quantum computing framework.

Does this toolkit support quantum chemistry and materials science simulations?▼

Yes, the framework supports quantum chemistry and materials science computations, allowing you to simulate molecular properties and optimize materials for specific scientific applications.

What libraries do I need to execute quantum machine learning algorithms?▼

To implement quantum machine learning algorithms, you need qiskit, qiskit-machine-learning, numpy, scipy, and matplotlib for algorithm implementation, numerical computation, and result visualization.

How can I visualize quantum circuits and execution results?▼

You can visualize quantum circuits and their execution results using the matplotlib library, which renders graphical representations of circuit diagrams and measurement outputs.

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