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Cirq

Quantum computing framework for building, simulating, optimizing, and executing quantum circuits. Use this skill when working with quantum algorithms, quantum circuit design, quantum simulation (noiseless or noisy), running on quantum hardware (Google, IonQ, AQT, Pasqal), circuit optimization and compilation, noise modeling and characterization, or quantum experiments and benchmarking (VQE, QAOA, QPE, randomized benchmarking).

K-Dense-AI

Core Features

Ready to Use

Quick integration into your workflow with minimal setup

Community Verified

Active open-source community with continuous updates

Completely Free

MIT/Apache licensed for commercial and personal use

Flexible Extension

Customizable and extendable based on your needs

How to Use

1Get Skill File

Download or copy the skill file from the source repository

2Install to Claude

Place the skill file in Claude's skills directory (usually ~/.claude/skills/)。

3Start Using

Restart Claude or run the reload command to load the skill

Tip: Read the documentation and code carefully before first use to understand functionality and permission requirements

Related Tags

#authentication#data-analysis#documentation#git#python

Technical Information

Author
K-Dense-AI
Category
Development
File Size
10.42 KB
Source Repository
K-Dense-AI__claude-scientific-skills
Metadata
Includes YAML metadata
License
MIT

All Skills from open-source community, preserving original authors' copyrights

K-Dense-AI__claude-scientific-skills/scientific-skills/cirq/SKILL.md

Why Choose This Skill

Proven benefits and measurable impact

70%

Error Reduction

Decrease undetected errors by verifying outputs before task completion

50%

Time Saved

Save half the time spent on manual verification through automation

2x

Reliability Boost

Double deployment success rates with pre-completion checks

Use Cases

Perfect for these scenarios

🔧

System Deployment Verification

Run deployment checks and confirm service health before marking tasks complete

🧪

Code Testing Automation

Execute unit tests and verify all pass before declaring feature implementation done

📊

Data Validation Pipelines

Run validation scripts to ensure data integrity before processing analytics

🔒

Security Scan Verification

Run security scans and verify no vulnerabilities before releasing to production

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