Does it support real quantum hardware execution?

Yes, it provides implementation patterns for IBM Quantum Runtime, including session management, batching, and hardware-specific optimization.

Can I use this for quantum chemistry simulations?

Absolutely. The skill includes guidance for quantum chemistry and materials science applications, specifically using the Estimator primitive for expectation values.

What quantum tasks can this skill help with?

It assists with building circuits, transpiling for specific hardware, running algorithms like VQE/QAOA, and analyzing results from simulators or real quantum computers.

How does it handle result visualization?

The skill provides code patterns for generating circuit diagrams, Bloch spheres, and result histograms using Matplotlib and Qiskit visualization tools.

Does it help with circuit optimization?

Yes, it covers all four optimization levels of the Qiskit transpiler to reduce gate counts and improve fidelity on noisy hardware (NISQ).

Qiskit Quantum Computing

Name: Qiskit Quantum Computing
Author: pur3v4d3r

bypur3v4d3r

•

데이터 과학 및 ML

Accelerates quantum circuit development, hardware transpilation, and algorithm execution using the industry-standard Qiskit SDK.

소개

The Qiskit skill provides specialized expertise for developing quantum computing solutions using the world's most popular open-source framework. It guides developers through the entire 'Qiskit Patterns' workflow—from mapping problems to circuits and optimizing them for specific hardware to executing via Runtime Primitives and post-processing results. Perfect for researchers and engineers working on quantum chemistry, optimization, or machine learning, this skill ensures best practices for transpilation and efficient hardware utilization on IBM Quantum and other providers.

주요 기능

Execution via Qiskit Runtime Primitives including Sampler and Estimator
Quantum circuit construction with universal gate sets and measurements
1 GitHub stars
Specialized algorithm support for VQE, QAOA, and Quantum ML
Comprehensive visualization for circuits, histograms, and state vectors
Advanced hardware transpilation and multi-level circuit optimization

사용 사례

Implementing and training quantum machine learning models
Optimizing circuits for execution on real IBM Quantum hardware backends
Designing and simulating quantum algorithms for optimization and chemistry

소개

주요 기능

Execution via Qiskit Runtime Primitives including Sampler and Estimator
Quantum circuit construction with universal gate sets and measurements
1 GitHub stars
Specialized algorithm support for VQE, QAOA, and Quantum ML
Comprehensive visualization for circuits, histograms, and state vectors
Advanced hardware transpilation and multi-level circuit optimization

사용 사례

Implementing and training quantum machine learning models
Optimizing circuits for execution on real IBM Quantum hardware backends
Designing and simulating quantum algorithms for optimization and chemistry