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Quantum Machine Learning with Pennylane and Qulacs: A Comparative Study

Discover how to use Pennylane and Qulacs for quantum machine learning, including quantum circuit learning and quantum k-means clustering. Learn about the strengths and weaknesses of each library and how to choose the best tool for your specific use case.

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NextGenBeing Founder

NextGenBeing Founder

Dec 14, 2025 1 views
Quantum Machine Learning with Pennylane and Qulacs: A Comparative Study
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Introduction to Quantum Machine Learning

My team and I have been exploring the applications of quantum machine learning for the past year. Last quarter, we discovered that our quantum circuits were losing coherence at scale. We tried surface codes first - complete failure. Here's what we learned about using Pennylane and Qulacs for quantum circuit learning and quantum k-means clustering.

Background on Pennylane and Qulacs

Pennylane is an open-source software framework for quantum machine learning, while Qulacs is a high-performance simulator for quantum many-body systems. Both libraries have their strengths and weaknesses. I realized that Pennylane is better suited for quantum circuit learning due to its intuitive API, while Qulacs excels at simulating large quantum systems.

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