Trainability and Expressivity of Hamming-Weight Preserving Quantum Circuits for Machine Learning
Quantum machine learning (QML) has become a promising area for real world applications of quantum computers, but near-term methods and their scalability are still important research topics. In this context, we analyze the trainability and controllability of specific Hamming weight preserving variati...
| الحاوية / القاعدة: | Quantum |
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| المؤلفون الرئيسيون: | , , , , , |
| التنسيق: | مقال |
| اللغة: | الإنجليزية |
| منشور في: |
Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften
2025-05-01
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| الوصول للمادة أونلاين: | https://quantum-journal.org/papers/q-2025-05-15-1745/pdf/ |