تقرير
Efficient Learning of Quantum States Prepared With Few Non-Clifford Gates II: Single-Copy Measurements
| العنوان: | Efficient Learning of Quantum States Prepared With Few Non-Clifford Gates II: Single-Copy Measurements |
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| المؤلفون: | Grewal, Sabee, Iyer, Vishnu, Kretschmer, William, Liang, Daniel |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science Quantum Physics |
| مصطلحات موضوعية: | Quantum Physics, Computer Science - Machine Learning |
| الوصف: | Recent work has shown that $n$-qubit quantum states output by circuits with at most $t$ single-qubit non-Clifford gates can be learned to trace distance $\epsilon$ using $\mathsf{poly}(n,2^t,1/\epsilon)$ time and samples. All prior algorithms achieving this runtime use entangled measurements across two copies of the input state. In this work, we give a similarly efficient algorithm that learns the same class of states using only single-copy measurements. Comment: This work has been merged into arXiv:2305.13409 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2308.07175 |
| رقم الأكسشن: | edsarx.2308.07175 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |