Efficient Learning of Quantum States Prepared With Few Non-Clifford Gates II: Single-Copy Measurements
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2023
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866916193902788608 |
|---|---|
| author | Grewal, Sabee Iyer, Vishnu Kretschmer, William Liang, Daniel |
| author_facet | Grewal, Sabee Iyer, Vishnu Kretschmer, William Liang, Daniel |
| contents | 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 $ε$ using $\mathsf{poly}(n,2^t,1/ε)$ 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2308_07175 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Efficient Learning of Quantum States Prepared With Few Non-Clifford Gates II: Single-Copy Measurements Grewal, Sabee Iyer, Vishnu Kretschmer, William Liang, Daniel Quantum Physics Machine Learning 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 $ε$ using $\mathsf{poly}(n,2^t,1/ε)$ 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. |
| title | Efficient Learning of Quantum States Prepared With Few Non-Clifford Gates II: Single-Copy Measurements |
| topic | Quantum Physics Machine Learning |
| url | https://arxiv.org/abs/2308.07175 |