Scalable quantum circuits for $n$-qubit unitary matrices
Fuente:
arXiv
Salvato in:
| Autori principali: | , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2023
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866914640804446208 |
|---|---|
| author | Sarkar, Rohit Sarma Adhikari, Bibhas |
| author_facet | Sarkar, Rohit Sarma Adhikari, Bibhas |
| contents | This work presents an optimization-based scalable quantum neural network framework for approximating $n$-qubit unitaries through generic parametric representation of unitaries, which are obtained as product of exponential of basis elements of a new basis that we propose as an alternative to Pauli string basis. We call this basis as the Standard Recursive Block Basis, which is constructed using a recursive method, and its elements are permutation-similar to block Hermitian unitary matrices. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2304_14096 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Scalable quantum circuits for $n$-qubit unitary matrices Sarkar, Rohit Sarma Adhikari, Bibhas Quantum Physics Hardware Architecture Mathematical Physics This work presents an optimization-based scalable quantum neural network framework for approximating $n$-qubit unitaries through generic parametric representation of unitaries, which are obtained as product of exponential of basis elements of a new basis that we propose as an alternative to Pauli string basis. We call this basis as the Standard Recursive Block Basis, which is constructed using a recursive method, and its elements are permutation-similar to block Hermitian unitary matrices. |
| title | Scalable quantum circuits for $n$-qubit unitary matrices |
| topic | Quantum Physics Hardware Architecture Mathematical Physics |
| url | https://arxiv.org/abs/2304.14096 |