Design and execution of quantum circuits using tens of superconducting qubits and thousands of gates for dense Ising optimization problems
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866914948169334784 |
|---|---|
| author | Maciejewski, Filip B. Hadfield, Stuart Hall, Benjamin Hodson, Mark Dupont, Maxime Evert, Bram Sud, James Alam, M. Sohaib Wang, Zhihui Jeffrey, Stephen Sundar, Bhuvanesh Lott, P. Aaron Grabbe, Shon Rieffel, Eleanor G. Reagor, Matthew J. Venturelli, Davide |
| author_facet | Maciejewski, Filip B. Hadfield, Stuart Hall, Benjamin Hodson, Mark Dupont, Maxime Evert, Bram Sud, James Alam, M. Sohaib Wang, Zhihui Jeffrey, Stephen Sundar, Bhuvanesh Lott, P. Aaron Grabbe, Shon Rieffel, Eleanor G. Reagor, Matthew J. Venturelli, Davide |
| contents | We develop a hardware-efficient ansatz for variational optimization, derived from existing ansatze in the literature, that parametrizes subsets of all interactions in the Cost Hamiltonian in each layer. We treat gate orderings as a variational parameter and observe that doing so can provide significant performance boosts in experiments. We carried out experimental runs of a compilation-optimized implementation of fully-connected Sherrington-Kirkpatrick Hamiltonians on a 50-qubit linear-chain subsystem of Rigetti Aspen-M-3 transmon processor. Our results indicate that, for the best circuit designs tested, the average performance at optimized angles and gate orderings increases with circuit depth (using more parameters), despite the presence of a high level of noise. We report performance significantly better than using a random guess oracle for circuits involving up to approx 5000 two-qubit and approx 5000 one-qubit native gates. We additionally discuss various takeaways of our results toward more effective utilization of current and future quantum processors for optimization. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2308_12423 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Design and execution of quantum circuits using tens of superconducting qubits and thousands of gates for dense Ising optimization problems Maciejewski, Filip B. Hadfield, Stuart Hall, Benjamin Hodson, Mark Dupont, Maxime Evert, Bram Sud, James Alam, M. Sohaib Wang, Zhihui Jeffrey, Stephen Sundar, Bhuvanesh Lott, P. Aaron Grabbe, Shon Rieffel, Eleanor G. Reagor, Matthew J. Venturelli, Davide Quantum Physics Emerging Technologies We develop a hardware-efficient ansatz for variational optimization, derived from existing ansatze in the literature, that parametrizes subsets of all interactions in the Cost Hamiltonian in each layer. We treat gate orderings as a variational parameter and observe that doing so can provide significant performance boosts in experiments. We carried out experimental runs of a compilation-optimized implementation of fully-connected Sherrington-Kirkpatrick Hamiltonians on a 50-qubit linear-chain subsystem of Rigetti Aspen-M-3 transmon processor. Our results indicate that, for the best circuit designs tested, the average performance at optimized angles and gate orderings increases with circuit depth (using more parameters), despite the presence of a high level of noise. We report performance significantly better than using a random guess oracle for circuits involving up to approx 5000 two-qubit and approx 5000 one-qubit native gates. We additionally discuss various takeaways of our results toward more effective utilization of current and future quantum processors for optimization. |
| title | Design and execution of quantum circuits using tens of superconducting qubits and thousands of gates for dense Ising optimization problems |
| topic | Quantum Physics Emerging Technologies |
| url | https://arxiv.org/abs/2308.12423 |