POPQC: Parallel Optimization for Quantum Circuits (Extended Version)
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866911007582978048 |
|---|---|
| author | Liu, Pengyu Arora, Jatin Xu, Mingkuan Acar, Umut A. |
| author_facet | Liu, Pengyu Arora, Jatin Xu, Mingkuan Acar, Umut A. |
| contents | Optimization of quantum programs or circuits is a fundamental problem in quantum computing and remains a major challenge. State-of-the-art quantum circuit optimizers rely on heuristics and typically require superlinear, and even exponential, time. Recent work proposed a new approach that pursues a weaker form of optimality called local optimality. Parameterized by a natural number $Ω$, local optimality insists that each and every $Ω$-segment of the circuit is optimal with respect to an external optimizer, called the oracle. Local optimization can be performed using only a linear number of calls to the oracle but still incurs quadratic computational overheads in addition to oracle calls. Perhaps most importantly, the algorithm is sequential.
In this paper, we present a parallel algorithm for local optimization of quantum circuits. To ensure efficiency, the algorithm operates by keeping a set of fingers into the circuit and maintains the invariant that a $Ω$-deep circuit needs to be optimized only if it contains a finger. Operating in rounds, the algorithm selects a set of fingers, optimizes in parallel the segments containing the fingers, and updates the finger set to ensure the invariant. For constant $Ω$, we prove that the algorithm requires $O(n\lg{n})$ work and $O(r\lg{n})$ span, where $n$ is the circuit size and $r$ is the number of rounds. We prove that the optimized circuit returned by the algorithm is locally optimal in the sense that any $Ω$-segment of the circuit is optimal with respect to the oracle. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_13720 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | POPQC: Parallel Optimization for Quantum Circuits (Extended Version) Liu, Pengyu Arora, Jatin Xu, Mingkuan Acar, Umut A. Distributed, Parallel, and Cluster Computing Quantum Physics Optimization of quantum programs or circuits is a fundamental problem in quantum computing and remains a major challenge. State-of-the-art quantum circuit optimizers rely on heuristics and typically require superlinear, and even exponential, time. Recent work proposed a new approach that pursues a weaker form of optimality called local optimality. Parameterized by a natural number $Ω$, local optimality insists that each and every $Ω$-segment of the circuit is optimal with respect to an external optimizer, called the oracle. Local optimization can be performed using only a linear number of calls to the oracle but still incurs quadratic computational overheads in addition to oracle calls. Perhaps most importantly, the algorithm is sequential. In this paper, we present a parallel algorithm for local optimization of quantum circuits. To ensure efficiency, the algorithm operates by keeping a set of fingers into the circuit and maintains the invariant that a $Ω$-deep circuit needs to be optimized only if it contains a finger. Operating in rounds, the algorithm selects a set of fingers, optimizes in parallel the segments containing the fingers, and updates the finger set to ensure the invariant. For constant $Ω$, we prove that the algorithm requires $O(n\lg{n})$ work and $O(r\lg{n})$ span, where $n$ is the circuit size and $r$ is the number of rounds. We prove that the optimized circuit returned by the algorithm is locally optimal in the sense that any $Ω$-segment of the circuit is optimal with respect to the oracle. |
| title | POPQC: Parallel Optimization for Quantum Circuits (Extended Version) |
| topic | Distributed, Parallel, and Cluster Computing Quantum Physics |
| url | https://arxiv.org/abs/2506.13720 |