Qompose: A Technique to Select Optimal Algorithm- Specific Layout for Neutral Atom Quantum Architectures

Fuente: arXiv
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Main Authors: Silver, Daniel, Patel, Tirthak, Tiwari, Devesh
Format: Preprint
Published: 2024
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author Silver, Daniel
Patel, Tirthak
Tiwari, Devesh
author_facet Silver, Daniel
Patel, Tirthak
Tiwari, Devesh
contents As quantum computing architecture matures, it is important to investigate new technologies that lend unique advantages. In this work, we propose, Qompose, a neutral atom quantum computing framework for efficiently composing quantum circuits on 2-D topologies of neutral atoms. Qompose selects an efficient topology for any given circuit in order to optimize for length of execution through efficient parallelism and for overall fidelity. our extensive evaluation demonstrates the Qompose is effective for a large collection of randomly-generated quantum circuits and a range of real-world benchmarks including VQE, ISING, and QAOA.
format Preprint
id arxiv_https___arxiv_org_abs_2409_19820
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Qompose: A Technique to Select Optimal Algorithm- Specific Layout for Neutral Atom Quantum Architectures
Silver, Daniel
Patel, Tirthak
Tiwari, Devesh
Quantum Physics
Artificial Intelligence
As quantum computing architecture matures, it is important to investigate new technologies that lend unique advantages. In this work, we propose, Qompose, a neutral atom quantum computing framework for efficiently composing quantum circuits on 2-D topologies of neutral atoms. Qompose selects an efficient topology for any given circuit in order to optimize for length of execution through efficient parallelism and for overall fidelity. our extensive evaluation demonstrates the Qompose is effective for a large collection of randomly-generated quantum circuits and a range of real-world benchmarks including VQE, ISING, and QAOA.
title Qompose: A Technique to Select Optimal Algorithm- Specific Layout for Neutral Atom Quantum Architectures
topic Quantum Physics
Artificial Intelligence
url https://arxiv.org/abs/2409.19820