doi.org/10.1109/QCE49297.2020.00036

Preview meta tags from the doi.org website.

Linked Hostnames

2

Thumbnail

Search Engine Appearance

Google

https://doi.org/10.1109/QCE49297.2020.00036

Towards Optimal Topology Aware Quantum Circuit Synthesis

We present an algorithm for compiling arbitrary unitaries into a sequence of gates native to a quantum processor. As CNOT gates are error-prone for the foreseeable Noisy-Intermediate-Scale Quantum devices era, our A* inspired algorithm minimizes their count while accounting for connectivity. We discuss the formulation of synthesis as a search problem as well as an algorithm to find solutions. For a workload of circuits with complexity appropriate for the NISQ era, we produce solutions well within the best upper bounds published in literature and match or exceed hand tuned implementations, as well as other existing synthesis alternatives. In particular, when comparing against state-of-the-art available synthesis packages we show 2.4× average (up to 5.3×) reduction in CNOT count. We also show how to re-target the algorithm for a different chip topology and native gate set while obtaining similar quality results. We believe that tools like ours can facilitate algorithmic exploration and guide gate set discovery for quantum processor designers, as well as being useful for optimization in the quantum compilation tool-chain.



Bing

Towards Optimal Topology Aware Quantum Circuit Synthesis

https://doi.org/10.1109/QCE49297.2020.00036

We present an algorithm for compiling arbitrary unitaries into a sequence of gates native to a quantum processor. As CNOT gates are error-prone for the foreseeable Noisy-Intermediate-Scale Quantum devices era, our A* inspired algorithm minimizes their count while accounting for connectivity. We discuss the formulation of synthesis as a search problem as well as an algorithm to find solutions. For a workload of circuits with complexity appropriate for the NISQ era, we produce solutions well within the best upper bounds published in literature and match or exceed hand tuned implementations, as well as other existing synthesis alternatives. In particular, when comparing against state-of-the-art available synthesis packages we show 2.4× average (up to 5.3×) reduction in CNOT count. We also show how to re-target the algorithm for a different chip topology and native gate set while obtaining similar quality results. We believe that tools like ours can facilitate algorithmic exploration and guide gate set discovery for quantum processor designers, as well as being useful for optimization in the quantum compilation tool-chain.



DuckDuckGo

https://doi.org/10.1109/QCE49297.2020.00036

Towards Optimal Topology Aware Quantum Circuit Synthesis

We present an algorithm for compiling arbitrary unitaries into a sequence of gates native to a quantum processor. As CNOT gates are error-prone for the foreseeable Noisy-Intermediate-Scale Quantum devices era, our A* inspired algorithm minimizes their count while accounting for connectivity. We discuss the formulation of synthesis as a search problem as well as an algorithm to find solutions. For a workload of circuits with complexity appropriate for the NISQ era, we produce solutions well within the best upper bounds published in literature and match or exceed hand tuned implementations, as well as other existing synthesis alternatives. In particular, when comparing against state-of-the-art available synthesis packages we show 2.4× average (up to 5.3×) reduction in CNOT count. We also show how to re-target the algorithm for a different chip topology and native gate set while obtaining similar quality results. We believe that tools like ours can facilitate algorithmic exploration and guide gate set discovery for quantum processor designers, as well as being useful for optimization in the quantum compilation tool-chain.

  • General Meta Tags

    12
    • title
      Towards Optimal Topology Aware Quantum Circuit Synthesis | IEEE Conference Publication | IEEE Xplore
    • google-site-verification
      qibYCgIKpiVF_VVjPYutgStwKn-0-KBB6Gw4Fc57FZg
    • Description
      We present an algorithm for compiling arbitrary unitaries into a sequence of gates native to a quantum processor. As CNOT gates are error-prone for the foreseea
    • Content-Type
      text/html; charset=utf-8
    • viewport
      width=device-width, initial-scale=1.0
  • Open Graph Meta Tags

    3
    • og:image
      https://ieeexplore.ieee.org/assets/img/ieee_logo_smedia_200X200.png
    • og:title
      Towards Optimal Topology Aware Quantum Circuit Synthesis
    • og:description
      We present an algorithm for compiling arbitrary unitaries into a sequence of gates native to a quantum processor. As CNOT gates are error-prone for the foreseeable Noisy-Intermediate-Scale Quantum devices era, our A* inspired algorithm minimizes their count while accounting for connectivity. We discuss the formulation of synthesis as a search problem as well as an algorithm to find solutions. For a workload of circuits with complexity appropriate for the NISQ era, we produce solutions well within the best upper bounds published in literature and match or exceed hand tuned implementations, as well as other existing synthesis alternatives. In particular, when comparing against state-of-the-art available synthesis packages we show 2.4× average (up to 5.3×) reduction in CNOT count. We also show how to re-target the algorithm for a different chip topology and native gate set while obtaining similar quality results. We believe that tools like ours can facilitate algorithmic exploration and guide gate set discovery for quantum processor designers, as well as being useful for optimization in the quantum compilation tool-chain.
  • Twitter Meta Tags

    1
    • twitter:card
      summary
  • Link Tags

    9
    • canonical
      https://ieeexplore.ieee.org/document/9259942/
    • icon
      /assets/img/favicon.ico
    • stylesheet
      https://ieeexplore.ieee.org/assets/css/osano-cookie-consent-xplore.css
    • stylesheet
      /assets/css/simplePassMeter.min.css?cv=20250923_00000
    • stylesheet
      /assets/dist/ng-new/styles.css?cv=20250923_00000

Links

17