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  3. 飞桨学习赛:量子电路合成
Baidu AI StudioGeneral MLBeginnerRegistration unverified

飞桨学习赛:量子电路合成

A beginner general ml competition requiring roughly 4–12 hours for an end-to-end practice run.

Difficulty
Beginner
Estimated effort
4–12 hours
Registration deadline
To be confirmed
Compute
CPU only
OverviewResourcesPreparationSource

Overview

Who this competition fits

适合已经了解量子比特、实数酉矩阵、$R_y$ 与 CNOT 门,并能用 PaddlePaddle 2.0 及以上版本完成端到端模型的个人参赛者。前几题有固定电路结构可练习,但想取得较高总分的人需要能处理无结构的三、四和八量子比特电路分解。

Read the original official blurb
量子电路合成是量子计算中十分重要的问题,对于实现量子计算机有指导意义。本次比赛以量子电路合成为题,旨在让参赛者了解并掌握如何使用给定量子门集合来高效的近似合成目标量子门,加深对量子计算的认识。 Official tags: 量子计算. Sign-ups: 67.

Resources

What this competition gives you

Taken from the competition's official page.

  • DataQuestion 2 input: a 4×4 real unitary matrix
  • DataQuestion 3 input: an 8×8 real unitary matrix
  • DataQuestion 4 input: an 8×8 real unitary matrix
  • DataQuestion 5 input: a 16×16 real unitary matrix
  • TutorialSelected project by bnpzsx
  • TutorialSelected project by Mr.郑先生_
  • TutorialSelected project by Jhong1996
  • TutorialSelected project by 伽利略
  • TutorialSelected project by yanggh
  • TutorialSelected project by Sqhttwl
  • TutorialSelected project by 红白黑
  • TutorialPaddle Quantum official materials repository
  • TutorialQuantum computing quick reference manual

Preparation

From registration to a first submission

  1. 01

    PaddlePaddle 2.0

  2. 02

    量子电路基础

  3. 03

    实数酉矩阵

  4. 04

    线性代数与张量积

  5. 05

    量子门保真度计算

  6. 06

    文本格式化输出

Before you commit: 主要难点是为无预设结构的目标酉矩阵设计电路:既要提高与目标矩阵的保真度,又要压低 $R_y$ 和 CNOT 门数量,因为门数会直接计入代价并影响得分。八量子比特题的目标矩阵为 $256\times256$,且占总题目分值的主要部分,电路搜索与验证工作会最重。

Source

How this page was assembled

Competition information is structured from the official page. Scores are platform estimates for decision support; official rules take precedence.

Official competition page
Baidu AI Studio
Last checked
Not recorded

Entry assessment

est.
78

Worth shortlisting

Overall fit estimate

Beginner fit78/100
Learning value72/100

Confirm eligibility and time commitment before moving into formal preparation.

Entry eligibility needs official confirmation

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Data and review state

Separate what is confirmed from what still needs review. Official rules and deadlines win.

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Source page verifiedMetric confirmedReviewed
Published on this site
Jul 21, 2026

Official metric is not published on the Baidu AI Studio competition listing; verify scoring on the competition page.