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Reproduce arXiv:1709.01662 #70

Description

@refraction-ray

1. Paper Information

2. Reproduction Goal

Which specific figure or table from the paper needs to be reproduced?

  • Target: Fig. 3

  • Expected Metric/Result:

  • Allow to reduce the problem size compared to the paper: Yes

3. Directory Structure Plan

To keep the repository organized, please strictly follow this folder structure:

  • Proposed Folder Name: examples/reproduce_papers/<YYYY>_<Keywords>/
    • Naming Convention: Year_Keywords (snake_case)
    • Example: examples/reproduce_papers/2023_quantum_transformer/

4. Metadata Definition (meta.yaml)

Please provide the content for the meta.yaml file that will be placed in the folder.

Contributors/AI: Copy and fill this block directly into the meta.yaml file.

title: ""
arxiv_id: ""
url: ""
year: 
authors: 
  - ""
  - ""
tags:
  - ""
  - ""
hardware_requirements:
  gpu: False
  min_memory: ""
description: ""
outputs:
  - target: "Figure 3"
    path: result.png
    script: "main.py"

5. Implementation Requirements

For AI Assistants / Contributors: Please strictly follow the rules below.

  • Docstring Standard:

    • The file MUST start with a docstring containing the paper title and the link.
      Format example:

      """
      Reproduction of "Paper Title"
      Link: https://arxiv.org/abs/xxxx.xxxxx
      
      Description:
      This script reproduces Figure 3 from the paper using TensorCircuit-NG.
      """
  • Outputs:
    The reproduced data and figures should be in outputs/ subfolder.

  • Subfolder structure:

    examples/reproduce_papers/<YYYY>_<Keywords>/
    ├── meta.yaml
    ├── main.py
    ├── ...       # models, data, etc.
    └── outputs/
        ├── result.png    # used for gallery
        └── ...           # other outputs if necessary
    
  • Code Quality & Linter:

    • Formatter: The code must be formatted using black.
    • Linter: The code must pass pylint checks (clean code, handle errors).
    • Type Hints: Standard type is NOT REQUIRED.
  • Dependencies:

    • Use tensorcircuit as the main framework.
    • Use matplotlib for plotting if necessary.

6. Verification

To be considered complete, please provide:

  1. A screenshot of the generated plot or the terminal output matching the paper's result.
  2. Confirmation that black and pylint have been run.
# Example verification commands
black examples/reproduce_papers/<paper_subfolder>/*.py
pylint examples/reproduce_papers/<paper_subfolder>/*.py

7. Checklist

  • I have checked that this paper hasn't been reproduced in the repo yet.

  • The script is self-contained and runnable.

  • The docstring includes the correct arXiv/DOI link.

  • black formatting applied.

  • pylint check passed.

Activity

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