# PRBench Task Configuration
# Each paper has one task.yaml that contains ALL task-specific information.
# Agent code is fully generic and reads everything from this file.

task_id: task_wu_2018

# --- Paper Info ---
paper:
  title: "Noise analysis for high-fidelity quantum entangling gates in an anharmonic linear Paul trap"
  author: "Yukai Wu, Sheng-Tao Wang, L.-M. Duan"
  doi: "10.1103/PhysRevA.97.062325"
  year: 2018
  paper_file: "GateOfLinearTrap.md"           # relative to task dir

# --- Files ---
instruction_file: "instruction.md"              # what the white agent receives
metadata_file: "metadata.md"                   # ground truth formulas + methodology (for grading)
ground_truth_data_dir: "data"                  # directory with reference CSV files
ground_truth_code_dir: "reproduction"

# --- Expected Outputs (what the white agent must produce) ---
expected_outputs:
  analysis:
    - "reproduction/ANALYSIS.md"
  code:
    - "reproduction/GateOfLinearTrap.py"
    - "reproduction/Balance_place_of_ions.py"
    - "reproduction/normal_frequancy.py"
    - "reproduction/infidelity_of_mu.py"
    - "reproduction/Raman_Segments.py"
  data:
    - "data/Balance_place_of_ions.csv"
    - "data/normal_frequancy.csv"
    - "data/infidelity_of_mu.csv"
    - "data/Segments.csv"

# --- Docker Environment ---
docker:
  image: "python:3.11-slim"
  memory_limit: "4g"
  timeout: 10800                         # 3 hours max
  pip_install:
    - numpy
    - scipy
    - matplotlib

# --- Grading Rubric (for model-judge) ---
grading:
  dimensions:
    - name: "methodology_understanding"
      weight: 0.15
      description: >
        Does the agent's ANALYSIS.md correctly describe the ion trap physics,
        equilibrium position calculation, normal mode analysis, and gate optimization
        methodology? Compare against metadata.md.
    - name: "code_correctness"
      weight: 0.15
      description: >
        Are all required code files present? Does the code correctly implement
        the balance position solver (Newton's method), normal mode eigenvalue problem,
        infidelity computation, and Lagrange multiplier optimization for segments?
    - name: "data_accuracy"
      weight: 0.55
      description: >
        How well do the generated CSV data files match the ground truth reference data?
        Compare numerical values with ~10% relative tolerance. Check that column names
        match, row counts are reasonable, and values are in the correct range.
        Weights: Balance positions (10pts), Normal frequencies (20pts),
        Infidelity of mu (40pts), Segments (30pts).
    - name: "completeness"
      weight: 0.15
      description: >
        Are all 4 CSV files, all 5 code files, and the ANALYSIS.md present?
        Are the files non-trivial (not empty/placeholder)?

# --- Code-Only Evaluation Mode ---
code_only:
  instruction_suffix: |
    ## IMPORTANT: Code-Only Mode

    In this task you are in **code-only mode**. You must:
    1. Read and analyze the paper
    2. Write `reproduction/ANALYSIS.md` with your methodology analysis
    3. Implement ALL code files under `reproduction/`
    4. **DO NOT** run the scripts or generate CSV data files
    5. Focus on writing correct, complete, and well-structured code

    Your deliverables are ONLY the analysis document and code files.
    Do NOT produce any CSV data files.

  expected_outputs:
    analysis:
      - "reproduction/ANALYSIS.md"
    code:
      - "reproduction/GateOfLinearTrap.py"
      - "reproduction/Balance_place_of_ions.py"
      - "reproduction/normal_frequancy.py"
      - "reproduction/infidelity_of_mu.py"
      - "reproduction/Raman_Segments.py"

  grading:
    dimensions:
      - name: "methodology_understanding"
        weight: 0.25
        description: >
          Does ANALYSIS.md correctly describe the ion trap physics,
          equilibrium position calculation, normal mode analysis, and
          gate optimization methodology?
      - name: "code_correctness"
        weight: 0.50
        description: >
          Read every code file carefully. Check whether the implementation is
          physically and algorithmically correct:
          - Equilibrium position solver with anharmonic potential
          - Normal mode eigenvalue problem (x/y/z directions)
          - Infidelity computation as function of mu
          - Segment optimization via Lagrange multiplier
          Compare against ground truth formulas in metadata.
      - name: "code_quality"
        weight: 0.10
        description: >
          Is the code well-structured, readable, and does it follow the
          expected file organization?
      - name: "completeness"
        weight: 0.15
        description: >
          Are all 5 code files and the ANALYSIS.md present and non-trivial?