# 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_fu_2001

# --- Paper Info ---
paper:
  title: "Classical collisional trajectories as the source of strong-field double ionization of helium in the knee regime"
  author: "L. B. Fu, J. Liu, J. Chen, S. G. Chen"
  doi: "10.1103/PhysRevA.63.043416"
  year: 2001
  paper_file: "fu2001.md"               # relative to task dir

# --- Files ---
instruction_file: "instruction.md"       # what the white agent receives (no ground truth)
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/fig3_knee_structure.py"
  data:
    - "data/fig3_knee_structure.csv"

# --- Docker Environment ---
docker:
  image: "python:3.11-slim"
  memory_limit: "4g"
  timeout: 21600                        # 6 hours max (Monte Carlo over 13 intensity points)
  pip_install:
    - numpy
    - scipy
    - matplotlib

# --- Grading Rubric (for model-judge) ---
grading:
  dimensions:
    - name: "methodology_understanding"
      weight: 0.20
      description: >
        Does the agent's ANALYSIS.md correctly describe the quasistatic CTMC model,
        ADK tunneling rate, microcanonical distribution for the inner electron,
        Kustaanheimo-Stiefel regularization, and ionization classification?
        Compare against metadata.md.
    - name: "code_correctness"
      weight: 0.15
      description: >
        Is the CTMC implementation correct? Check laser field envelope, ADK weight
        computation, KS regularization, adaptive RK integration, and SI/DI classification
        based on single-particle energies.
    - name: "data_accuracy"
      weight: 0.50
      description: >
        How well does the generated CSV match the ground truth reference data?
        CTMC is stochastic so allow factor-of-3 relative tolerance on individual points.
        Key checks: He2+/He+ ratio plateau at ~0.002 for I > 1e15 W/cm2,
        monotonically increasing DI yield, correct qualitative knee structure.
    - name: "completeness"
      weight: 0.15
      description: >
        Is the CSV file, the code file, and the ANALYSIS.md present?
        Is the data file non-trivial (13 rows, correct column names)?

# --- 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 Monte Carlo simulation 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/fig3_knee_structure.py"

  grading:
    dimensions:
      - name: "methodology_understanding"
        weight: 0.25
        description: >
          Does ANALYSIS.md correctly describe the two-step CTMC model:
          ADK tunneling (Step 1) and classical trajectory propagation (Step 2)?
          Are the KS regularization and microcanonical sampling correctly described?
      - name: "code_correctness"
        weight: 0.50
        description: >
          Read the code carefully. Check whether the implementation is
          physically and algorithmically correct:
          - Total potential: V = -Z/r1 - Z/r2 + 1/|r1-r2| + (r1+r2)·F(t)
          - Laser field: F(t) = a(t)*F*cos(omega*t) with flat-top + cos^2 ramp
          - Microcanonical sampling at E2 = -2 a.u.
          - ADK weight: w = w^(0) * w^(1) where w^(1) has Gaussian transverse factor
          - KS map: x = u1^2-u2^2-u3^2+u4^2, etc., with dt/ds = r
          - SI: E1>0 AND E2<0; DI: E1>0 AND E2>0
          - Yield: weighted sum DI/all
          Compare against ground truth formulas in metadata. Flag any bugs.
      - name: "code_quality"
        weight: 0.10
        description: >
          Is the code well-structured and readable? Is the CTMC pipeline
          clearly separated into laser, sampling, propagation, and classification modules?
      - name: "completeness"
        weight: 0.15
        description: >
          Are the code file and the ANALYSIS.md present and non-trivial?