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Add 31 PRBench task specifications (instructions, task.yaml, paper markdown; ground truth withheld)
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# 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_wang_2015
# --- Paper Info ---
paper:
title: "Quantum Computation under Micromotion in a Planar Ion Crystal"
author: "S.-T. Wang, C. Shen, L.-M. Duan"
doi: "10.1038/srep08555"
year: 2015
paper_file: "MicroOf2DTrap.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/Raman_Segments.py"
data:
- "data/Balance_place_of_ions.csv"
- "data/normal_frequancy.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 planar ion trap physics,
Mathieu equation, pseudopotential, micromotion effects, 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 2D equilibrium position solver, normal mode eigenvalue problem with
micromotion corrections, and segment optimization?
- 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 (30pts), Normal frequencies (30pts), Segments (40pts).
- name: "completeness"
weight: 0.15
description: >
Are all 3 CSV files, all 4 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/Raman_Segments.py"
grading:
dimensions:
- name: "methodology_understanding"
weight: 0.25
description: >
Does ANALYSIS.md correctly describe the planar ion trap physics,
Mathieu equation, micromotion, 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:
- 2D equilibrium position solver with Mathieu parameters
- Normal mode eigenvalue problem with micromotion corrections
- 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 4 code files and the ANALYSIS.md present and non-trivial?