Chook

Version 0.2.0 (Release date: March 21, 2021)

License

This software is shared under an Apache License (attached). We ask you to please cite the paper if you choose to use chook. Thank you.

Description

Chook is a comprehensive suite for generating binary optimization problems with planted solutions. Chook currently supports the following problem types:

• Tile planting (2D/3D)
• Wishart planting
• Deceptive cluster loops (DCL)
• Equation planting (k-regular k-XORSAT)
• k-local planting

Requirements

You will need Python 3.4 or later to run Chook.

Installation

One can install Chook using the Python package manager pip:

pip install chook

Alternatively, Chook can be downloaded from GitHub and can be installed as follows:

cd <path_to_repo>
python setup.py install

Usage

chook problem_type config_file [-h] [-n num_instances] [-o output_format] [-f file_format] 

Required arguments

• problem_type: Choose the type of problems to be generated. Allowed options: {TP, WP, DCL, XORSAT, K_LOCAL}

  • TP : Tile planting (2D/3D)
  • WP : Wishart planting
  • DCL : Deceptive cluster loops (DCL)
  • XORSAT : Equation planting (k-regular k-XORSAT)
  • K_LOCAL : k-local planting

• config_file: Configuration file containing problem-type specific parameters. Refer the provided params.in file for an example.

Optional arguments

• -n num_instances
  The number of problem instances to be generated (default: 10)
• -o output_format
  Output format: ising/hobo (default: ising)
• -f file_format
  File format: txt/json (default: txt)
• -h, --help
  Show this help message and exit

The generated instances will be stored as text/JSON files in a subdirectory within the current working directory. The ground state energies will be recorded in a separate text file gs_energies.txt. For XORSAT problems, gs_energies.txt will also contain the ground state degeneracies.